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+# About Dataset
+Explore the intricate dance between gold prices and key economic events across major global players – Canada, Japan, USA, Russia, European Union, and China. This comprehensive dataset spans from January 2019 to December 2023, offering a nuanced analysis of how economic news from these influential regions impacts the ever-volatile gold market. Delve into the ebb and flow of financial landscapes, uncovering trends, correlations, and invaluable insights for strategic decision-making in the dynamic world of investments.
+
+## Historical Gold Price Dataset:
+
+* Day: The day of the week when the data was recorded.
+* Date: The specific date corresponding to the recorded gold price.
+* Hour: The time of day when the gold price was recorded.
+* Country: The country associated with the economic event or news affecting gold prices.
+* Event: The economic event or news that potentially influenced gold prices.
+* Actual: The actual reported value or figure related to the economic event.
+* Previous: The previously reported value or figure for the same economic event.
+* Consensus: The consensus forecast or expected value for the economic event.
+* Forecast: The forecasted value or figure for the economic event.
+
+## Economic Calendar Dataset:
+
+* Day: The day of the week when the economic event is scheduled.
+* Date: The specific date when the economic event is expected to occur.
+* Hour: The time of day when the economic event is scheduled.
+* Country: The country associated with the economic event.
+* Event: The specific economic event or news scheduled to take place.
+* Actual: The actual reported value or figure related to the economic event.
+* Previous: The previously reported value or figure for the same economic event.
+* Consensus: The consensus forecast or expected value for the economic event.
+* Forecast: The forecasted value or figure for the economic event.
+
+## Sentiment Labeled Data:
+* Date: The specific date when the economic event is expected to occur
+* Price: The price of Gold in Dollars(US) on that particular Date.
+* Vol_K: Volume of the Gold traded.
+* Change_percent: The percentage of change in the Previous and Actual
+* Country: The country associated with the economic event
+* Event: The specific economic event or news scheduled to take place.
+* D_Consensus: The difference in the Previous Consensus and Actual Consensus.
+* D_Forecast: The difference in the Previous Forecast and Actual Forecast.
+* Sentiment: The Sentiment (Positive, Negative, Neutral) assigned to the event based on the Change_Percent.
\ No newline at end of file
diff --git a/The Effect of Economic News on Gold Prices Analysis/Dataset/economic_calendar_19_24.csv b/The Effect of Economic News on Gold Prices Analysis/Dataset/economic_calendar_19_24.csv
new file mode 100644
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+Day,Date,Hour,Country,Event,Actual,Previous,Consensus,Forecast
+Tuesday,01/01/19,20:45,CN,Caixin Manufacturing PMI DEC,49.7,50.2,50.1,50.1
+Friday,01/04/19,8:30,US,Non Farm Payrolls DEC,312K,176K,177K,165K
+Sunday,01/06/19,,CN,US-China Trade Talks,,,,
+Monday,01/07/19,10:00,CA,Ivey PMI s.a DEC,59.7,57.2,56.8,56.7
+Monday,01/07/19,,CN,US-China Trade Talks,,,,
+Tuesday,01/08/19,0:00,JP,Consumer Confidence DEC,42.7,42.9,,42
+Tuesday,01/08/19,5:00,EA,Business Confidence DEC,0.82,1.04,0.99,1.1
+Tuesday,01/08/19,8:30,CA,Balance of Trade NOV,-2.06B,-0.85B,-1.95B,
+Wednesday,01/09/19,20:30,CN,Inflation Rate YoY DEC,0.019,2.20%,0.021,0.022
+Friday,01/11/19,4:30,GB,Balance of Trade NOV,-2.904B,-3.037B,, -2.2B
+Friday,01/11/19,8:30,US,Core Inflation Rate YoY DEC,0.022,2.20%,0.022,0.022
+Friday,01/11/19,8:30,US,Inflation Rate YoY DEC,0.019,2.20%,0.019,0.022
+Wednesday,01/16/19,4:30,GB,Inflation Rate YoY DEC,0.021,2.30%,0.021,0.022
+Thursday,01/17/19,18:30,JP,Inflation Rate YoY DEC,0.003,0.80%,0.003,0.006
+Friday,01/18/19,8:30,CA,Inflation Rate YoY DEC,0.02,1.70%,0.017,0.017
+Tuesday,01/22/19,4:30,GB,Claimant Count Change DEC,20.8K,24.8K,20K,10K
+Tuesday,01/22/19,18:50,JP,Balance of Trade DEC,-55B,-738B,-29.5B,-25B
+Wednesday,01/30/19,0:00,JP,Consumer Confidence JAN,41.9,42.7,42.5,42.4
+Wednesday,01/30/19,5:00,EA,Business Confidence JAN,0.69,0.86,0.75,0.75
+Wednesday,01/30/19,19:01,GB,Gfk Consumer Confidence JAN,-14,-14,-15,-16
+Wednesday,01/30/19,20:00,CN,NBS Manufacturing PMI JAN,49.5,49.4,49.3,49.8
+Thursday,01/31/19,20:45,CN,Caixin Manufacturing PMI JAN,48.3,49.7,49.5,50
+Friday,02/01/19,8:30,US,Non Farm Payrolls JAN,304K,222K,165K,170K
+Wednesday,02/06/19,8:30,US,Balance of Trade NOV,-49.3B,-55.7B,-54B,-53B
+Wednesday,02/06/19,10:00,CA,Ivey PMI s.a JAN,54.7,59.7,56,58
+Monday,02/11/19,4:30,GB,Balance of Trade DEC,-3.229B,-3.615B,, -1.9B
+Wednesday,02/13/19,4:30,GB,Inflation Rate YoY JAN,0.018,2.10%,0.019,0.02
+Wednesday,02/13/19,8:30,US,Core Inflation Rate YoY JAN,0.022,2.20%,0.021,0.02
+Wednesday,02/13/19,8:30,US,Inflation Rate YoY JAN,0.016,1.90%,0.015,0.019
+Thursday,02/14/19,8:30,US,Retail Sales MoM DEC,-0.012,0.10%,0.002,0.003
+Thursday,02/14/19,20:30,CN,Inflation Rate YoY JAN,0.017,1.90%,0.019,0.019
+Tuesday,02/19/19,4:30,GB,Claimant Count Change JAN,14.2K,20.2K,2.7K,5.1K
+Tuesday,02/19/19,18:50,JP,Balance of Trade JAN,-1415B,-57B,-1011B,-1000B
+Thursday,02/21/19,8:30,US,Durable Goods Orders MoM DEC,0.012,1%,0.015,0.025
+Thursday,02/21/19,18:30,JP,Inflation Rate YoY JAN,0.002,0.30%,0.002,0.005
+Wednesday,02/27/19,5:00,EA,Business Confidence FEB,0.69,0.69,0.6,0.61
+Wednesday,02/27/19,8:30,CA,Inflation Rate YoY JAN,0.014,2%,0.015,0.018
+Wednesday,02/27/19,19:01,GB,Gfk Consumer Confidence FEB,-13,-14,-15,-17
+Wednesday,02/27/19,20:00,CN,NBS Manufacturing PMI FEB,49.2,49.5,49.5,49.8
+Thursday,02/28/19,20:45,CN,Caixin Manufacturing PMI FEB,49.9,48.3,48.5,49
+Friday,03/01/19,0:00,JP,Consumer Confidence FEB,41.5,41.9,41.6,41.3
+Friday,03/01/19,8:30,US,Personal Income MoM DEC,0.01,0.30%,0.004,0.004
+Friday,03/01/19,8:30,US,Personal Income MoM JAN,-0.001,1%,0.003,0.003
+Friday,03/01/19,8:30,US,Personal Spending MoM DEC,-0.005,0.60%,-0.002,-0.002
+Monday,03/04/19,,CN,National People’s Congress,,,,
+Wednesday,03/06/19,8:30,CA,Balance of Trade DEC,-4.59B,-1.98B,-2.8B,-1.7B
+Wednesday,03/06/19,8:30,US,Balance of Trade DEC,-59.8B,-50.3B,-57.9B,-56B
+Wednesday,03/06/19,10:00,CA,Ivey PMI s.a FEB,50.6,54.7,55.1,53
+Friday,03/08/19,8:30,US,Non Farm Payrolls FEB,20K,311K,180K,190K
+Friday,03/08/19,20:30,CN,Inflation Rate YoY FEB,0.015,1.70%,0.015,0.016
+Monday,03/11/19,7:30,US,Retail Sales MoM JAN,0.002,-1.60%,0,0.003
+Tuesday,03/12/19,4:30,GB,Balance of Trade JAN,-3.825B,-3.448B,-3.5B,-2.6B
+Tuesday,03/12/19,7:30,US,Core Inflation Rate YoY FEB,0.021,2.20%,0.022,0.022
+Tuesday,03/12/19,7:30,US,Inflation Rate YoY FEB,0.015,1.60%,0.016,0.016
+Wednesday,03/13/19,7:30,US,Durable Goods Orders MoM JAN,0.004,1.30%,-0.005,-0.009
+Sunday,03/17/19,18:50,JP,Balance of Trade FEB,339B,-1416B,310.2B,-200B
+Tuesday,03/19/19,4:20,GB,Claimant Count Change FEB,27K,15.7K,2.7K,9.1K
+Wednesday,03/20/19,4:30,GB,Inflation Rate YoY FEB,0.019,1.80%,0.018,0.018
+Thursday,03/21/19,18:30,JP,Inflation Rate YoY FEB,0.002,0.20%,0.003,0.001
+Friday,03/22/19,7:30,CA,Inflation Rate YoY FEB,0.015,1.40%,0.014,0.015
+Wednesday,03/27/19,7:30,CA,Balance of Trade JAN,-4.25B,-4.82B,-3.5B,-3.9B
+Wednesday,03/27/19,7:30,US,Balance of Trade JAN,-51.1B,-59.9B,-57B,-59B
+Wednesday,03/27/19,,CN,US-China Trade Talks,,,,
+Thursday,03/28/19,5:00,EA,Business Confidence MAR,0.53,0.69,0.66,0.6
+Thursday,03/28/19,19:01,GB,Gfk Consumer Confidence MAR,-13,-13,-14,-13
+Thursday,03/28/19,,CN,US-China Trade Talks,,,,
+Friday,03/29/19,7:30,US,Personal Income MoM FEB,0.002,-0.10%,0.003,0.002
+Friday,03/29/19,7:30,US,Personal Spending MoM JAN,0.001,-0.60%,0.003,0.004
+Saturday,03/30/19,20:00,CN,NBS Manufacturing PMI MAR,50.5,49.2,49.5,49.6
+Sunday,03/31/19,18:50,JP,Tankan Large Manufacturers Index Q1,12,19,13,18
+Sunday,03/31/19,20:45,CN,Caixin Manufacturing PMI MAR,50.8,49.9,50.1,49.8
+Monday,04/01/19,7:30,US,Retail Sales MoM FEB,-0.002,0.70%,0.003,0.002
+Tuesday,04/02/19,7:30,US,Durable Goods Orders MoM FEB,-0.016,0.10%,-0.018,-0.007
+Thursday,04/04/19,9:00,CA,Ivey PMI s.a MAR,54.3,50.6,51.1,50.4
+Friday,04/05/19,7:30,US,Non Farm Payrolls MAR,196K,33K,180K,178K
+Monday,04/08/19,0:00,JP,Consumer Confidence MAR,40.5,41.5,42.3,42
+Wednesday,04/10/19,3:30,GB,Balance of Trade FEB,-4.860B,-5.345B,,-1.2B
+Wednesday,04/10/19,7:30,US,Core Inflation Rate YoY MAR,0.02,2.10%,0.021,0.022
+Wednesday,04/10/19,7:30,US,Inflation Rate YoY MAR,0.019,1.50%,0.018,0.017
+Wednesday,04/10/19,20:30,CN,Inflation Rate YoY MAR,0.023,1.50%,0.023,0.02
+Tuesday,04/16/19,3:30,GB,Claimant Count Change MAR,28.3K,26.7K,20K,5K
+Tuesday,04/16/19,18:50,JP,Balance of Trade MAR,529B,335B,372.2B,250B
+Wednesday,04/17/19,3:30,GB,Inflation Rate YoY MAR,0.019,1.90%,0.02,0.019
+Wednesday,04/17/19,7:30,CA,Balance of Trade FEB,-2.9B,-3.09B,-3.5B,-3.9B
+Wednesday,04/17/19,7:30,CA,Inflation Rate YoY MAR,0.019,1.50%,0.019,0.017
+Wednesday,04/17/19,7:30,US,Balance of Trade FEB,-49.4B,-51.1B,-53.5B,-52.8B
+Thursday,04/18/19,7:30,US,Retail Sales MoM MAR,0.016,-0.20%,0.009,0.006
+Thursday,04/18/19,18:30,JP,Inflation Rate YoY MAR,0.005,0.20%,0.005,0.003
+Thursday,04/25/19,7:30,US,Durable Goods Orders MoM MAR,0.027,-1.10%,0.008,0.005
+Monday,04/29/19,4:00,EA,Business Confidence APR,0.42,0.54,0.49,0.51
+Monday,04/29/19,7:30,US,Personal Income MoM MAR,0.001,0.20%,0.004,0.003
+Monday,04/29/19,7:30,US,Personal Spending MoM MAR,0.009,0.10%,0.007,0.005
+Monday,04/29/19,7:30,US,Personal Spending MoM FEB,0.001,0.30%,0.002,0.003
+Monday,04/29/19,18:01,GB,Gfk Consumer Confidence APR,-13,-13,-12,-12
+Monday,04/29/19,20:00,CN,NBS Manufacturing PMI APR,50.1,50.5,50.5,50.8
+Monday,04/29/19,20:45,CN,Caixin Manufacturing PMI APR,50.2,50.8,51,51
+Monday,04/29/19,,CN,US-China Trade Talks,,,,
+Monday,04/29/19,7:30,US,Non Farm Payrolls APR,263K,189K,185K,178K
+Tuesday,05/07/19,9:00,CA,Ivey PMI s.a APR,55.9,54.3,53,53.5
+Wednesday,05/08/19,20:30,CN,Inflation Rate YoY APR,0.025,2.30%,0.025,0.021
+Thursday,05/09/19,0:00,JP,Consumer Confidence APR,40.4,40.5,40.3,41
+Thursday,05/09/19,7:30,CA,Balance of Trade MAR,-3.21B,-3.42B,-2.45B, -2.3B
+Thursday,05/09/19,7:30,US,Balance of Trade MAR,-50B,-49.3B,-50.2B, -50.1B
+Thursday,05/09/19,3:30,GB,Balance of Trade MAR,-5.408B,-6.219B,,-2.7B
+Thursday,05/09/19,7:30,US,Core Inflation Rate YoY APR,0.021,2%,0.021,0.02
+Thursday,05/09/19,7:30,US,Inflation Rate YoY APR,0.02,1.90%,0.021,0.019
+Tuesday,05/14/19,3:30,GB,Claimant Count Change APR,24.7K,22.6K,24.2K,25K
+Wednesday,05/15/19,7:30,CA,Inflation Rate YoY APR,0.02,1.90%,0.02,0.02
+Wednesday,05/15/19,7:30,US,Retail Sales MoM APR,-0.002,1.70%,0.002,0.003
+Tuesday,05/21/19,18:50,JP,Balance of Trade APR,60.4B,527.8B,203.2B,272B
+Wednesday,05/22/19,3:30,GB,Inflation Rate YoY APR,0.021,1.90%,0.022,0.018
+Thursday,05/23/19,18:30,JP,Inflation Rate YoY APR,0.009,0.50%,0.009,0.003
+Thursday,05/23/19,7:30,US,Durable Goods Orders MoM APR,-0.021,1.70%,-0.02,-0.017
+Tuesday,05/28/19,4:00,EA,Business Confidence 05,0.3,0.42,0.4,0.36
+Thursday,05/30/19,18:01,GB,Gfk Consumer Confidence 05,-10,-13,-12,-12
+Thursday,05/30/19,20:00,CN,NBS Manufacturing PMI 05,49.4,50.1,49.9,50.2
+Thursday,05/30/19,0:00,JP,Consumer Confidence 05,39.4,40.4,40.6,40.5
+Thursday,05/30/19,7:30,US,Personal Income MoM APR,0.005,0.10%,0.003,0.002
+Thursday,05/30/19,7:30,US,Personal Spending MoM APR,0.003,1.10%,0.002,0.001
+Sunday,06/02/19,20:45,CN,Caixin Manufacturing PMI 05,50.2,50.2,50,50.4
+Thursday,06/06/19,7:30,CA,Balance of Trade APR,-0.97B,-2.34B,-2.8B,-3B
+Thursday,06/06/19,7:30,US,Balance of Trade APR,-50.8B,-51.9B,-50.7B,-51.2B
+Thursday,06/06/19,9:00,CA,Ivey PMI s.a 05,55.9,55.9,56.7,54.7
+Friday,06/07/19,7:30,US,Non Farm Payrolls 05,75K,224K,185K,190K
+Monday,06/10/19,3:30,GB,Balance of Trade APR,-2.740B,-6.151B,,-3.2B
+Tuesday,06/11/19,3:30,GB,Claimant Count Change 05,23.2K,19.1K,22.9K,21K
+Tuesday,06/11/19,20:30,CN,Inflation Rate YoY 05,0.027,2.50%,0.027,0.025
+Wednesday,06/12/19,7:30,US,Core Inflation Rate YoY 05,0.02,2.10%,0.021,0.021
+Wednesday,06/12/19,7:30,US,Inflation Rate YoY 05,0.018,2%,0.019,0.019
+Friday,06/14/19,7:30,US,Retail Sales MoM 05,0.005,0.30%,0.006,0.006
+Tuesday,06/18/19,18:50,JP,Balance of Trade 05,-967.1B,56.8B,-979.2B,-851B
+Wednesday,06/19/19,3:30,GB,Inflation Rate YoY 05,0.02,2.10%,0.02,0.021
+Wednesday,06/19/19,7:30,CA,Inflation Rate YoY 05,0.024,2%,0.021,0.021
+Thursday,06/20/19,18:30,JP,Inflation Rate YoY 05,0.007,0.90%,0.007,0.01
+Wednesday,06/26/19,7:30,US,Durable Goods Orders MoM 05,-0.013,-2.80%,-0.001,0.002
+Thursday,06/27/19,4:00,EA,Business Confidence JUN,0.17,0.3,0.23,0.25
+Thursday,06/27/19,18:01,GB,Gfk Consumer Confidence JUN,-13,-10,-11,-9
+Friday,06/28/19,7:30,US,Personal Income MoM 05,0.005,0.50%,0.003,0.003
+Friday,06/28/19,7:30,US,Personal Spending MoM 05,0.004,0.60%,0.004,0.002
+Saturday,06/29/19,20:00,CN,NBS Manufacturing PMI JUN,49.4,49.4,49.5,49.8
+Sunday,06/30/19,18:50,JP,Tankan Large Manufacturers Index Q2,7,12,9,8
+Sunday,06/30/19,20:45,CN,Caixin Manufacturing PMI JUN,49.4,50.2,50,49.6
+Monday,07/01/19,0:00,JP,Consumer Confidence JUN,38.7,39.4,39.2,40.8
+Wednesday,07/03/19,7:30,CA,Balance of Trade 05,0.76B,-1.08B,-1.5B,-1.3B
+Wednesday,07/03/19,7:30,US,Balance of Trade 05,-55.5B,-51.2B,-54B,-54.3B
+Friday,07/05/19,7:30,US,Non Farm Payrolls JUN,224K,72K,160K,171K
+Friday,07/05/19,9:00,CA,Ivey PMI s.a JUN,52.4,55.9,55,54
+Tuesday,07/09/19,20:30,CN,Inflation Rate YoY JUN,0.027,2.70%,0.027,0.026
+Wednesday,07/10/19,3:30,GB,Balance of Trade 05,-2.324B,-3.716B,,-2.6B
+Thursday,07/11/19,7:30,US,Core Inflation Rate YoY JUN,0.021,2%,0.02,0.02
+Thursday,07/11/19,7:30,US,Inflation Rate YoY JUN,0.016,1.80%,0.016,0.017
+Tuesday,07/16/19,3:30,GB,Claimant Count Change JUN,38K,24.5K,22.8K,15K
+Tuesday,07/16/19,7:30,US,Retail Sales MoM JUN,0.004,0.40%,0.001,0.004
+Wednesday,07/17/19,3:30,GB,Inflation Rate YoY JUN,0.02,2%,0.02,0.021
+Wednesday,07/17/19,7:30,CA,Inflation Rate YoY JUN,0.02,2.40%,0.02,0.022
+Wednesday,07/17/19,18:50,JP,Balance of Trade JUN,589.5B,-968.3B,420B,510B
+Thursday,07/18/19,18:30,JP,Inflation Rate YoY JUN,0.007,0.70%,0.007,0.008
+Thursday,07/25/19,7:30,US,Durable Goods Orders MoM JUN,0.02,-2.30%,0.007,0.007
+Monday,07/29/19,,CN,US-China Trade Talks,,,,
+Tuesday,07/30/19,4:00,EA,Business Confidence JUL,-0.12,0.17,0.08,0.08
+Tuesday,07/30/19,7:30,US,Personal Income MoM JUN,0.004,0.40%,0.004,0.003
+Tuesday,07/30/19,7:30,US,Personal Spending MoM JUN,0.003,0.50%,0.003,0.003
+Tuesday,07/30/19,18:01,GB,Gfk Consumer Confidence JUL,-11,-13,-13,-14
+Tuesday,07/30/19,20:00,CN,NBS Manufacturing PMI JUL,49.7,49.4,49.6,49.3
+Tuesday,07/30/19,,CN,US-China Trade Talks,,,,
+Wednesday,07/31/19,0:00,JP,Consumer Confidence JUL,37.8,38.7,38.5,41
+Wednesday,07/31/19,20:45,CN,Caixin Manufacturing PMI JUL,49.9,49.4,49.6,49.2
+Friday,08/02/19,7:30,CA,Balance of Trade JUN,0.14B,0.56B,-0.3B,0.3B
+Friday,08/02/19,7:30,US,Balance of Trade JUN,-55.2B,-55.3B,-54.6B,-54.7B
+Friday,08/02/19,7:30,US,Non Farm Payrolls JUL,164K,193K,164K,160K
+Wednesday,08/07/19,9:00,CA,Ivey PMI s.a JUL,54.2,52.4,53,51.8
+Thursday,08/08/19,20:30,CN,Inflation Rate YoY JUL,0.028,2.70%,0.027,0.027
+Friday,08/09/19,3:30,GB,Balance of Trade JUN,1.779B,-2.002B,,-2.9B
+Tuesday,08/13/19,3:30,GB,Claimant Count Change JUL,28K,31.4K,32K,12K
+Tuesday,08/13/19,7:30,US,Core Inflation Rate YoY JUL,0.022,2.10%,0.021,0.021
+Tuesday,08/13/19,7:30,US,Inflation Rate YoY JUL,0.018,1.60%,0.017,0.017
+Wednesday,08/14/19,3:30,GB,Inflation Rate YoY JUL,0.021,2%,0.019,0.02
+Thursday,08/15/19,7:30,US,Retail Sales MoM JUL,0.007,0.30%,0.003,0.003
+Sunday,08/18/19,18:50,JP,Balance of Trade JUL,-249.6B,589.6B,-200B,-320B
+Wednesday,08/21/19,7:30,CA,Inflation Rate YoY JUL,0.02,2%,0.017,0.018
+Thursday,08/22/19,18:30,JP,Inflation Rate YoY JUL,0.005,0.70%,0.005,0.008
+Monday,08/26/19,7:30,US,Durable Goods Orders MoM JUL,0.021,1.80%,0.012,0.008
+Thursday,08/29/19,0:00,JP,Consumer Confidence AUG,37.1,37.8,,37.6
+Thursday,08/29/19,4:00,EA,Business Confidence AUG,0.11,-0.11,0.08,-0.2
+Thursday,08/29/19,18:01,GB,Gfk Consumer Confidence AUG,-14,-11,-12,-12
+Friday,08/30/19,7:30,US,Personal Income MoM JUL,0.001,0.50%,0.003,0.003
+Friday,08/30/19,7:30,US,Personal Spending MoM JUL,0.006,0.30%,0.005,0.004
+Friday,08/30/19,20:00,CN,NBS Manufacturing PMI AUG,49.5,49.7,49.7,49.5
+Sunday,09/01/19,20:45,CN,Caixin Manufacturing PMI AUG,50.4,49.9,49.8,49.8
+Wednesday,09/04/19,7:30,CA,Balance of Trade JUL,-1.12B,-0.06B,-0.4B,-0.1B
+Wednesday,09/04/19,7:30,US,Balance of Trade JUL,-54B,-55.5B,-53.5B,-53.4B
+Friday,09/06/19,7:30,US,Non Farm Payrolls AUG,130K,159K,158K,151K
+Friday,09/06/19,9:00,CA,Ivey PMI s.a AUG,60.6,54.2,53,53.9
+Monday,09/09/19,3:30,GB,Balance of Trade JUL,-0.219B,-0.132B,,-2.3B
+Monday,09/09/19,20:30,CN,Inflation Rate YoY AUG,0.028,2.80%,0.026,0.026
+Tuesday,09/10/19,3:30,GB,Claimant Count Change AUG,28.2K,19.8K,30K,16K
+Thursday,09/12/19,7:30,US,Core Inflation Rate YoY AUG,0.024,2.20%,0.023,0.022
+Thursday,09/12/19,7:30,US,Inflation Rate YoY AUG,0.017,1.80%,0.018,0.019
+Friday,09/13/19,7:30,US,Retail Sales MoM AUG,0.004,0.80%,0.002,0.004
+Tuesday,09/17/19,18:50,JP,Balance of Trade AUG,-136.3B,-250.7B,-355.9B,-430B
+Wednesday,09/18/19,3:30,GB,Inflation Rate YoY AUG,0.017,2.10%,0.019,0.019
+Wednesday,09/18/19,7:30,CA,Inflation Rate YoY AUG,0.019,2%,0.02,0.019
+Thursday,09/19/19,18:30,JP,Inflation Rate YoY AUG,0.003,0.50%,0.006,0.008
+Thursday,09/19/19,20:30,CN,Loan Prime Rate 1Y,0.042,4.25%,,0.0415
+Thursday,09/26/19,18:01,GB,Gfk Consumer Confidence SEP,-12,-14,-14,-14
+Friday,09/27/19,4:00,EA,Business Confidence SEP,-0.22,0.12,0.11,0.19
+Friday,09/27/19,7:30,US,Durable Goods Orders MoM AUG,0.002,2%,-0.01,-0.012
+Friday,09/27/19,7:30,US,Personal Income MoM AUG,0.004,0.10%,0.004,0.003
+Friday,09/27/19,7:30,US,Personal Spending MoM AUG,0.001,0.50%,0.003,0.004
+Sunday,09/29/19,20:00,CN,NBS Manufacturing PMI SEP,49.8,49.5,49.5,49.9
+Sunday,09/29/19,20:45,CN,Caixin Manufacturing PMI SEP,51.4,50.4,50.2,50
+Monday,09/30/19,18:50,JP,Tankan Large Manufacturers Index Q3,5,7,2,1
+Wednesday,10/02/19,0:00,JP,Consumer Confidence SEP,35.6,37.1,,37.3
+Friday,10/04/19,7:30,CA,Balance of Trade AUG,-0.96B,-1.38B,-1B,-0.8B
+Friday,10/04/19,7:30,US,Balance of Trade AUG,-54.9B,-54B,-54.5B,-54.3B
+Friday,10/04/19,7:30,US,Non Farm Payrolls SEP,136K,168K,145K,165K
+Friday,10/04/19,9:00,CA,Ivey PMI s.a SEP,48.7,60.6,54.3,58
+Thursday,10/10/19,3:30,GB,Balance of Trade AUG,-1.546B,-1.681B,,-3.8B
+Thursday,10/10/19,7:30,US,Core Inflation Rate YoY SEP,0.024,2.40%,0.024,0.024
+Thursday,10/10/19,7:30,US,Inflation Rate YoY SEP,0.017,1.70%,0.018,0.019
+Monday,10/14/19,20:30,CN,Inflation Rate YoY SEP,0.03,2.80%,0.029,0.029
+Tuesday,10/15/19,3:30,GB,Claimant Count Change SEP,21.1K,16.3K,26.5K,24K
+Wednesday,10/16/19,3:30,GB,Inflation Rate YoY SEP,0.017,1.70%,0.018,0.019
+Wednesday,10/16/19,7:30,CA,Inflation Rate YoY SEP,0.019,1.90%,0.021,0.02
+Wednesday,10/16/19,7:30,US,Retail Sales MoM SEP,-0.003,0.60%,0.003,0.003
+Thursday,10/17/19,18:30,JP,Inflation Rate YoY SEP,0.002,0.30%,0.004,0.004
+Sunday,10/20/19,18:50,JP,Balance of Trade SEP,-123B,-143.5B,54B,151B
+Sunday,10/20/19,20:30,CN,Loan Prime Rate 1Y,0.042,4.20%,,0.0405
+Thursday,10/24/19,7:30,US,Durable Goods Orders MoM SEP,-0.011,0.30%,-0.008,-0.006
+Wednesday,10/30/19,5:00,EA,Business Confidence OCT,-0.19,-0.23,-0.24,0.14
+Wednesday,10/30/19,19:01,GB,Gfk Consumer Confidence OCT,-14,-12,-13,-16
+Wednesday,10/30/19,20:00,CN,NBS Manufacturing PMI OCT,49.3,49.8,49.8,49.6
+Thursday,10/31/19,0:00,JP,Consumer Confidence OCT,36.2,35.6,35.5,34.9
+Thursday,10/31/19,7:30,US,Personal Income MoM SEP,0.003,0.50%,0.003,0.003
+Thursday,10/31/19,7:30,US,Personal Spending MoM SEP,0.002,0.20%,0.002,0.002
+Thursday,10/31/19,20:45,CN,Caixin Manufacturing PMI OCT,51.7,51.4,51,50.9
+Friday,11/01/19,7:30,US,Non Farm Payrolls OCT,128K,180K,89K,100K
+Tuesday,11/05/19,8:30,CA,Balance of Trade SEP,-0.98B,-1.24B,-0.7B, -0.3B
+Tuesday,11/05/19,8:30,US,Balance of Trade SEP,-52.5B,-55B,-52.5B,-52.0B
+Wednesday,11/06/19,10:00,CA,Ivey PMI s.a OCT,48.2,48.7,0.8,53
+Friday,11/08/19,20:30,CN,Inflation Rate YoY OCT,0.038,3%,0.033,0.03
+Monday,11/11/19,4:30,GB,Balance of Trade SEP,-3.36B,-1.76B,,-2.2B
+Tuesday,11/12/19,4:30,GB,Claimant Count Change OCT,33K,13.5K,21.3K,27K
+Wednesday,11/13/19,4:30,GB,Inflation Rate YoY OCT,0.015,1.70%,0.016,0.016
+Wednesday,11/13/19,8:30,US,Core Inflation Rate YoY OCT,0.023,2.40%,0.024,0.024
+Wednesday,11/13/19,8:30,US,Inflation Rate YoY OCT,0.018,1.70%,0.017,0.016
+Friday,11/15/19,8:30,US,Retail Sales MoM OCT,0.003,-0.30%,0.002,0.003
+Tuesday,11/19/19,18:50,JP,Balance of Trade OCT,17.3B,-124.8B,301B,219B
+Tuesday,11/19/19,20:30,CN,Loan Prime Rate 1Y,0.0415,4.20%,0.042,0.041
+Wednesday,11/20/19,8:30,CA,Inflation Rate YoY OCT,0.019,1.90%,0.019,0.02
+Thursday,11/21/19,18:30,JP,Inflation Rate YoY OCT,0.002,0.20%,0.003,0.004
+Wednesday,11/27/19,8:30,US,Durable Goods Orders MoM OCT,0.006,-1.40%,-0.008,-0.006
+Wednesday,11/27/19,10:00,US,Personal Income MoM OCT,0,0.30%,0.003,0.002
+Wednesday,11/27/19,10:00,US,Personal Spending MoM OCT,0.003,0.20%,0.003,0.002
+Thursday,11/28/19,5:00,EA,Business Confidence NOV,-0.23,-0.2,-0.14,-0.16
+Thursday,11/28/19,19:01,GB,GfK Consumer Confidence NOV,-14,-14,-14,-13
+Friday,11/29/19,0:00,JP,Consumer Confidence NOV,38.7,36.2,35.4,36
+Friday,11/29/19,20:00,CN,NBS Manufacturing PMI NOV,50.2,49.3,49.5,49.8
+Sunday,12/01/19,20:45,CN,Caixin Manufacturing PMI NOV,51.8,51.7,51.4,51.1
+Thursday,12/05/19,8:30,CA,Balance of Trade OCT,-1.08B,-1.23B,-1.37B,-1.4B
+Thursday,12/05/19,8:30,US,Balance of Trade OCT,-47.2B,-51.1B,-48.7B, -48.1B
+Thursday,12/05/19,10:00,CA,Ivey PMI s.a NOV,60,48.2,53.8,48.6
+Friday,12/06/19,8:30,US,Non Farm Payrolls NOV,266K,156K,180K,175K
+Monday,12/09/19,20:30,CN,Inflation Rate YoY NOV,0.045,3.80%,0.042,0.043
+Tuesday,12/10/19,4:30,GB,Balance of Trade OCT,-5.19B,-1.92B,,-3.0B
+Wednesday,12/11/19,8:30,US,Core Inflation Rate YoY NOV,0.023,2.30%,0.023,0.023
+Wednesday,12/11/19,8:30,US,Inflation Rate YoY NOV,0.021,1.80%,0.02,0.019
+Thursday,12/12/19,18:50,JP,Tankan Large Manufacturers Index Q4,0,5,2,2
+Friday,12/13/19,8:30,US,Retail Sales MoM NOV,0.002,0.40%,0.005,0.003
+Tuesday,12/17/19,4:30,GB,Claimant Count Change NOV,28.8K,26.4K,24.5K,29K
+Tuesday,12/17/19,18:50,JP,Balance of Trade NOV,-82.1B,15.7B,-369B,-620B
+Wednesday,12/18/19,4:30,GB,Inflation Rate YoY NOV,0.015,1.50%,0.014,0.014
+Wednesday,12/18/19,8:30,CA,Inflation Rate YoY NOV,0.022,1.90%,0.022,0.021
+Thursday,12/19/19,18:30,JP,Inflation Rate YoY NOV,0.005,0.20%,0.002,0.003
+Thursday,12/19/19,19:01,GB,GfK Consumer Confidence DEC,-11,-14,-14,-12
+Thursday,12/19/19,20:30,CN,Loan Prime Rate 1Y,0.0415,4.15%,,0.0405
+Friday,12/20/19,10:00,US,Personal Income MoM NOV,0.005,0.10%,0.003,0.002
+Friday,12/20/19,10:00,US,Personal Spending MoM NOV,0.004,0.30%,0.004,0.003
+Monday,12/23/19,8:30,US,Durable Goods Orders MoM NOV,-0.02,0.20%,0.015,0.011
+Monday,12/30/19,20:00,CN,NBS Manufacturing PMI DEC,50.2,50.2,50.1,50.3
+Wednesday,01/01/20,20:45,CN,Caixin Manufacturing PMI DEC,51.5,51.8,51.8,52.2
+Friday,01/03/20,14:00,US,FOMC Minutes,,,,
+Tuesday,01/07/20,8:30,CA,Balance of Trade NOV,-1.09B,-1.61B,-1.15B, -0.9B
+Tuesday,01/07/20,8:30,US,Balance of Trade NOV,-43.1B,-46.9B,-43.8B, -43B
+Tuesday,01/07/20,10:00,CA,Ivey PMI s.a DEC,51.9,60,53.8,56
+Wednesday,01/08/20,0:00,JP,Consumer Confidence DEC,39.1,38.7,38,39
+Wednesday,01/08/20,5:00,EA,Business Confidence DEC,-0.25,-0.21,-0.16,-0.1
+Wednesday,01/08/20,20:30,CN,Inflation Rate YoY DEC,0.045,4.50%,0.047,0.047
+Friday,01/10/20,8:30,US,Non Farm Payrolls DEC,145K,256K,164K,165K
+Monday,01/13/20,4:30,GB,Balance of Trade NOV,4.03B,-1.34B,,-3.2B
+Tuesday,01/14/20,8:30,US,Core Inflation Rate YoY DEC,0.023,2.30%,0.023,0.022
+Tuesday,01/14/20,8:30,US,Inflation Rate YoY DEC,0.023,2.10%,0.023,0.023
+Wednesday,01/15/20,4:30,GB,Inflation Rate YoY DEC,0.013,1.50%,0.015,0.015
+Wednesday,01/15/20,,US,US-China Phase 1 Trade Deal Signature,,,,
+Thursday,01/16/20,8:30,US,Retail Sales MoM DEC,0.003,0.30%,0.003,0.003
+Sunday,01/19/20,20:30,CN,Loan Prime Rate 1Y,0.0415,4.15%,,0.0405
+Tuesday,01/21/20,4:30,GB,Claimant Count Change DEC,14.9K,14.9K,22.6K,26K
+Wednesday,01/22/20,8:30,CA,Inflation Rate YoY DEC,0.022,2.20%,0.022,0.022
+Wednesday,01/22/20,18:50,JP,Balance of Trade DEC,-152.5B,-85.2B,-150B,-124B
+Thursday,01/23/20,18:30,JP,Inflation Rate YoY DEC,0.008,0.50%,0.004,0.005
+Tuesday,01/28/20,8:30,US,Durable Goods Orders MoM DEC,0.024,-3.10%,0.004,0.006
+Wednesday,01/29/20,0:00,JP,Consumer Confidence JAN,39.1,39.1,40.8,40.5
+Wednesday,01/29/20,,US,USMCA Trade Deal Signature,,,,
+Thursday,01/30/20,5:00,EA,Business Confidence JAN,-0.23,-0.32,-0.19,-0.18
+Thursday,01/30/20,19:01,GB,Gfk Consumer Confidence JAN,-9,-11,-9,-10
+Thursday,01/30/20,20:00,CN,NBS Manufacturing PMI JAN,50,50.2,50,50
+Friday,01/31/20,8:30,US,Personal Income MoM DEC,0.002,0.40%,0.003,0.004
+Friday,01/31/20,8:30,US,Personal Spending MoM DEC,0.003,0.40%,0.003,0.005
+Friday,01/31/20,18:00,GB,Brexit Deadline,,,,
+Sunday,02/02/20,20:45,CN,Caixin Manufacturing PMI JAN,51.1,51.5,51.3,50.5
+Monday,02/03/20,8:10,RU,Full Year GDP Growth 2019,0.013,2.50%,,
+Wednesday,02/05/20,8:30,CA,Balance of Trade DEC,-0.4B,-1.2B,-0.61B, -0.8B
+Wednesday,02/05/20,8:30,US,Balance of Trade DEC,-48.9B,-43.7B,-48.2B,-49B
+Friday,02/07/20,8:30,US,Non Farm Payrolls JAN,225K,147K,160K,148K
+Friday,02/07/20,10:00,CA,Ivey PMI s.a JAN,57.3,51.9,53.3,52.3
+Sunday,02/09/20,20:30,CN,Inflation Rate YoY JAN,0.054,4.50%,0.049,0.051
+Tuesday,02/11/20,4:30,GB,Balance of Trade DEC,7.715B,1.821B,,-2.6B
+Thursday,02/13/20,8:30,US,Core Inflation Rate YoY JAN,0.023,2.30%,0.022,0.023
+Thursday,02/13/20,8:30,US,Inflation Rate YoY JAN,0.025,2.30%,0.024,0.024
+Friday,02/14/20,8:30,US,Retail Sales MoM JAN,0.003,0.20%,0.003,0.003
+Tuesday,02/18/20,4:30,GB,Claimant Count Change JAN,5.5K,2.6K,22.6K,15K
+Tuesday,02/18/20,18:50,JP,Balance of Trade JAN,-1312.6B,-154.6B,-1694.9B,-1723B
+Wednesday,02/19/20,4:30,GB,Inflation Rate YoY JAN,0.018,1.30%,0.016,0.014
+Wednesday,02/19/20,8:30,CA,Inflation Rate YoY JAN,0.024,2.20%,0.023,0.023
+Wednesday,02/19/20,20:30,CN,Loan Prime Rate 1Y,0.0405,4.15%,,0.0395
+Thursday,02/20/20,18:30,JP,Inflation Rate YoY JAN,0.007,0.80%,0.007,0.007
+Sunday,02/23/20,,CN,NPC Committee Meeting,,,,
+Wednesday,02/26/20,18:00,US,President Trump Speech ,,,,
+Thursday,02/27/20,5:00,EA,Business Confidence FEB,-0.04,-0.19,-0.28,-0.27
+Thursday,02/27/20,8:30,US,Durable Goods Orders MoM JAN,-0.002,2.90%,-0.015,-0.02
+Thursday,02/27/20,19:01,GB,Gfk Consumer Confidence FEB,-7,-9,-8,-8
+Friday,02/28/20,8:30,US,Personal Income MoM JAN,0.006,0.10%,0.003,0.003
+Friday,02/28/20,8:30,US,Personal Spending MoM JAN,0.002,0.40%,0.003,0.002
+Friday,02/28/20,20:00,CN,NBS Manufacturing PMI FEB,35.7,50,46,45
+Sunday,03/01/20,20:45,CN,Caixin Manufacturing PMI FEB,40.3,51.1,45.7,46
+Tuesday,03/03/20,0:00,JP,Consumer Confidence FEB,38.4,39.1,40.6,37.7
+Tuesday,03/03/20,11:00,US,Fed Press Conference,,,,
+Friday,03/06/20,8:30,CA,Balance of Trade JAN,-1.47B,-0.73B,-0.83B, -0.7B
+Friday,03/06/20,8:30,US,Balance of Trade JAN,-45.3B,-48.6B,-46.1B, -45.8B
+Friday,03/06/20,8:30,US,Non Farm Payrolls FEB,273K,273K,175K,165K
+Friday,03/06/20,10:00,CA,Ivey PMI s.a FEB,54.1,57.3,53.6,56
+Monday,03/09/20,20:30,CN,Inflation Rate YoY FEB,0.052,5.40%,0.052,0.051
+Wednesday,03/11/20,4:00,GB,BoE Press Conference,,,,
+Wednesday,03/11/20,4:30,GB,Balance of Trade JAN,4.2B,6.3B,,-3.7B
+Wednesday,03/11/20,7:30,GB,Spring Budget 2020,,,,
+Wednesday,03/11/20,7:30,US,Core Inflation Rate YoY FEB,0.024,2.30%,0.023,0.023
+Wednesday,03/11/20,7:30,US,Inflation Rate YoY FEB,0.023,2.50%,0.022,0.023
+Wednesday,03/11/20,20:00,US,President Trump Statement on Coronavirus,,,,
+Friday,03/13/20,14:00,US,President Trump Statement on Coronavirus,,,,
+Sunday,03/15/20,17:30,US,Fed Press Conference,,,,
+Tuesday,03/17/20,4:30,GB,Claimant Count Change FEB,17.3K,-0.2K,21.4K,24K
+Tuesday,03/17/20,7:30,US,Retail Sales MoM FEB,-0.005,0.60%,0.002,0.001
+Tuesday,03/17/20,18:50,JP,Balance of Trade FEB,1109.8B,-1313.2B,917.2B,915B
+Wednesday,03/18/20,7:30,CA,Inflation Rate YoY FEB,0.022,2.40%,0.021,0.022
+Wednesday,03/18/20,8:00,CA,Prime Minister Trudeau Speech ,,,,
+Wednesday,03/18/20,18:30,JP,Inflation Rate YoY FEB,0.004,0.70%,0.008,0.005
+Thursday,03/19/20,20:30,CN,Loan Prime Rate 1Y,0.0405,4.05%,,0.0395
+Tuesday,03/24/20,11:00,CA,Parliamentary Debate & Vote on Coronavirus Aid Package,,,,
+Wednesday,03/25/20,2:00,GB,Inflation Rate YoY FEB,0.017,1.80%,0.017,0.015
+Wednesday,03/25/20,7:30,US,Durable Goods Orders MoM FEB,0.012,0.10%,-0.008,-0.007
+Friday,03/27/20,7:30,US,Personal Income MoM FEB,0.006,0.60%,0.004,0.003
+Friday,03/27/20,7:30,US,Personal Spending MoM FEB,0.002,0.20%,0.002,0.003
+Monday,03/30/20,4:00,EA,Business Confidence MAR,-0.28,-0.06,-0.05,-0.6
+Monday,03/30/20,18:01,GB,Gfk Consumer Confidence MAR,-9,-7,-15,-16
+Monday,03/30/20,20:00,CN,NBS Manufacturing PMI MAR,52,35.7,45,44.2
+Tuesday,03/31/20,18:50,JP,Tankan Large Manufacturers Index Q1,-8,0,-10,-12
+Tuesday,03/31/20,20:45,CN,Caixin Manufacturing PMI MAR,50.1,40.3,45.5,45.7
+Thursday,04/02/20,7:30,CA,Balance of Trade FEB,-0.98B,-1.66B,-1.87B, -2B
+Thursday,04/02/20,7:30,US,Balance of Trade FEB,-39.9B,-45.5B,-40B, -39B
+Friday,04/03/20,7:30,US,Non Farm Payrolls MAR,-701K,275K,-100K,-150K
+Sunday,04/05/20,18:01,GB,Gfk Consumer Confidence MAR,-34,-9,,-30
+Monday,04/06/20,0:20,JP,Consumer Confidence MAR,30.9,38.4,,36.8
+Tuesday,04/07/20,9:00,CA,Ivey PMI s.a MAR,26,54.1,41,43
+Tuesday,04/07/20,,EA,Eurogroup Meeting,,,,
+Thursday,04/09/20,1:00,GB,Balance of Trade FEB,-2.8B,2.4B,,2.2B
+Thursday,04/09/20,20:30,CN,Inflation Rate YoY MAR,0.043,5.20%,0.048,0.05
+Thursday,04/09/20,,EA,Eurogroup Meeting,,,,
+Friday,04/10/20,7:30,US,Core Inflation Rate YoY MAR,0.021,2.40%,0.023,0.023
+Friday,04/10/20,7:30,US,Inflation Rate YoY MAR,0.015,2.30%,0.016,0.015
+Wednesday,04/15/20,7:30,US,Retail Sales MoM MAR,-0.087,-0.40%,-0.08,-0.065
+Sunday,04/19/20,18:50,JP,Balance of Trade MAR,4.9B,1108.8B,420B, 400B
+Sunday,04/19/20,20:30,CN,Loan Prime Rate 1Y,0.0385,4.05%,0.0385,0.0385
+Tuesday,04/21/20,1:00,GB,Claimant Count Change MAR,12.2K,5.9K,175K,272K
+Wednesday,04/22/20,1:00,GB,Inflation Rate YoY MAR,0.015,1.70%,0.015,0.013
+Wednesday,04/22/20,7:30,CA,Inflation Rate YoY MAR,0.009,2.20%,0.012,0.015
+Thursday,04/23/20,18:01,GB,Gfk Consumer Confidence APR,-34,-34,-40,-46
+Thursday,04/23/20,18:30,JP,Inflation Rate YoY MAR,0.004,0.40%,,0.002
+Friday,04/24/20,7:30,US,Durable Goods Orders MoM MAR,-0.144,1.10%,-0.119,-0.12
+Wednesday,04/29/20,4:25,EA,Business Confidence APR,-1.81,-0.28,,-1.24
+Wednesday,04/29/20,20:00,CN,NBS Manufacturing PMI APR,50.8,52,51,47.6
+Wednesday,04/29/20,21:45,CN,Caixin Manufacturing PMI APR,49.4,50.1,50.3,47.8
+Thursday,04/30/20,0:00,JP,Consumer Confidence APR,21.6,30.9,,22.3
+Thursday,04/30/20,7:30,US,Personal Income MoM MAR,-0.02,0.60%,-0.015,-0.01
+Thursday,04/30/20,7:30,US,Personal Spending MoM MAR,-0.075,0.20%,-0.05,-0.063
+Tuesday,05/05/20,7:30,CA,Balance of Trade MAR,-1.41B,-0.89B,-2B, -1.5B
+Tuesday,05/05/20,7:30,US,Balance of Trade MAR,-44.4B,-39.8B,-44B,-44.2B
+Thursday,05/07/20,9:00,CA,Ivey PMI s.a APR,22.8,26,25,20
+Thursday,05/07/20,7:30,US,Non Farm Payrolls APR,-20500K,-870K,-22000K,-21780K
+Thursday,05/07/20,20:30,CN,Inflation Rate YoY APR,0.033,4.30%,0.037,0.036
+Tuesday,05/12/20,7:30,US,Core Inflation Rate YoY APR,0.014,2.10%,0.017,0.016
+Tuesday,05/12/20,7:30,US,Inflation Rate YoY APR,0.003,1.50%,0.004,0.005
+Wednesday,05/13/20,1:00,GB,Balance of Trade MAR,-6.7B,-1.5B,,-1.7B
+Wednesday,05/13/20,7:30,US,Retail Sales MoM APR,-0.164,-8.30%,-0.12,-0.118
+Tuesday,05/19/20,1:00,GB,Claimant Count Change APR,856.5K,12.1K,676.5K,650K
+Tuesday,05/19/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,0.0385,0.0385
+Wednesday,05/20/20,1:00,GB,Inflation Rate YoY APR,0.008,1.50%,0.009,0.008
+Wednesday,05/20/20,7:30,CA,Inflation Rate YoY APR,-0.002,0.90%,-0.001,-0.001
+Wednesday,05/20/20,18:50,JP,Balance of Trade APR,-930B,5.4B,-560B,-480B
+Thursday,05/21/20,18:01,GB,Gfk Consumer Confidence 05,-34,-33,,-42
+Thursday,05/21/20,18:30,JP,Inflation Rate YoY APR,0.001,0.40%,,0.002
+Thursday,05/21/20,,CN,National People’s Congress,,,,
+Thursday,05/28/20,4:00,EA,Business Confidence 05,-2.43,-1.99,,-3
+Thursday,05/28/20,7:30,US,Durable Goods Orders MoM APR,-0.172,-16.60%,-0.19,-0.19
+Thursday,05/28/20,0:00,JP,Consumer Confidence 05,24,21.6,,25.1
+Thursday,05/28/20,7:30,US,Personal Income MoM APR,0.105,-2.20%,-0.065,-0.066
+Thursday,05/28/20,7:30,US,Personal Spending MoM APR,-0.136,-6.90%,-0.126,-0.114
+Saturday,05/30/20,20:00,CN,NBS Manufacturing PMI 05,50.6,50.8,51,50.5
+Saturday,05/30/20,20:45,CN,Caixin Manufacturing PMI 05,50.7,49.4,49.6,49.5
+Thursday,06/04/20,7:30,CA,Balance of Trade APR,-3.25B,-1.53B,-2.36B, 0.5B
+Thursday,06/04/20,7:30,US,Balance of Trade APR,-49.4B,-42.3B,-49B, -54.3B
+Thursday,06/04/20,18:01,GB,Gfk Consumer Confidence Final 05,-36,-33,-34,-34
+Friday,06/05/20,7:30,US,Non Farm Payrolls 05,2509K,-20687K,-8000K,-8870K
+Friday,06/05/20,9:00,CA,Ivey PMI s.a 05,39.1,22.8,,25
+Tuesday,06/09/20,20:30,CN,Inflation Rate YoY 05,0.024,3.30%,0.027,0.027
+Wednesday,06/10/20,7:30,US,Core Inflation Rate YoY 05,0.012,1.40%,0.013,0.012
+Wednesday,06/10/20,7:30,US,Inflation Rate YoY 05,0.001,0.30%,0.002,0.002
+Friday,06/12/20,1:00,GB,Balance of Trade APR,0.31B,-3.96B,,-6.2B
+Tuesday,06/16/20,1:00,GB,Claimant Count Change 05,528.9K,1032.7K,400K,330K
+Tuesday,06/16/20,7:30,US,Retail Sales MoM 05,0.177,-14.70%,0.08,0.075
+Tuesday,06/16/20,18:50,JP,Balance of Trade 05,-833.4B,-931.9B,-970.8B,-880B
+Wednesday,06/17/20,1:00,GB,Inflation Rate YoY 05,0.005,0.80%,0.005,0.005
+Wednesday,06/17/20,7:30,CA,Inflation Rate YoY 05,-0.004,-0.20%,0,0
+Thursday,06/18/20,18:30,JP,Inflation Rate YoY 05,0.001,0.10%,0.001,0.001
+Sunday,06/21/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.037
+Thursday,06/25/20,7:30,US,Durable Goods Orders MoM 05,0.158,-18.10%,0.109,0.085
+Friday,06/26/20,7:30,US,Personal Income MoM 05,-0.042,10.80%,-0.06,-0.056
+Friday,06/26/20,7:30,US,Personal Spending MoM 05,0.082,-12.60%,0.09,0.095
+Monday,06/29/20,20:00,CN,NBS Manufacturing PMI JUN,50.9,50.6,50.4,50.2
+Tuesday,06/30/20,18:50,JP,Tankan Large Manufacturers Index Q2,-34,-8,-31,-34
+Tuesday,06/30/20,20:45,CN,Caixin Manufacturing PMI JUN,51.2,50.7,50.5,50.3
+Wednesday,07/01/20,0:00,JP,Consumer Confidence JUN,28.4,24,,30
+Thursday,07/02/20,7:30,CA,Balance of Trade 05,-0.68B,-4.27B,-3B, -2.8B
+Thursday,07/02/20,7:30,US,Balance of Trade 05,-54.6B,-49.8B,-53B, -53B
+Thursday,07/02/20,7:30,US,Non Farm Payrolls JUN,4800K,2699K,3000K,2900K
+Thursday,07/02/20,18:01,GB,Gfk Consumer Confidence Final JUN,-27,-30,,-32
+Tuesday,07/07/20,9:00,CA,Ivey PMI s.a JUN,58.2,39.1,,43
+Wednesday,07/08/20,6:30,GB,Supplementary Budget,,,,
+Wednesday,07/08/20,20:30,CN,Inflation Rate YoY JUN,0.025,2.40%,0.025,0.025
+Thursday,07/09/20,,EA,Eurogroup Meeting,,,,
+Tuesday,07/14/20,1:00,GB,Balance of Trade 05,4.3B,2.3B,,-0.8B
+Tuesday,07/14/20,7:30,US,Core Inflation Rate YoY JUN,0.012,1.20%,0.011,0.012
+Tuesday,07/14/20,7:30,US,Inflation Rate YoY JUN,0.006,0.10%,0.006,0.005
+Wednesday,07/15/20,1:00,GB,Inflation Rate YoY JUN,0.006,0.50%,0.004,0.006
+Thursday,07/16/20,1:00,GB,Claimant Count Change JUN,-28.1K,566.4K,250K,210K
+Thursday,07/16/20,7:30,US,Retail Sales MoM JUN,0.075,18.20%,0.05,0.045
+Sunday,07/19/20,18:50,JP,Balance of Trade JUN,-268.8B,-838.2B,-35.8B,-40B
+Sunday,07/19/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,0.0385,0.0385
+Monday,07/20/20,18:30,JP,Inflation Rate YoY JUN,0.001,0.10%,,0.001
+Wednesday,07/22/20,7:30,CA,Inflation Rate YoY JUN,0.007,-0.40%,0.003,0.003
+Thursday,07/23/20,18:01,GB,Gfk Consumer Confidence JUL,-27,-30,-26,-26
+Monday,07/27/20,7:30,US,Durable Goods Orders MoM JUN,0.073,15.10%,0.07,0.05
+Thursday,07/30/20,20:00,CN,NBS Manufacturing PMI JUL,51.1,50.9,50.7,51
+Friday,07/31/20,0:00,JP,Consumer Confidence JUL,29.5,28.4,,26
+Friday,07/31/20,7:30,US,Personal Income MoM JUN,-0.011,-4.40%,-0.005,-0.003
+Friday,07/31/20,7:30,US,Personal Spending MoM JUN,0.056,8.50%,0.055,0.053
+Sunday,08/02/20,20:45,CN,Caixin Manufacturing PMI JUL,52.8,51.2,51.3,51.6
+Wednesday,08/05/20,7:30,CA,Balance of Trade JUN,-3.19B,-1.33B,-0.9B, -1B
+Wednesday,08/05/20,7:30,US,Balance of Trade JUN,-50.7B,-54.8B,-50.1B,-50.7B
+Friday,08/07/20,7:30,US,Non Farm Payrolls JUL,1763K,4800K,1600K,1620K
+Friday,08/07/20,9:00,CA,Ivey PMI s.a JUL,68.5,58.2,57.5,57.9
+Sunday,08/09/20,20:30,CN,Inflation Rate YoY JUL,0.027,2.50%,0.026,0.027
+Tuesday,08/11/20,1:00,GB,Claimant Count Change JUL,94.4K,-28.1K,10K,5K
+Wednesday,08/12/20,1:00,GB,Balance of Trade JUN,5.3B,7.7B,,2.8B
+Wednesday,08/12/20,7:30,US,Core Inflation Rate YoY JUL,0.016,1.20%,0.011,0.01
+Wednesday,08/12/20,7:30,US,Inflation Rate YoY JUL,0.01,0.60%,0.008,0.007
+Friday,08/14/20,7:30,US,Retail Sales MoM JUL,0.012,8.40%,0.019,0.02
+Tuesday,08/18/20,18:50,JP,Balance of Trade JUL,11.6B,-269.3B,-77.6B,-120B
+Wednesday,08/19/20,1:00,GB,Inflation Rate YoY JUL,0.01,0.60%,0.006,0.007
+Wednesday,08/19/20,7:30,CA,Inflation Rate YoY JUL,0.001,0.70%,0.005,0.005
+Wednesday,08/19/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385
+Thursday,08/20/20,18:01,GB,Gfk Consumer Confidence AUG,-27,-27,-25,-24
+Thursday,08/20/20,18:30,JP,Inflation Rate YoY JUL,0.003,0.10%,,0.001
+Wednesday,08/26/20,7:30,US,Durable Goods Orders MoM JUL,0.112,7.70%,0.043,0.039
+Friday,08/28/20,7:30,US,Personal Income MoM JUL,0.004,-1%,-0.002,-0.004
+Friday,08/28/20,7:30,US,Personal Spending MoM JUL,0.019,6.20%,0.015,0.012
+Sunday,08/30/20,20:00,CN,NBS Manufacturing PMI AUG,51,51.1,51.2,51.3
+Monday,08/31/20,0:00,JP,Consumer Confidence AUG,29.3,29.5,,29
+Monday,08/31/20,20:45,CN,Caixin Manufacturing PMI AUG,53.1,52.8,52.6,52.4
+Thursday,09/03/20,7:30,CA,Balance of Trade JUL,-2.45B,-1.59B,-2.5B, -2.3B
+Thursday,09/03/20,7:30,US,Balance of Trade JUL,-63.6B,-53.5B,-58B, -59B
+Friday,09/04/20,7:30,US,Non Farm Payrolls AUG,1371K,1734K,1400K,1490K
+Friday,09/04/20,9:00,CA,Ivey PMI s.a AUG,67.8,68.5,,68.7
+Tuesday,09/08/20,20:30,CN,Inflation Rate YoY AUG,0.024,2.70%,0.024,0.025
+Friday,09/11/20,1:00,GB,Balance of Trade JUL,1.1B,3.9B,,1.2B
+Friday,09/11/20,7:30,US,Core Inflation Rate YoY AUG,0.017,1.60%,0.016,0.015
+Friday,09/11/20,7:30,US,Inflation Rate YoY AUG,0.013,1%,0.012,0.011
+Friday,09/11/20,,EA,Eurogroup Meeting,,,,
+Tuesday,09/15/20,1:00,GB,Claimant Count Change AUG,73.7K,69.9K,100K,51K
+Tuesday,09/15/20,18:50,JP,Balance of Trade AUG,248.3B,10.9B,-37.5B,-50B
+Wednesday,09/16/20,1:00,GB,Inflation Rate YoY AUG,0.002,1%,0,0.001
+Wednesday,09/16/20,7:30,CA,Inflation Rate YoY AUG,0.001,0.10%,0.004,0.003
+Wednesday,09/16/20,7:30,US,Retail Sales MoM AUG,0.006,0.90%,0.01,0.01
+Thursday,09/17/20,18:30,JP,Inflation Rate YoY AUG,0.002,0.30%,,0.001
+Sunday,09/20/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,0.0385,0.0385
+Thursday,09/24/20,6:30,GB,Winter Economy Plan,,,,
+Thursday,09/24/20,18:01,GB,Gfk Consumer Confidence SEP,-25,-27,-27,-26
+Friday,09/25/20,7:30,US,Durable Goods Orders MoM AUG,0.004,11.70%,0.015,0.02
+Tuesday,09/29/20,20:00,CN,NBS Manufacturing PMI SEP,51.5,51,51.2,51.4
+Tuesday,09/29/20,20:45,CN,Caixin Manufacturing PMI SEP,53,53.1,53.1,53.4
+Wednesday,09/30/20,18:50,JP,Tankan Large Manufacturers Index Q3,-27,-34,-23,-26
+Thursday,10/01/20,7:30,US,Personal Income MoM AUG,-0.027,0.50%,-0.024,-0.02
+Thursday,10/01/20,7:30,US,Personal Spending MoM AUG,0.01,1.50%,0.008,0.008
+Friday,10/02/20,0:00,JP,Consumer Confidence SEP,32.7,29.3,,32
+Friday,10/02/20,7:30,US,Non Farm Payrolls SEP,661K,1489K,850K,915K
+Monday,10/05/20,,EA,Eurogroup Video Conference,,,,
+Tuesday,10/06/20,7:30,CA,Balance of Trade AUG,-2.45B,-2.53B,-2B, -2.1B
+Tuesday,10/06/20,7:30,US,Balance of Trade AUG,-67.1B,-63.4B,-66.1B, -66.5B
+Wednesday,10/07/20,9:00,CA,Ivey PMI s.a SEP,54.3,67.8,,68
+Friday,10/09/20,1:00,GB,Balance of Trade AUG,1.4B,1.7B,,0.6B
+Tuesday,10/13/20,1:00,GB,Claimant Count Change SEP,28K,39.5K,78.8K,72K
+Tuesday,10/13/20,7:30,US,Core Inflation Rate YoY SEP,0.017,1.70%,0.018,0.017
+Tuesday,10/13/20,7:30,US,Inflation Rate YoY SEP,0.014,1.30%,0.014,0.015
+Wednesday,10/14/20,20:30,CN,Inflation Rate YoY SEP,0.017,2.40%,0.018,0.02
+Friday,10/16/20,7:30,US,Retail Sales MoM SEP,0.019,0.60%,0.007,0.005
+Sunday,10/18/20,18:50,JP,Balance of Trade SEP,675B,248.6B,989.8B, 900B
+Monday,10/19/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,0.0385,0.0385
+Wednesday,10/21/20,1:00,GB,Inflation Rate YoY SEP,0.005,0.20%,0.005,0.004
+Wednesday,10/21/20,7:30,CA,Inflation Rate YoY SEP,0.005,0.10%,0.004,0.003
+Thursday,10/22/20,18:01,GB,Gfk Consumer Confidence OCT,-31,-30,-28,-26
+Thursday,10/22/20,18:30,JP,Inflation Rate YoY SEP,0,0.20%,,0.001
+Tuesday,10/27/20,7:30,US,Durable Goods Orders MoM SEP,0.019,0.40%,0.005,0.004
+Thursday,10/29/20,0:00,JP,Consumer Confidence OCT,33.6,32.7,,34.8
+Friday,10/30/20,7:30,US,Personal Income MoM SEP,0.009,-2.50%,0.004,0.004
+Friday,10/30/20,7:30,US,Personal Spending MoM SEP,0.014,1%,0.01,0.008
+Friday,10/30/20,20:00,CN,NBS Manufacturing PMI OCT,51.4,51.5,51.3,51.4
+Sunday,11/01/20,20:45,CN,Caixin Manufacturing PMI OCT,53.6,53,53,52.8
+Monday,11/02/20,,US,Presidential Election,,,,
+Tuesday,11/03/20,,EA,Eurogroup Video Conference,,,,
+Wednesday,11/04/20,8:30,CA,Balance of Trade SEP,-3.25B,-3.21B,-2.6B, -2.6B
+Wednesday,11/04/20,8:30,US,Balance of Trade SEP,-63.9B,-67B,-63.8B, -63.1B
+Friday,11/06/20,8:30,US,Non Farm Payrolls OCT,638K,672K,600K,510K
+Friday,11/06/20,10:00,CA,Ivey PMI s.a OCT,54.5,54.3,51.5,52
+Monday,11/09/20,20:30,CN,Inflation Rate YoY OCT,0.005,1.70%,0.008,0.01
+Tuesday,11/10/20,2:00,GB,Claimant Count Change OCT,-29.8K,-40.2K,50K,36K
+Thursday,11/12/20,2:00,GB,Balance of Trade SEP,0.6B,2.9B,,-1.0B
+Thursday,11/12/20,8:30,US,Core Inflation Rate YoY OCT,0.016,1.70%,0.018,0.018
+Thursday,11/12/20,8:30,US,Inflation Rate YoY OCT,0.012,1.40%,0.013,0.015
+Tuesday,11/17/20,8:30,US,Retail Sales MoM OCT,0.003,1.60%,0.005,0.004
+Tuesday,11/17/20,18:50,JP,Balance of Trade OCT,872.9B,687.8B,250B,210B
+Wednesday,11/18/20,2:00,GB,Inflation Rate YoY OCT,0.007,0.50%,0.006,0.007
+Wednesday,11/18/20,8:30,CA,Inflation Rate YoY OCT,0.007,0.50%,0.004,0.003
+Thursday,11/19/20,18:30,JP,Inflation Rate YoY OCT,-0.004,0%,-0.003,-0.002
+Thursday,11/19/20,19:01,GB,GfK Consumer Confidence NOV,-33,-31,-34,-33
+Thursday,11/19/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385
+Wednesday,11/25/20,8:30,US,Durable Goods Orders MoM OCT,0.013,2.10%,0.009,0.008
+Wednesday,11/25/20,10:00,US,Personal Income MoM OCT,-0.007,0.70%,0,0.002
+Wednesday,11/25/20,10:00,US,Personal Spending MoM OCT,0.005,1.20%,0.004,0.005
+Sunday,11/29/20,20:00,CN,NBS Manufacturing PMI NOV,52.1,51.4,51.5,51
+Monday,11/30/20,20:45,CN,Caixin Manufacturing PMI NOV,54.9,53.6,53.5,53.2
+Monday,11/30/20,,EA,Eurogroup Video Conference,,,,
+Wednesday,12/02/20,0:00,JP,Consumer Confidence NOV,33.7,33.6,,33
+Friday,12/04/20,8:30,CA,Balance of Trade OCT,-3.76B,-3.8B,-3B,-3.5B
+Friday,12/04/20,8:30,US,Balance of Trade OCT,-63.1B,-62.1B,-64.8B,-65B
+Friday,12/04/20,8:30,US,Non Farm Payrolls NOV,245K,610K,469K,500K
+Monday,12/07/20,10:00,CA,Ivey PMI s.a NOV,52.7,54.5,54.7,54
+Tuesday,12/08/20,20:30,CN,Inflation Rate YoY NOV,-0.005,0.50%,0,0.001
+Thursday,12/10/20,2:00,GB,Balance of Trade OCT,-1.7B,0.6B,,0.5B
+Thursday,12/10/20,8:30,US,Core Inflation Rate YoY NOV,0.016,1.60%,0.016,0.016
+Thursday,12/10/20,8:30,US,Inflation Rate YoY NOV,0.012,1.20%,0.011,0.012
+Sunday,12/13/20,18:50,JP,Tankan Large Manufacturers Index Q4,-10,-27,-15,-17
+Tuesday,12/15/20,2:00,GB,Claimant Count Change NOV,64.3K,-29.8K,,30K
+Tuesday,12/15/20,18:50,JP,Balance of Trade NOV,366.8B,871.7B,529.8B,510B
+Wednesday,12/16/20,2:00,GB,Inflation Rate YoY NOV,0.003,0.70%,0.006,0.008
+Wednesday,12/16/20,8:30,CA,Inflation Rate YoY NOV,0.01,0.70%,0.008,0.008
+Wednesday,12/16/20,8:30,US,Retail Sales MoM NOV,-0.011,-0.10%,-0.003,-0.003
+Wednesday,12/16/20,,EA,Eurogroup Video Conference,,,,
+Thursday,12/17/20,18:30,JP,Inflation Rate YoY NOV,-0.009,-0.40%,,-0.005
+Thursday,12/17/20,19:01,GB,GfK Consumer Confidence DEC,-26,-33,-31,-30
+Sunday,12/20/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,0.0385,0.0385
+Wednesday,12/23/20,8:30,US,Durable Goods Orders MoM NOV,0.009,1.80%,0.006,0.006
+Wednesday,12/23/20,8:30,US,Personal Income MoM NOV,-0.011,-0.60%,-0.003,-0.004
+Wednesday,12/23/20,8:30,US,Personal Spending MoM NOV,-0.004,0.30%,-0.002,-0.004
+Wednesday,12/30/20,20:00,CN,NBS Manufacturing PMI DEC,51.9,52.1,52,51.5
+Sunday,01/03/21,20:45,CN,Caixin Manufacturing PMI DEC,53,54.9,54.8,54.6
+Wednesday,01/06/21,0:00,JP,Consumer Confidence DEC,31.8,33.7,,35
+Thursday,01/07/21,8:30,CA,Balance of Trade NOV,-3.34B,-3.73B,-3.5B,-3.2B
+Thursday,01/07/21,8:30,US,Balance of Trade NOV,-68.1B,-63.1B,-65.2B,-67.6B
+Thursday,01/07/21,10:00,CA,Ivey PMI s.a DEC,46.7,52.7,,53.2
+Friday,01/08/21,8:30,US,Non Farm Payrolls DEC,-140K,336K,71K,112K
+Sunday,01/10/21,20:30,CN,Inflation Rate YoY DEC,0.002,-0.50%,0.001,0
+Wednesday,01/13/21,8:30,US,Core Inflation Rate YoY DEC,0.016,1.60%,0.016,0.016
+Wednesday,01/13/21,8:30,US,Inflation Rate YoY DEC,0.014,1.20%,0.013,0.012
+Friday,01/15/21,2:00,GB,Balance of Trade NOV,-5B,-2.3B,,-1.2B
+Friday,01/15/21,8:30,US,Retail Sales MoM DEC,-0.007,-1.40%,0,-0.002
+Tuesday,01/19/21,10:00,US,Treasury Secretary Yellen Senate Confirmation Hearing,,,,
+Tuesday,01/19/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385
+Wednesday,01/20/21,2:00,GB,Inflation Rate YoY DEC,0.006,0.30%,0.005,0.006
+Wednesday,01/20/21,8:30,CA,Inflation Rate YoY DEC,0.007,1%,0.01,0.01
+Wednesday,01/20/21,18:50,JP,Balance of Trade DEC,751B,366.8B,942.8B,800B
+Thursday,01/21/21,18:30,JP,Inflation Rate YoY DEC,-0.012,-0.90%,,-0.01
+Thursday,01/21/21,19:01,GB,Gfk Consumer Confidence JAN,-28,-26,-29,-28
+Tuesday,01/26/21,2:00,GB,Claimant Count Change DEC,7K,38.1K,35K,40K
+Wednesday,01/27/21,8:30,US,Durable Goods Orders MoM DEC,0.002,1.20%,0.009,0.008
+Wednesday,01/27/21,14:30,US,Fed Press Conference,,,,
+Friday,01/29/21,0:00,JP,Consumer Confidence JAN,29.6,31.8,,31.2
+Friday,01/29/21,8:30,US,Personal Income MoM DEC,0.006,-1.30%,0.001,0.001
+Friday,01/29/21,8:30,US,Personal Spending MoM DEC,-0.002,-0.70%,-0.004,-0.006
+Saturday,01/30/21,20:00,CN,NBS Manufacturing PMI JAN,51.3,51.9,51.6,51.5
+Sunday,01/31/21,20:45,CN,Caixin Manufacturing PMI JAN,51.5,53,52.7,52.5
+Friday,02/05/21,8:30,CA,Balance of Trade DEC,-1.67B,-3.56B,-3B, -3.2B
+Friday,02/05/21,8:30,US,Balance of Trade DEC,-66.6B,-69B,-65.7B,-70B
+Friday,02/05/21,8:30,US,Non Farm Payrolls JAN,49K,-227K,50K,45K
+Friday,02/05/21,10:00,CA,Ivey PMI s.a JAN,48.4,46.7,,47
+Tuesday,02/09/21,20:30,CN,Inflation Rate YoY JAN,-0.003,0.20%,0,-0.002
+Wednesday,02/10/21,8:30,US,Core Inflation Rate YoY JAN,0.014,1.60%,0.015,0.016
+Wednesday,02/10/21,8:30,US,Inflation Rate YoY JAN,0.014,1.40%,0.015,0.014
+Friday,02/12/21,2:00,GB,Balance of Trade DEC,-6.2B,-6.6B,,-4.2B
+Tuesday,02/16/21,18:50,JP,Balance of Trade JAN,-323.9B,749.6B,-600B,-430B
+Wednesday,02/17/21,2:00,GB,Inflation Rate YoY JAN,0.007,0.60%,0.006,0.004
+Wednesday,02/17/21,8:30,CA,Inflation Rate YoY JAN,0.01,0.70%,0.009,0.008
+Wednesday,02/17/21,8:30,US,Retail Sales MoM JAN,0.053,-1%,0.011,0.009
+Wednesday,02/17/21,14:00,US,FOMC Minutes,,,,
+Thursday,02/18/21,18:30,JP,Inflation Rate YoY JAN,-0.006,-1.20%,,-0.01
+Thursday,02/18/21,19:01,GB,Gfk Consumer Confidence FEB,-23,-28,-27,-26
+Friday,02/19/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385
+Tuesday,02/23/21,2:00,GB,Claimant Count Change JAN,-20K,-20.4K,,25K
+Thursday,02/25/21,8:30,US,Durable Goods Orders MoM JAN,0.034,1.20%,0.011,0.012
+Friday,02/26/21,8:30,US,Personal Income MoM JAN,0.1,0.60%,0.095,0.085
+Friday,02/26/21,8:30,US,Personal Spending MoM JAN,0.024,-0.40%,0.025,0.019
+Sunday,02/28/21,3:00,CN,NBS Manufacturing PMI FEB,50.6,51.3,51.1,51
+Sunday,02/28/21,20:45,CN,Caixin Manufacturing PMI FEB,50.9,51.5,51.5,51.2
+Thursday,03/04/21,0:00,JP,Consumer Confidence FEB,33.8,29.6,,30.8
+Thursday,03/04/21,,CN,National People's Congress,,,,
+Thursday,03/04/21,,CN,Premier Li Keqiang Speech ,,,,
+Friday,03/05/21,8:30,CA,Balance of Trade JAN,1.41B,-1.98B,-1.4B, -1.6B
+Friday,03/05/21,8:30,US,Balance of Trade JAN,-68.2B,-67B,-67.5B,-67.5B
+Friday,03/05/21,8:30,US,Non Farm Payrolls FEB,379K,166K,182K,170K
+Friday,03/05/21,10:00,CA,Ivey PMI s.a FEB,60,48.4,,49
+Tuesday,03/09/21,20:30,CN,Inflation Rate YoY FEB,-0.002,-0.30%,-0.004,-0.003
+Wednesday,03/10/21,8:30,US,Core Inflation Rate YoY FEB,0.013,1.40%,0.014,0.014
+Wednesday,03/10/21,8:30,US,Inflation Rate YoY FEB,0.017,1.40%,0.017,0.016
+Friday,03/12/21,2:00,GB,Balance of Trade JAN,-1.6B,-6.2B,,-4.8B
+Tuesday,03/16/21,7:30,US,Retail Sales MoM FEB,-0.03,7.60%,-0.005,-0.006
+Tuesday,03/16/21,18:50,JP,Balance of Trade FEB,217.4B,-325.4B,420B,450B
+Wednesday,03/17/21,7:30,CA,Inflation Rate YoY FEB,0.011,1%,0.013,0.011
+Wednesday,03/17/21,13:30,US,Fed Press Conference,,,,
+Thursday,03/18/21,18:30,JP,Inflation Rate YoY FEB,-0.004,-0.60%,,-0.004
+Thursday,03/18/21,19:01,GB,Gfk Consumer Confidence MAR,-16,-23,-20,-20
+Tuesday,03/23/21,2:00,GB,Claimant Count Change FEB,86.6K,-20.8K,,-17K
+Wednesday,03/24/21,2:00,GB,Inflation Rate YoY FEB,0.004,0.70%,0.008,0.008
+Wednesday,03/24/21,7:30,US,Durable Goods Orders MoM FEB,-0.011,3.50%,0.008,0.011
+Friday,03/26/21,7:30,US,Personal Income MoM FEB,-0.071,10.10%,-0.073,-0.08
+Friday,03/26/21,7:30,US,Personal Spending MoM FEB,-0.01,3.40%,-0.007,-0.007
+Tuesday,03/30/21,20:00,CN,NBS Manufacturing PMI MAR,51.9,50.6,51,51.1
+Tuesday,03/30/21,,US,President Biden Speech on Recovery Package ,,,,
+Wednesday,03/31/21,18:50,JP,Tankan Large Manufacturers Index Q1,5,-10,0,-2
+Wednesday,03/31/21,20:45,CN,Caixin Manufacturing PMI MAR,50.6,50.9,51.3,51.2
+Friday,04/02/21,7:30,US,Non Farm Payrolls MAR,916K,468K,647K,680K
+Wednesday,04/07/21,7:30,CA,Balance of Trade FEB,1.04B,1.21B,1B,1.5B
+Wednesday,04/07/21,7:30,US,Balance of Trade FEB,-71.1B,-67.8B,-70.5B,-69.8B
+Wednesday,04/07/21,9:00,CA,Ivey PMI s.a MAR,72.9,60,60.5,62
+Wednesday,04/07/21,13:00,US,FOMC Minutes,,,,
+Thursday,04/08/21,0:00,JP,Consumer Confidence MAR,36.1,33.8,,36
+Thursday,04/08/21,20:30,CN,Inflation Rate YoY MAR,0.004,-0.20%,0.003,0.002
+Tuesday,04/13/21,1:00,GB,Balance of Trade FEB,-7.1B,-3.4B,,-2.2B
+Tuesday,04/13/21,7:30,US,Core Inflation Rate YoY MAR,0.016,1.30%,0.015,0.016
+Tuesday,04/13/21,7:30,US,Inflation Rate YoY MAR,0.026,1.70%,0.025,0.026
+Thursday,04/15/21,7:30,US,Retail Sales MoM MAR,0.098,-2.70%,0.059,0.045
+Sunday,04/18/21,18:50,JP,Balance of Trade MAR,663.7B,215.9B,490B, 300B
+Monday,04/19/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,0.0385,0.0385
+Tuesday,04/20/21,1:00,GB,Claimant Count Change MAR,10.1K,86.6K,,150K
+Wednesday,04/21/21,1:00,GB,Inflation Rate YoY MAR,0.007,0.40%,0.008,0.008
+Wednesday,04/21/21,7:30,CA,Inflation Rate YoY MAR,0.022,1.10%,0.023,0.021
+Thursday,04/22/21,18:01,GB,Gfk Consumer Confidence APR,-15,-16,-12,-12
+Thursday,04/22/21,18:30,JP,Inflation Rate YoY MAR,-0.002,-0.40%,,-0.001
+Monday,04/26/21,7:30,US,Durable Goods Orders MoM MAR,0.005,-0.90%,0.025,0.017
+Wednesday,04/28/21,13:30,US,Fed Press Conference,,,,
+Thursday,04/29/21,20:00,CN,NBS Manufacturing PMI APR,51.1,51.9,51.7,52.1
+Thursday,04/29/21,20:45,CN,Caixin Manufacturing PMI APR,51.9,50.6,50.8,50.9
+Friday,04/30/21,0:00,JP,Consumer Confidence APR,34.7,36.1,,35.5
+Friday,04/30/21,7:30,US,Personal Income MoM MAR,0.211,-7%,0.203,0.205
+Friday,04/30/21,7:30,US,Personal Spending MoM MAR,0.042,-1%,0.041,0.046
+Tuesday,05/04/21,7:30,CA,Balance of Trade MAR,-1.14B,1.42B,0.7B,0.5B
+Tuesday,05/04/21,7:30,US,Balance of Trade MAR,-74.4B,-70.5B,-74.5B,-73.4B
+Tuesday,05/04/21,7:30,US,Non Farm Payrolls APR,266K,770K,978K,950K
+Tuesday,05/04/21,9:00,CA,Ivey PMI s.a APR,60.6,72.9,,67
+Tuesday,05/04/21,20:30,CN,Inflation Rate YoY APR,0.009,0.40%,0.01,0.011
+Wednesday,05/12/21,1:00,GB,Balance of Trade MAR,-2B,-0.9B,,-6.1B
+Wednesday,05/12/21,7:30,US,Core Inflation Rate YoY APR,0.03,1.60%,0.023,0.022
+Wednesday,05/12/21,7:30,US,Inflation Rate YoY APR,0.042,2.60%,0.036,0.038
+Wednesday,05/12/21,7:30,US,Retail Sales MoM APR,0,10.70%,0.01,0.003
+Tuesday,05/18/21,1:00,GB,Claimant Count Change APR,-15.1K,-19.4K,,25K
+Wednesday,05/19/21,1:00,GB,Inflation Rate YoY APR,0.015,0.70%,0.014,0.014
+Wednesday,05/19/21,7:30,CA,Inflation Rate YoY APR,0.034,2.20%,0.032,0.032
+Wednesday,05/19/21,13:00,US,FOMC Minutes,,,,
+Wednesday,05/19/21,18:50,JP,Balance of Trade APR,255.3B,662.2B,140B,150B
+Wednesday,05/19/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385
+Thursday,05/20/21,18:01,GB,Gfk Consumer Confidence 05,-9,-15,-12,-14
+Thursday,05/20/21,18:30,JP,Inflation Rate YoY APR,-0.004,-0.20%,,0.001
+Thursday,05/27/21,7:30,US,Durable Goods Orders MoM APR,-0.013,1.30%,0.007,0.007
+Thursday,05/27/21,7:30,US,Personal Income MoM APR,-0.131,20.90%,-0.141,-0.14
+Thursday,05/27/21,7:30,US,Personal Spending MoM APR,0.005,4.70%,0.005,0.005
+Thursday,05/27/21,20:00,CN,NBS Manufacturing PMI 05,51,51.1,51.1,51.2
+Thursday,05/27/21,0:00,JP,Consumer Confidence 05,34.1,34.7,,34
+Thursday,05/27/21,20:45,CN,Caixin Manufacturing PMI 05,52,51.9,51.9,51.7
+Friday,06/04/21,7:30,US,Non Farm Payrolls 05,559K,278K,650K,610K
+Friday,06/04/21,9:00,CA,Ivey PMI s.a 05,64.7,60.6,,65
+Tuesday,06/08/21,7:30,CA,Balance of Trade APR,0.59B,-1.35B,-0.7B,-0.9B
+Tuesday,06/08/21,7:30,US,Balance of Trade APR,-68.9B,-75B,-69B,-69B
+Tuesday,06/08/21,20:30,CN,Inflation Rate YoY 05,0.013,0.90%,0.016,0.015
+Thursday,06/10/21,7:30,US,Core Inflation Rate YoY 05,0.038,3%,0.034,0.032
+Thursday,06/10/21,7:30,US,Inflation Rate YoY 05,0.05,4.20%,0.047,0.047
+Friday,06/11/21,1:00,GB,Balance of Trade APR,-0.9B,-2B,,-3.2B
+Tuesday,06/15/21,1:00,GB,Claimant Count Change 05,-92.6K,-55.8K,,-62K
+Tuesday,06/15/21,7:30,US,Retail Sales MoM 05,-0.013,0.90%,-0.008,-0.003
+Tuesday,06/15/21,18:50,JP,Balance of Trade 05,-187.1B,253.1B,-91.2B,-78B
+Wednesday,06/16/21,1:00,GB,Inflation Rate YoY 05,0.021,1.50%,0.018,0.018
+Wednesday,06/16/21,7:30,CA,Inflation Rate YoY 05,0.036,3.40%,0.035,0.036
+Wednesday,06/16/21,13:30,US,Fed Press Conference,,,,
+Thursday,06/17/21,18:30,JP,Inflation Rate YoY 05,-0.001,-0.40%,,-0.003
+Sunday,06/20/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385
+Thursday,06/24/21,7:30,US,Durable Goods Orders MoM 05,0.023,-0.80%,0.028,0.02
+Thursday,06/24/21,18:01,GB,Gfk Consumer Confidence JUN,-9,-9,-7,-7
+Friday,06/25/21,7:30,US,Personal Income MoM 05,-0.02,-13.10%,-0.025,-0.03
+Friday,06/25/21,7:30,US,Personal Spending MoM 05,0,0.90%,0.004,0.004
+Tuesday,06/29/21,20:00,CN,NBS Manufacturing PMI JUN,50.9,51,50.8,50.9
+Wednesday,06/30/21,0:00,JP,Consumer Confidence JUN,37.4,34.1,,33
+Wednesday,06/30/21,18:50,JP,Tankan Large Manufacturers Index Q2,14,5,15,15
+Wednesday,06/30/21,20:45,CN,Caixin Manufacturing PMI JUN,51.3,52,51.8,51.9
+Friday,07/02/21,7:30,CA,Balance of Trade 05,-1.39B,0.46B,0.37B,-0.3B
+Friday,07/02/21,7:30,US,Balance of Trade 05,-71.2B,-69.1B,-71.4B,-71.6B
+Friday,07/02/21,7:30,US,Non Farm Payrolls JUN,850K,583K,700K,650K
+Wednesday,07/07/21,9:00,CA,Ivey PMI s.a JUN,71.9,64.7,,65
+Wednesday,07/07/21,13:00,US,FOMC Minutes,,,,
+Thursday,07/08/21,20:30,CN,Inflation Rate YoY JUN,0.011,1.30%,0.013,0.015
+Friday,07/09/21,6:00,GB,Balance of Trade 05,0.9B,-1.6B,,-1.4B
+Tuesday,07/13/21,7:30,US,Core Inflation Rate YoY JUN,0.045,3.80%,0.04,0.039
+Tuesday,07/13/21,7:30,US,Inflation Rate YoY JUN,0.054,5%,0.049,0.049
+Wednesday,07/14/21,1:00,GB,Inflation Rate YoY JUN,0.025,2.10%,0.022,0.023
+Thursday,07/15/21,1:00,GB,Claimant Count Change JUN,-114.8K,-92.6K,,-120K
+Friday,07/16/21,7:30,US,Retail Sales MoM JUN,0.006,-1.70%,-0.004,-0.005
+Monday,07/19/21,18:30,JP,Inflation Rate YoY JUN,0.002,-0.10%,,0
+Monday,07/19/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385
+Tuesday,07/20/21,18:50,JP,Balance of Trade JUN,383.2B,-189.4B,460B, 400B
+Thursday,07/22/21,18:01,GB,Gfk Consumer Confidence JUL,-7,-9,-8,-7
+Tuesday,07/27/21,7:30,US,Durable Goods Orders MoM JUN,0.008,3.20%,0.021,0.019
+Wednesday,07/28/21,7:30,CA,Inflation Rate YoY JUN,0.031,3.60%,0.032,0.031
+Wednesday,07/28/21,13:30,US,Fed Press Conference,,,,
+Friday,07/30/21,7:30,US,Personal Income MoM JUN,0.001,-2.20%,-0.003,-0.003
+Friday,07/30/21,7:30,US,Personal Spending MoM JUN,0.01,-0.10%,0.007,0.005
+Friday,07/30/21,20:00,CN,NBS Manufacturing PMI JUL,50.4,50.9,50.8,50.8
+Sunday,08/01/21,20:45,CN,Caixin Manufacturing PMI JUL,50.3,51.3,51,51
+Monday,08/02/21,0:00,JP,Consumer Confidence JUL,37.5,37.4,,37
+Thursday,08/05/21,7:30,CA,Balance of Trade JUN,3.23B,-1.58B,-0.68B, -0.7B
+Thursday,08/05/21,7:30,US,Balance of Trade JUN,-75.7B,-71B,-73.9B,-74.3B
+Friday,08/06/21,7:30,US,Non Farm Payrolls JUL,943K,938K,870K,900K
+Friday,08/06/21,9:00,CA,Ivey PMI s.a JUL,56.4,71.9,,70
+Sunday,08/08/21,20:30,CN,Inflation Rate YoY JUL,0.01,1.10%,0.008,0.009
+Wednesday,08/11/21,7:30,US,Core Inflation Rate YoY JUL,0.043,4.50%,0.043,0.044
+Wednesday,08/11/21,7:30,US,Inflation Rate YoY JUL,0.054,5.40%,0.053,0.054
+Thursday,08/12/21,1:00,GB,Balance of Trade JUN,-2.5B,-0.2B,,-2.2B
+Tuesday,08/17/21,1:00,GB,Claimant Count Change JUL,-7.8K,-114.8K,,-180K
+Tuesday,08/17/21,7:30,US,Retail Sales MoM JUL,-0.011,0.70%,-0.003,-0.003
+Tuesday,08/17/21,18:50,JP,Balance of Trade JUL,441B,384B,202.3B,300B
+Wednesday,08/18/21,1:00,GB,Inflation Rate YoY JUL,0.02,2.50%,0.023,0.024
+Wednesday,08/18/21,7:30,CA,Inflation Rate YoY JUL,0.037,3.10%,0.034,0.033
+Wednesday,08/18/21,13:00,US,FOMC Minutes,,,,
+Thursday,08/19/21,18:01,GB,Gfk Consumer Confidence AUG,-8,-7,-7,-6
+Thursday,08/19/21,18:30,JP,Inflation Rate YoY JUL,-0.003,-0.50%,,-0.001
+Thursday,08/19/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385
+Wednesday,08/25/21,7:30,US,Durable Goods Orders MoM JUL,-0.001,0.80%,-0.003,-0.002
+Friday,08/27/21,7:30,US,Personal Income MoM JUL,0.011,0.20%,0.002,0.002
+Friday,08/27/21,7:30,US,Personal Spending MoM JUL,0.003,1.10%,0.003,0.005
+Monday,08/30/21,20:00,CN,NBS Manufacturing PMI AUG,50.1,50.4,50.2,50.3
+Tuesday,08/31/21,0:00,JP,Consumer Confidence AUG,36.7,37.5,,37
+Tuesday,08/31/21,20:45,CN,Caixin Manufacturing PMI AUG,49.2,50.3,50.2,50.2
+Thursday,09/02/21,7:30,CA,Balance of Trade JUL,0.78B,2.56B,1.4B,2.5B
+Thursday,09/02/21,7:30,US,Balance of Trade JUL,-70B,-73.2B,-71B,-70B
+Friday,09/03/21,7:30,US,Non Farm Payrolls AUG,235K,1053K,750K,750K
+Wednesday,09/08/21,9:00,CA,Ivey PMI s.a AUG,66,56.4,,56
+Wednesday,09/08/21,20:30,CN,Inflation Rate YoY AUG,0.008,1.00%,0.01,0.01
+Friday,09/10/21,1:00,GB,Balance of Trade JUL,-3.1B,-2.5B,,-2B
+Tuesday,09/14/21,1:00,GB,Claimant Count Change AUG,-58.6K,-7.8K,,-26K
+Tuesday,09/14/21,7:30,US,Core Inflation Rate YoY AUG,0.04,4.30%,0.042,0.043
+Tuesday,09/14/21,7:30,US,Inflation Rate YoY AUG,0.053,5.40%,0.053,0.053
+Wednesday,09/15/21,1:00,GB,Inflation Rate YoY AUG,0.032,2%,0.029,0.029
+Wednesday,09/15/21,7:30,CA,Inflation Rate YoY AUG,0.041,3.70%,0.039,0.037
+Wednesday,09/15/21,18:50,JP,Balance of Trade AUG,-635.4B,439.4B,-47.7B,-60B
+Thursday,09/16/21,7:30,US,Retail Sales MoM AUG,0.007,-1.80%,-0.008,-0.007
+Tuesday,09/21/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385
+Wednesday,09/22/21,13:30,US,Fed Press Conference,,,,
+Thursday,09/23/21,18:01,GB,Gfk Consumer Confidence SEP,-13,-8,-8,-8
+Thursday,09/23/21,18:30,JP,Inflation Rate YoY AUG,-0.004,-0.30%,,-0.001
+Monday,09/27/21,7:30,US,Durable Goods Orders MoM AUG,0.018,0.50%,0.007,0.004
+Wednesday,09/29/21,20:00,CN,NBS Manufacturing PMI SEP,49.6,50.1,50.1,50.4
+Wednesday,09/29/21,20:45,CN,Caixin Manufacturing PMI SEP,50,49.2,49.5,49.9
+Thursday,09/30/21,18:50,JP,Tankan Large Manufacturers Index Q3,18,14,13,12
+Friday,10/01/21,0:00,JP,Consumer Confidence SEP,37.8,36.7,,37
+Friday,10/01/21,4:00,EA,Inflation Rate YoY Flash SEP,0.034,3%,0.033,0.031
+Friday,10/01/21,7:30,US,Personal Income MoM AUG,0.002,1.10%,0.003,0.002
+Friday,10/01/21,7:30,US,Personal Spending MoM AUG,0.008,-0.10%,0.006,0.003
+Friday,10/01/21,9:00,US,ISM Manufacturing PMI SEP,61.1,59.9,59.6,59
+Tuesday,10/05/21,7:30,CA,Balance of Trade AUG,1.94B,0.74B,0.43B,0.6B
+Tuesday,10/05/21,7:30,US,Balance of Trade AUG,-73.3B,-70.3B,-70.5B,-70.8B
+Thursday,10/07/21,9:00,CA,Ivey PMI s.a SEP,70.4,66,,64.2
+Friday,10/08/21,7:30,US,Non Farm Payrolls SEP,194K,366K,500K,475K
+Tuesday,10/12/21,1:00,GB,Claimant Count Change SEP,-51.1K,-58.6K,,-46K
+Tuesday,10/12/21,9:00,US,JOLTs Job Openings AUG,10.439M,11.098M,10.925M,10.8M
+Tuesday,10/12/21,22:00,CN,Exports YoY SEP,0.281,25.60%,0.21,0.21
+Tuesday,10/12/21,22:00,CN,Imports YoY SEP,0.176,33.10%,0.2,0.21
+Wednesday,10/13/21,1:00,GB,Balance of Trade AUG,-3.7B,-2.9B,,-2.8B
+Wednesday,10/13/21,7:30,US,Core Inflation Rate YoY SEP,0.04,4%,0.04,0.04
+Wednesday,10/13/21,7:30,US,Inflation Rate YoY SEP,0.054,5.30%,0.053,0.053
+Wednesday,10/13/21,13:00,US,FOMC Minutes,,,,
+Wednesday,10/13/21,20:30,CN,Inflation Rate YoY SEP,0.007,0.80%,0.009,0.008
+Friday,10/15/21,7:30,US,Retail Sales MoM SEP,0.007,0.90%,-0.002,-0.001
+Friday,10/15/21,9:00,US,Michigan Consumer Sentiment Prel OCT,71.4,72.8,73.1,75
+Sunday,10/17/21,21:00,CN,Industrial Production YoY SEP,0.031,5.30%,0.045,0.044
+Sunday,10/17/21,21:00,CN,Retail Sales YoY SEP,0.044,2.50%,0.033,0.023
+Tuesday,10/19/21,7:30,US,Building Permits SEP,1.589M,1.721M,1.68M,1.69M
+Tuesday,10/19/21,18:50,JP,Balance of Trade SEP,-622.8B,-637.2B,-519.2B, -500B
+Tuesday,10/19/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385
+Wednesday,10/20/21,1:00,GB,Inflation Rate YoY SEP,0.031,3.20%,0.032,0.032
+Wednesday,10/20/21,7:30,CA,Inflation Rate YoY SEP,0.044,4.10%,0.043,0.044
+Thursday,10/21/21,18:01,GB,Gfk Consumer Confidence OCT,-17,-13,-16,-14
+Thursday,10/21/21,18:30,JP,Inflation Rate YoY SEP,0.002,-0.40%,,-0.003
+Friday,10/22/21,1:00,GB,Retail Sales MoM SEP,-0.002,-0.60%,0.005,0.005
+Friday,10/22/21,3:00,EA,Markit Composite PMI Flash OCT,54.3,56.2,55.2,55.4
+Friday,10/22/21,3:30,GB,Markit/CIPS Composite PMI Flash OCT,56.8,54.9,54,54.2
+Wednesday,10/27/21,6:30,GB,Autumn Budget,,,,
+Wednesday,10/27/21,7:30,US,Durable Goods Orders MoM SEP,-0.004,1.30%,-0.011,-0.008
+Friday,10/29/21,0:00,JP,Consumer Confidence OCT,39.2,37.8,,39
+Friday,10/29/21,4:00,EA,Inflation Rate YoY Flash OCT,0.041,3.40%,0.037,0.036
+Friday,10/29/21,7:30,US,Personal Income MoM SEP,-0.01,0.20%,-0.002,0.002
+Friday,10/29/21,7:30,US,Personal Spending MoM SEP,0.006,1%,0.005,0.006
+Saturday,10/30/21,20:00,CN,NBS Manufacturing PMI OCT,49.2,49.6,49.7,50
+Sunday,10/31/21,20:45,CN,Caixin Manufacturing PMI OCT,50.6,50,50,50
+Monday,11/01/21,9:00,US,ISM Manufacturing PMI OCT,60.8,61.1,60.5,60.3
+Wednesday,11/03/21,13:30,US,Fed Press Conference,,,,
+Thursday,11/04/21,7:30,CA,Balance of Trade SEP,1.86B,1.51B,1.55B, 2.1B
+Thursday,11/04/21,7:30,US,Balance of Trade SEP,-80.9B,-72.8B,-80.5B, -75B
+Friday,11/05/21,7:30,US,Non Farm Payrolls OCT,531K,312K,450K,400K
+Friday,11/05/21,9:00,CA,Ivey PMI s.a OCT,59.3,70.4,,65
+Saturday,11/06/21,22:00,CN,Exports YoY OCT,0.271,28.10%,0.245,0.25
+Saturday,11/06/21,22:00,CN,Imports YoY OCT,0.206,17.60%,0.25,0.26
+Tuesday,11/09/21,8:30,US,PPI MoM OCT,0.006,0.50%,0.006,0.006
+Tuesday,11/09/21,20:30,CN,Inflation Rate YoY OCT,0.015,0.70%,0.014,0.012
+Wednesday,11/10/21,8:30,US,Core Inflation Rate YoY OCT,0.046,4%,0.043,0.041
+Wednesday,11/10/21,8:30,US,Inflation Rate YoY OCT,0.062,5.40%,0.058,0.057
+Thursday,11/11/21,2:00,GB,Balance of Trade SEP,-2.8B,-1.9B,,-3.4B
+Thursday,11/11/21,5:00,EA,ECB Macroeconomic Projections,,,,
+Friday,11/12/21,10:00,US,JOLTs Job Openings SEP,10.438M,10.629M,10.3M,10.1M
+Friday,11/12/21,10:00,US,Michigan Consumer Sentiment Prel NOV,66.8,71.7,72.4,71
+Sunday,11/14/21,21:00,CN,Industrial Production YoY OCT,0.035,3.10%,0.03,0.029
+Sunday,11/14/21,21:00,CN,Retail Sales YoY OCT,0.049,4.40%,0.035,0.036
+Sunday,11/14/21,,US,President Biden and President Xi Jinping Virtual Meeting,,,,
+Tuesday,11/16/21,2:00,GB,Claimant Count Change OCT,-14.9K,-51.1K,,-30K
+Tuesday,11/16/21,8:30,US,Retail Sales MoM OCT,0.017,0.80%,0.014,0.012
+Tuesday,11/16/21,18:50,JP,Balance of Trade OCT,-67.4B,-624.1B,-310B,-460B
+Wednesday,11/17/21,2:00,GB,Inflation Rate YoY OCT,0.042,3.10%,0.039,0.037
+Wednesday,11/17/21,8:30,CA,Inflation Rate YoY OCT,0.047,4.40%,0.047,0.049
+Wednesday,11/17/21,8:30,US,Building Permits OCT,1.65M,1.586M,1.638M,1.661M
+Thursday,11/18/21,18:30,JP,Inflation Rate YoY OCT,0.001,0.20%,,0.001
+Thursday,11/18/21,19:01,GB,GfK Consumer Confidence NOV,-14,-17,-18,-16
+Friday,11/19/21,2:00,GB,Retail Sales MoM OCT,0.008,0%,0.005,0.007
+Sunday,11/21/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385
+Tuesday,11/23/21,4:00,EA,Markit Composite PMI Flash NOV,55.8,54.2,53.2,53.7
+Tuesday,11/23/21,4:30,GB,Markit/CIPS Composite PMI Flash NOV,57.7,57.8,57.5,57.3
+Tuesday,11/23/21,9:45,US,Markit Manufacturing PMI Flash NOV,59.1,58.4,59,58.8
+Tuesday,11/23/21,9:45,US,Markit Services PMI Flash NOV,57,58.7,59,59
+Wednesday,11/24/21,8:30,US,Durable Goods Orders MoM OCT,-0.005,-0.40%,0.002,0.003
+Wednesday,11/24/21,10:00,US,Personal Income MoM OCT,0.005,-1%,0.002,0.001
+Wednesday,11/24/21,10:00,US,Personal Spending MoM OCT,0.013,0.60%,0.01,0.007
+Wednesday,11/24/21,14:00,US,FOMC Minutes,,,,
+Monday,11/29/21,15:05,US,Fed Chair Powell Speech ,,,,
+Monday,11/29/21,20:00,CN,NBS Manufacturing PMI NOV,50.1,49.2,49.6,49.8
+Tuesday,11/30/21,5:00,EA,Inflation Rate YoY Flash NOV,0.049,4.10%,0.045,0.045
+Tuesday,11/30/21,10:00,US,Fed Chair Powell Testimony,,,,
+Tuesday,11/30/21,20:45,CN,Caixin Manufacturing PMI NOV,49.9,50.6,50.5,50.2
+Wednesday,12/01/21,10:00,US,ISM Manufacturing PMI NOV,61.1,60.8,61,61.2
+Thursday,12/02/21,0:00,JP,Consumer Confidence NOV,39.2,39.2,,40
+Friday,12/03/21,8:30,US,Non Farm Payrolls NOV,210K,546K,550K,550K
+Friday,12/03/21,10:00,US,ISM Non-Manufacturing PMI NOV,69.1,66.7,65,65
+Monday,12/06/21,22:00,CN,Exports YoY NOV,0.22,27.10%,0.19,0.16
+Monday,12/06/21,22:00,CN,Imports YoY NOV,0.317,20.60%,0.198,0.21
+Tuesday,12/07/21,8:30,CA,Balance of Trade OCT,2.1B,1.4B,2B,3B
+Tuesday,12/07/21,8:30,US,Balance of Trade OCT,-67.1B,-81.4B,-66.8B,-66B
+Tuesday,12/07/21,10:00,CA,Ivey PMI s.a NOV,61.2,59.3,,58.7
+Wednesday,12/08/21,10:00,US,JOLTs Job Openings OCT,11M,10.602M,10.369M,10.4M
+Wednesday,12/08/21,20:30,CN,Inflation Rate YoY NOV,0.023,1.50%,0.025,0.026
+Friday,12/10/21,2:00,GB,Balance of Trade OCT,-2.027B,-2.8B,,-3.2B
+Friday,12/10/21,2:00,GB,GDP MoM OCT,0.001,0.60%,0.004,0.004
+Friday,12/10/21,2:00,GB,GDP YoY OCT,0.046,5.30%,0.049,0.051
+Friday,12/10/21,8:30,US,Core Inflation Rate YoY NOV,0.049,4.60%,0.049,0.049
+Friday,12/10/21,8:30,US,Inflation Rate YoY NOV,0.068,6.20%,0.068,0.069
+Friday,12/10/21,10:00,US,Michigan Consumer Sentiment Prel DEC,70.4,67.4,67.1,67
+Sunday,12/12/21,18:50,JP,Tankan Large Manufacturers Index Q4,18,18,19,20
+Tuesday,12/14/21,2:00,GB,Claimant Count Change NOV,-49.8K,-14.9K,,-20K
+Tuesday,12/14/21,21:00,CN,Industrial Production YoY NOV,0.038,3.50%,0.036,0.034
+Tuesday,12/14/21,21:00,CN,Retail Sales YoY NOV,0.039,4.90%,0.046,0.048
+Wednesday,12/15/21,2:00,GB,Inflation Rate YoY NOV,0.051,4.20%,0.047,0.05
+Wednesday,12/15/21,8:30,CA,Inflation Rate YoY NOV,0.047,4.70%,0.047,0.049
+Wednesday,12/15/21,8:30,US,Retail Sales MoM NOV,0.003,1.80%,0.008,0.01
+Wednesday,12/15/21,14:30,US,Fed Press Conference,,,,
+Wednesday,12/15/21,18:50,JP,Balance of Trade NOV,-954.8B,-68.5B,-675B,-700B
+Thursday,12/16/21,4:00,EA,Markit Composite PMI Flash DEC,53.4,55.4,54,54.2
+Thursday,12/16/21,4:30,GB,Markit/CIPS Composite PMI Flash DEC,53.2,57.6,56.4,56.5
+Thursday,12/16/21,7:00,GB,BoE Quantitative Easing,875B,875B,875B,875B
+Thursday,12/16/21,8:30,US,Building Permits NOV,1.712M,1.653M,1.663M,1.63M
+Thursday,12/16/21,9:45,US,Markit Manufacturing PMI Flash DEC,57.8,58.3,58.5,58.5
+Thursday,12/16/21,9:45,US,Markit Services PMI Flash DEC,57.5,58,58.5,58.2
+Thursday,12/16/21,19:01,GB,GfK Consumer Confidence DEC,-15,-14,,-16
+Friday,12/17/21,2:00,GB,Retail Sales MoM NOV,0.014,1.10%,0.008,0.01
+Sunday,12/19/21,20:30,CN,Loan Prime Rate 1Y,0.038,3.85%,,0.0385
+Thursday,12/23/21,8:30,US,Durable Goods Orders MoM NOV,0.025,0.10%,0.016,0.011
+Thursday,12/23/21,8:30,US,Personal Income MoM NOV,0.004,0.50%,0.004,0.003
+Thursday,12/23/21,8:30,US,Personal Spending MoM NOV,0.006,1.40%,0.006,0.005
+Thursday,12/23/21,18:30,JP,Inflation Rate YoY NOV,0.006,0.10%,,0.004
+Thursday,12/30/21,20:00,CN,NBS Manufacturing PMI DEC,50.3,50.1,50,50.5
+Monday,01/03/22,20:45,CN,Caixin Manufacturing PMI DEC,50.9,49.9,50,50.1
+Tuesday,01/04/22,10:00,US,ISM Manufacturing PMI DEC,58.7,61.1,60,60.2
+Tuesday,01/04/22,10:00,US,JOLTs Job Openings NOV,10.562M,11.033M,11.075M,10.8M
+Wednesday,01/05/22,0:00,JP,Consumer Confidence DEC,39.1,39.2,,39.8
+Wednesday,01/05/22,14:00,US,FOMC Minutes,,,,
+Thursday,01/06/22,8:30,CA,Balance of Trade NOV,3.13B,2.26B,2.03B,1.8B
+Thursday,01/06/22,8:30,US,Balance of Trade NOV,-80.2B,-67.2B,-77.1B,-81.8B
+Thursday,01/06/22,10:00,US,ISM Non-Manufacturing PMI DEC,62,69.1,66.9,67.5
+Friday,01/07/22,5:00,EA,Inflation Rate YoY Flash DEC,0.05,4.90%,0.047,0.051
+Friday,01/07/22,8:30,US,Non Farm Payrolls DEC,199K,249K,400K,425K
+Friday,01/07/22,10:00,CA,Ivey PMI s.a DEC,45,61.2,,61
+Tuesday,01/11/22,10:00,US,Fed Chair Powell Testimony,,,,
+Tuesday,01/11/22,20:30,CN,Inflation Rate YoY DEC,0.015,2.30%,0.018,0.02
+Wednesday,01/12/22,8:30,US,Core Inflation Rate YoY DEC,0.055,4.90%,0.054,0.054
+Wednesday,01/12/22,8:30,US,Inflation Rate YoY DEC,0.07,6.80%,0.07,0.071
+Thursday,01/13/22,22:00,CN,Exports YoY DEC,0.209,22%,0.2,0.21
+Thursday,01/13/22,22:00,CN,Imports YoY DEC,0.195,31.70%,0.263,0.27
+Friday,01/14/22,2:00,GB,Balance of Trade NOV,0.626B,0.151B,,-2.7B
+Friday,01/14/22,2:00,GB,GDP MoM NOV,0.009,0.20%,0.004,0.003
+Friday,01/14/22,8:30,US,Retail Sales MoM DEC,-0.019,0.20%,0,0.003
+Friday,01/14/22,10:00,US,Michigan Consumer Sentiment Prel JAN,68.8,70.6,70,70.4
+Sunday,01/16/22,21:00,CN,Industrial Production YoY DEC,0.043,3.80%,0.036,0.037
+Sunday,01/16/22,21:00,CN,Retail Sales YoY DEC,0.017,3.90%,0.037,0.037
+Tuesday,01/18/22,2:00,GB,Claimant Count Change DEC,-43.3K,-95.1K,,-36K
+Wednesday,01/19/22,2:00,GB,Inflation Rate YoY DEC,0.054,5.10%,0.052,0.052
+Wednesday,01/19/22,8:30,CA,Inflation Rate YoY DEC,0.048,4.70%,0.048,0.048
+Wednesday,01/19/22,8:30,US,Building Permits DEC,1.873M,1.717M,1.701M,1.72M
+Wednesday,01/19/22,18:50,JP,Balance of Trade DEC,-582.4B,-955.6B,-784.1B, -700B
+Wednesday,01/19/22,20:15,CN,Loan Prime Rate 1Y,0.037,3.80%,,0.038
+Thursday,01/20/22,18:30,JP,Inflation Rate YoY DEC,0.008,0.60%,,0.007
+Thursday,01/20/22,19:01,GB,Gfk Consumer Confidence JAN,-19,-15,-15,-18
+Friday,01/21/22,2:00,GB,Retail Sales MoM DEC,-0.037,1%,-0.006,-0.006
+Sunday,01/23/22,19:30,JP,Jibun Bank Composite PMI Flash JAN,48.8,52.5,,52.1
+Monday,01/24/22,4:00,EA,Markit Composite PMI Flash JAN,52.4,53.3,52.6,52.6
+Monday,01/24/22,4:30,GB,Markit/CIPS Composite PMI Flash JAN,53.4,53.6,55,54
+Monday,01/24/22,9:45,US,Markit Composite PMI Flash JAN,50.8,57,,56.7
+Wednesday,01/26/22,10:00,CA,BoC Monetary Policy Report,,,,
+Wednesday,01/26/22,14:30,US,Fed Press Conference,,,,
+Thursday,01/27/22,8:30,US,Durable Goods Orders MoM DEC,-0.009,3.20%,-0.005,-0.002
+Friday,01/28/22,8:30,US,Personal Income MoM DEC,0.003,0.50%,0.005,0.005
+Friday,01/28/22,8:30,US,Personal Spending MoM DEC,-0.006,0.40%,-0.006,-0.003
+Saturday,01/29/22,20:45,CN,Caixin Manufacturing PMI JAN,49.1,50.9,50.4,50.6
+Saturday,01/29/22,20:45,CN,NBS Manufacturing PMI JAN,50.1,50.3,50,50.1
+Monday,01/31/22,0:00,JP,Consumer Confidence JAN,36.7,39.1,,39.5
+Tuesday,02/01/22,10:00,US,ISM Manufacturing PMI JAN,57.6,58.8,57.5,58
+Tuesday,02/01/22,10:00,US,JOLTs Job Openings DEC,10.925M,10.775M,10.3M,10.52M
+Wednesday,02/02/22,5:00,EA,Inflation Rate YoY Flash JAN,0.051,5%,0.044,0.045
+Thursday,02/03/22,10:00,US,ISM Non-Manufacturing PMI JAN,59.9,62.3,59.5,61
+Friday,02/04/22,8:30,US,Non Farm Payrolls JAN,467K,510K,150K,30K
+Friday,02/04/22,10:00,CA,Ivey PMI s.a JAN,50.7,45,,50
+Tuesday,02/08/22,8:30,CA,Balance of Trade DEC,-0.14B,2.47B,2.5B, 1.5B
+Tuesday,02/08/22,8:30,US,Balance of Trade DEC,-80.7B,-79.3B,-83B,-83.2B
+Thursday,02/10/22,8:30,US,Core Inflation Rate YoY JAN,0.06,5.50%,0.059,0.057
+Thursday,02/10/22,8:30,US,Inflation Rate YoY JAN,0.075,7%,0.073,0.071
+Friday,02/11/22,2:00,GB,Balance of Trade DEC,-2.34B,-2.59B,, -3.1B
+Friday,02/11/22,2:00,GB,GDP MoM DEC,-0.002,0.70%,-0.006,-0.002
+Friday,02/11/22,2:00,GB,GDP YoY DEC,0.06,7.50%,0.063,0.067
+Friday,02/11/22,10:00,US,Michigan Consumer Sentiment Prel FEB,61.7,67.2,67.5,67.5
+Tuesday,02/15/22,2:00,GB,Claimant Count Change JAN,-31.9K,-43.3K,-28K,-27K
+Tuesday,02/15/22,20:30,CN,Inflation Rate YoY JAN,0.009,1.50%,0.01,0.014
+Wednesday,02/16/22,2:00,GB,Inflation Rate YoY JAN,0.055,5.40%,0.054,0.055
+Wednesday,02/16/22,8:30,CA,Inflation Rate YoY JAN,0.051,4.80%,0.048,0.05
+Wednesday,02/16/22,8:30,US,Retail Sales MoM JAN,0.038,-2.50%,0.02,0.015
+Wednesday,02/16/22,14:00,US,FOMC Minutes,,,,
+Wednesday,02/16/22,18:50,JP,Balance of Trade JAN,-2191.1B,-583.3B,-1607B,-1800B
+Thursday,02/17/22,8:30,US,Building Permits JAN,1.899M,1.885M,1.76M,1.79M
+Thursday,02/17/22,18:30,JP,Inflation Rate YoY JAN,0.005,0.80%,,0.009
+Friday,02/18/22,2:00,GB,Retail Sales MoM JAN,0.019,-4%,0.01,0.009
+Sunday,02/20/22,20:15,CN,Loan Prime Rate 1Y,0.037,3.70%,0.037,0.037
+Monday,02/21/22,4:30,GB,Markit/CIPS Manufacturing PMI Flash FEB,57.3,57.3,57.2,57.6
+Monday,02/21/22,4:30,GB,Markit/CIPS UK Services PMI Flash FEB,60.8,54.1,55.5,55
+Thursday,02/24/22,19:01,GB,Gfk Consumer Confidence FEB,-26,-19,-18,-16
+Friday,02/25/22,8:30,US,Durable Goods Orders MoM JAN,0.016,1.20%,0.008,0.004
+Friday,02/25/22,8:30,US,Personal Income MoM JAN,0,0.40%,-0.003,0.001
+Friday,02/25/22,8:30,US,Personal Spending MoM JAN,0.021,-0.80%,0.015,0.007
+Monday,02/28/22,20:30,CN,NBS Manufacturing PMI FEB,50.2,50.1,49.9,50.4
+Monday,02/28/22,20:45,CN,Caixin Manufacturing PMI FEB,50.4,49.1,49.3,49.3
+Tuesday,03/01/22,10:00,US,ISM Manufacturing PMI FEB,58.6,57.6,58,58.1
+Wednesday,03/02/22,5:00,EA,Inflation Rate YoY Flash FEB,0.058,5.10%,0.054,0.052
+Thursday,03/03/22,0:00,JP,Consumer Confidence FEB,35.3,36.7,,36
+Thursday,03/03/22,10:00,US,Fed Chair Powell Testimony,,,,
+Thursday,03/03/22,10:00,US,ISM Non-Manufacturing PMI FEB,56.5,59.9,61,61
+Friday,03/04/22,8:30,US,Non Farm Payrolls FEB,678K,481K,400K,350K
+Friday,03/04/22,10:00,CA,Ivey PMI s.a FEB,60.6,50.7,,52
+Sunday,03/06/22,22:00,CN,Balance of Trade JAN-FEB,115.95B,94.46B,99.5B,120B
+Tuesday,03/08/22,8:30,CA,Balance of Trade JAN,2.62B,-1.58B,1.6B,1.3B
+Tuesday,03/08/22,8:30,US,Balance of Trade JAN,-89.7B,-82B,-87.1B,-84B
+Tuesday,03/08/22,20:30,CN,Inflation Rate YoY FEB,0.009,0.90%,0.009,0.009
+Wednesday,03/09/22,10:00,US,JOLTs Job Openings JAN,11.263M,11.448M,10.925M,10.8M
+Thursday,03/10/22,8:30,US,Core Inflation Rate YoY FEB,0.064,6%,0.064,0.064
+Thursday,03/10/22,8:30,US,Inflation Rate YoY FEB,0.079,7.50%,0.079,0.079
+Friday,03/11/22,2:00,GB,GDP MoM JAN,0.008,-0.20%,0.002,0.003
+Friday,03/11/22,10:00,US,Michigan Consumer Sentiment Prel MAR,59.7,62.8,61.4,62
+Monday,03/14/22,21:00,CN,Industrial Production YoY JAN-FEB,0.075,4.30%,0.039,0.038
+Tuesday,03/15/22,2:00,GB,Claimant Count Change FEB,-48.1K,-67.3K,,-25K
+Tuesday,03/15/22,7:30,US,PPI MoM FEB,0.008,1.20%,0.009,0.011
+Tuesday,03/15/22,18:50,JP,Balance of Trade FEB,-668.3B,-2193.5B,-112.6B,-150B
+Wednesday,03/16/22,7:30,CA,Inflation Rate YoY FEB,0.057,5.10%,0.055,0.054
+Wednesday,03/16/22,7:30,US,Retail Sales MoM FEB,0.003,4.90%,0.004,0.007
+Wednesday,03/16/22,13:30,US,Fed Press Conference,,,,
+Thursday,03/17/22,7:30,US,Building Permits FEB,1.859M,1.895M,1.85M,1.86M
+Thursday,03/17/22,18:30,JP,Inflation Rate YoY FEB,0.009,0.50%,,0.007
+Wednesday,03/23/22,2:00,GB,Inflation Rate YoY FEB,0.062,5.50%,0.059,0.061
+Thursday,03/24/22,4:30,GB,Markit/CIPS Manufacturing PMI Flash MAR,55.5,58,56.7,57.1
+Thursday,03/24/22,4:30,GB,Markit/CIPS UK Services PMI Flash MAR,61,60.5,58,58.8
+Thursday,03/24/22,7:30,US,Durable Goods Orders MoM FEB,-0.022,1.60%,-0.005,-0.005
+Thursday,03/24/22,19:01,GB,Gfk Consumer Confidence MAR,-31,-26,-30,-35
+Friday,03/25/22,2:00,GB,Retail Sales MoM FEB,-0.003,1.90%,0.006,0.007
+Tuesday,03/29/22,9:00,US,JOLTs Job Openings FEB,11.266M,11.283M,11M,11.1M
+Wednesday,03/30/22,20:30,CN,NBS Manufacturing PMI MAR,49.5,50.2,49.9,49.1
+Thursday,03/31/22,7:30,US,Personal Income MoM FEB,0.005,0.10%,0.005,0.006
+Thursday,03/31/22,7:30,US,Personal Spending MoM FEB,0.002,2.70%,0.005,0.004
+Thursday,03/31/22,18:50,JP,Tankan Large Manufacturers Index Q1,14,18,12,13
+Thursday,03/31/22,20:45,CN,Caixin Manufacturing PMI MAR,48.1,50.4,50,49.1
+Friday,04/01/22,4:00,EA,Inflation Rate YoY Flash MAR,0.075,5.90%,0.066,0.069
+Friday,04/01/22,7:30,US,Non Farm Payrolls MAR,431K,750K,490K,460K
+Friday,04/01/22,9:00,US,ISM Manufacturing PMI MAR,57.1,58.6,59,58.5
+Tuesday,04/05/22,7:30,CA,Balance of Trade FEB,2.66B,3.12B,2.9B,2.4B
+Tuesday,04/05/22,7:30,US,Balance of Trade FEB,-89.2B,-89.2B,-88.5B,-88B
+Tuesday,04/05/22,9:00,US,ISM Non-Manufacturing PMI MAR,58.3,56.5,58.4,58.1
+Wednesday,04/06/22,9:00,CA,Ivey PMI s.a MAR,74.2,60.6,60,61
+Wednesday,04/06/22,13:00,US,FOMC Minutes,,,,
+Friday,04/08/22,0:00,JP,Consumer Confidence MAR,32.8,35.3,,34
+Sunday,04/10/22,20:30,CN,Inflation Rate YoY MAR,0.015,0.90%,0.012,0.012
+Monday,04/11/22,1:00,GB,GDP MoM FEB,0.001,0.80%,0.003,0.005
+Tuesday,04/12/22,1:00,GB,Claimant Count Change MAR,-46.9K,-58K,,-31K
+Tuesday,04/12/22,7:30,US,Core Inflation Rate YoY MAR,0.065,6.40%,0.066,0.067
+Tuesday,04/12/22,7:30,US,Inflation Rate YoY MAR,0.085,7.90%,0.084,0.083
+Tuesday,04/12/22,23:30,CN,Balance of Trade MAR,47.38B,115.95B,22.4B,25B
+Wednesday,04/13/22,1:00,GB,Inflation Rate YoY MAR,0.07,6.20%,0.067,0.07
+Wednesday,04/13/22,7:30,US,PPI MoM MAR,0.014,0.90%,0.011,0.01
+Wednesday,04/13/22,9:00,CA,BoC Monetary Policy Report,,,,
+Thursday,04/14/22,7:30,US,Retail Sales MoM MAR,0.005,0.80%,0.006,0.004
+Thursday,04/14/22,9:00,US,Michigan Consumer Sentiment Prel APR,65.7,59.4,59,58.8
+Sunday,04/17/22,21:00,CN,Industrial Production YoY MAR,0.05,7.50%,0.045,0.042
+Tuesday,04/19/22,7:30,US,Building Permits MAR,1.873M,1.865M,1.825M,1.81M
+Tuesday,04/19/22,18:50,JP,Balance of Trade MAR,-412.4B,-669.7B,-100.8B, -100B
+Wednesday,04/20/22,7:30,CA,Inflation Rate YoY MAR,0.067,5.70%,0.061,0.06
+Thursday,04/21/22,18:30,JP,Inflation Rate YoY MAR,0.012,0.90%,,0.011
+Thursday,04/21/22,21:10,GB,Gfk Consumer Confidence APR,-38,-31,-33,-33
+Friday,04/22/22,1:00,GB,Retail Sales MoM MAR,-0.014,-0.50%,-0.003,-0.001
+Friday,04/22/22,3:30,GB,S&P Global/CIPS Manufacturing PMI Flash APR,55.3,55.2,54,54.8
+Friday,04/22/22,3:30,GB,S&P Global/CIPS UK Services PMI Flash APR,58.3,62.6,60,58.9
+Tuesday,04/26/22,7:30,US,Durable Goods Orders MoM MAR,0.008,-1.70%,0.01,0.011
+Friday,04/29/22,4:00,EA,Inflation Rate YoY Flash APR,0.075,7.40%,0.075,0.074
+Friday,04/29/22,7:30,US,Personal Income MoM MAR,0.005,0.70%,0.004,0.004
+Friday,04/29/22,7:30,US,Personal Spending MoM MAR,0.011,0.60%,0.007,0.005
+Friday,04/29/22,20:30,CN,NBS Manufacturing PMI APR,47.4,49.5,48,49.1
+Friday,04/29/22,20:45,CN,Caixin Manufacturing PMI APR,46,48.1,47,47.9
+Friday,04/29/22,0:00,JP,Consumer Confidence APR,33,32.8,,31.7
+Friday,04/29/22,9:00,US,ISM Manufacturing PMI APR,55.4,57.1,57.6,57.5
+Tuesday,05/03/22,9:00,US,JOLTs Job Openings MAR,11.549M,11.344M,11M,11.27M
+Wednesday,05/04/22,7:30,CA,Balance of Trade MAR,2.49B,3.08B,3.9B,2.3B
+Wednesday,05/04/22,7:30,US,Balance of Trade MAR,-109.8B,-89.8B,-107B, -92B
+Wednesday,05/04/22,9:00,US,ISM Non-Manufacturing PMI APR,57.1,58.3,58.5,58.5
+Wednesday,05/04/22,13:30,US,Fed Press Conference,,,,
+Wednesday,05/04/22,7:30,US,Non Farm Payrolls APR,428K,428K,391K,415K
+Wednesday,05/04/22,9:00,CA,Ivey PMI s.a APR,66.3,74.2,,73.8
+Wednesday,05/04/22,23:00,CN,Balance of Trade APR,51.12B,47.38B,50.65B,53B
+Tuesday,05/10/22,20:30,CN,Inflation Rate YoY APR,0.021,1.50%,0.018,0.018
+Wednesday,05/11/22,7:30,US,Core Inflation Rate YoY APR,0.062,6.50%,0.06,0.062
+Wednesday,05/11/22,7:30,US,Inflation Rate YoY APR,0.083,8.50%,0.081,0.082
+Thursday,05/12/22,1:00,GB,GDP MoM MAR,-0.001,0%,0,0.001
+Thursday,05/12/22,7:30,US,PPI MoM APR,0.005,1.60%,0.005,0.005
+Thursday,05/12/22,9:00,US,Michigan Consumer Sentiment Prel 05,59.1,65.2,64,63.5
+Thursday,05/12/22,21:00,CN,Industrial Production YoY APR,-0.029,5%,0.004,0.004
+Thursday,05/12/22,,EA,European Commission Spring Forecasts,,,,
+Tuesday,05/17/22,1:00,GB,Claimant Count Change APR,-56.9K,-81.6K,-42.5K,-42K
+Tuesday,05/17/22,7:30,US,Retail Sales MoM APR,0.009,1.40%,0.009,0.006
+Tuesday,05/17/22,13:00,US,Fed Chair Powell Speech ,,,,
+Wednesday,05/18/22,1:00,GB,Inflation Rate YoY APR,0.09,7%,0.091,0.089
+Wednesday,05/18/22,7:30,CA,Inflation Rate YoY APR,0.068,6.70%,0.067,0.066
+Wednesday,05/18/22,7:30,US,Building Permits APR,1.819M,1.879M,1.812M,1.82M
+Wednesday,05/18/22,18:50,JP,Balance of Trade APR,-839.2B,-414.1B,-1150B,-1000B
+Thursday,05/19/22,18:01,GB,Gfk Consumer Confidence 05,-40,-38,-39,-40
+Thursday,05/19/22,18:30,JP,Inflation Rate YoY APR,0.025,1.20%,,0.015
+Thursday,05/19/22,1:00,GB,Retail Sales MoM APR,0.014,-1.20%,-0.002,-0.002
+Tuesday,05/24/22,3:30,GB,S&P Global/CIPS Manufacturing PMI Flash 05,54.6,55.8,55,55.2
+Tuesday,05/24/22,3:30,GB,S&P Global/CIPS UK Services PMI Flash 05,51.8,58.9,57,58.5
+Wednesday,05/25/22,7:30,US,Durable Goods Orders MoM APR,0.004,0.60%,0.006,0.004
+Wednesday,05/25/22,13:00,US,FOMC Minutes,,,,
+Wednesday,05/25/22,7:30,US,Personal Income MoM APR,0.004,0.50%,0.005,0.006
+Wednesday,05/25/22,7:30,US,Personal Spending MoM APR,0.009,1.40%,0.007,0.008
+Wednesday,05/25/22,20:30,CN,NBS Manufacturing PMI 05,49.6,47.4,,48.9
+Tuesday,05/31/22,0:00,JP,Consumer Confidence 05,34.1,33,,33.5
+Tuesday,05/31/22,4:00,EA,Inflation Rate YoY Flash 05,0.081,7.40%,0.077,0.076
+Tuesday,05/31/22,20:45,CN,Caixin Manufacturing PMI 05,48.1,46,48,48
+Wednesday,06/01/22,9:00,US,ISM Manufacturing PMI 05,56.1,55.4,54.5,54.8
+Wednesday,06/01/22,9:00,US,JOLTs Job Openings APR,11.4M,11.855M,11.4M,11.4M
+Friday,06/03/22,7:30,US,Non Farm Payrolls 05,390K,436K,325K,320K
+Friday,06/03/22,9:00,US,ISM Non-Manufacturing PMI 05,55.9,57.1,56.4,55
+Tuesday,06/07/22,7:30,CA,Balance of Trade APR,1.5B,2.28B,2.9B,2.8B
+Tuesday,06/07/22,7:30,US,Balance of Trade APR,-87.1B,-107.7B,-89.5B,-91B
+Tuesday,06/07/22,9:00,CA,Ivey PMI s.a 05,72,66.3,,64
+Wednesday,06/08/22,22:00,CN,Balance of Trade 05,78.76B,51.12B,58B,50B
+Thursday,06/09/22,20:30,CN,Inflation Rate YoY 05,0.021,2.10%,0.022,0.02
+Friday,06/10/22,7:30,US,Core Inflation Rate YoY 05,0.06,6.20%,0.059,0.06
+Friday,06/10/22,7:30,US,Inflation Rate YoY 05,0.086,8.30%,0.083,0.083
+Friday,06/10/22,9:00,US,Michigan Consumer Sentiment Prel JUN,50.2,58.4,58,59
+Monday,06/13/22,1:00,GB,GDP MoM APR,-0.003,-0.10%,0.001,0
+Tuesday,06/14/22,1:00,GB,Claimant Count Change 05,-19.7K,-65.5K,-49.4K,-29K
+Tuesday,06/14/22,7:30,US,PPI MoM 05,0.008,0.40%,0.008,0.007
+Tuesday,06/14/22,21:00,CN,Industrial Production YoY 05,0.007,-2.90%,-0.007,-0.008
+Tuesday,06/14/22,,EA,ECB Unscheduled Meeting to Discuss Markets,,,,
+Wednesday,06/15/22,7:30,US,Retail Sales MoM 05,-0.003,0.70%,0.002,0.003
+Wednesday,06/15/22,13:30,US,Fed Press Conference,,,,
+Wednesday,06/15/22,18:50,JP,Balance of Trade 05,-2384.7B,-842.8B,-2022.6B,-1750B
+Thursday,06/16/22,7:30,US,Building Permits 05,1.695M,1.823M,1.785M,1.79M
+Wednesday,06/22/22,1:00,GB,Inflation Rate YoY 05,0.091,9%,0.091,0.092
+Wednesday,06/22/22,7:30,CA,Inflation Rate YoY 05,0.077,6.80%,0.074,0.07
+Wednesday,06/22/22,8:30,US,Fed Chair Powell Testimony,,,,
+Thursday,06/23/22,3:30,GB,S&P Global/CIPS Manufacturing PMI Flash JUN,53.4,54.6,53.7,54.2
+Thursday,06/23/22,9:00,US,Fed Chair Powell Testimony,,,,
+Thursday,06/23/22,18:01,GB,Gfk Consumer Confidence JUN,-41,-40,-40,-42
+Thursday,06/23/22,18:30,JP,Inflation Rate YoY 05,0.025,2.50%,,0.023
+Friday,06/24/22,1:00,GB,Retail Sales MoM 05,-0.005,0.40%,-0.007,-0.003
+Sunday,06/26/22,,EA,ECB Forum on Central Banking,,,,
+Monday,06/27/22,7:30,US,Durable Goods Orders MoM 05,0.007,0.40%,0.001,-0.003
+Monday,06/27/22,,EA,ECB Forum on Central Banking,,,,
+Tuesday,06/28/22,,EA,ECB Forum on Central Banking,,,,
+Wednesday,06/29/22,0:00,JP,Consumer Confidence JUN,32.1,34.1,,33
+Wednesday,06/29/22,8:00,EA,ECB President Lagarde Speech ,,,,
+Wednesday,06/29/22,8:00,GB,BoE Gov Bailey Speech ,,,,
+Wednesday,06/29/22,8:00,US,Fed Chair Powell Speech ,,,,
+Wednesday,06/29/22,20:30,CN,NBS Manufacturing PMI JUN,50.2,49.6,50.5,48.3
+Thursday,06/30/22,7:30,US,Personal Income MoM 05,0.005,0.50%,0.005,0.003
+Thursday,06/30/22,7:30,US,Personal Spending MoM 05,0.002,0.60%,0.004,0.008
+Thursday,06/30/22,8:30,EA,ECB President Lagarde Speech ,,,,
+Thursday,06/30/22,18:50,JP,Tankan Large Manufacturers Index Q2,9,14,13,10
+Thursday,06/30/22,20:45,CN,Caixin Manufacturing PMI JUN,51.7,48.1,50.1,50.5
+Friday,07/01/22,4:00,EA,Inflation Rate YoY Flash JUN,0.086,8.10%,0.084,0.083
+Friday,07/01/22,9:00,US,ISM Manufacturing PMI JUN,53,56.1,54.9,55
+Tuesday,07/05/22,3:30,GB,S&P Global/CIPS UK Services PMI Final JUN,54.3,53.4,53.4,53.4
+Wednesday,07/06/22,9:00,US,ISM Non-Manufacturing PMI JUN,55.3,55.9,54.3,55.2
+Wednesday,07/06/22,9:00,US,JOLTs Job Openings 05,11.254M,11.681M,11M,11.3M
+Wednesday,07/06/22,13:00,US,FOMC Minutes,,,,
+Thursday,07/07/22,7:30,CA,Balance of Trade 05,5.32B,2.17B,2.4B,1.9B
+Thursday,07/07/22,7:30,US,Balance of Trade 05,-85.5B,-86.7B,-84.9B,-86B
+Thursday,07/07/22,9:00,CA,Ivey PMI s.a JUN,62.2,72,,64
+Friday,07/08/22,7:30,US,Non Farm Payrolls JUN,372K,384K,268K,300K
+Friday,07/08/22,20:30,CN,Inflation Rate YoY JUN,0.025,2.10%,0.024,0.023
+Wednesday,07/13/22,1:00,GB,GDP MoM 05,0.005,-0.20%,0,-0.001
+Wednesday,07/13/22,1:30,CN,Balance of Trade JUN,97.94B,78.76B,75.7B,76B
+Wednesday,07/13/22,7:30,US,Core Inflation Rate YoY JUN,0.059,6%,0.057,0.058
+Wednesday,07/13/22,7:30,US,Inflation Rate YoY JUN,0.091,8.60%,0.088,0.088
+Wednesday,07/13/22,9:00,CA,BoC Monetary Policy Report,,,,
+Thursday,07/14/22,7:30,US,PPI MoM JUN,0.011,0.90%,0.008,0.009
+Thursday,07/14/22,21:00,CN,Industrial Production YoY JUN,0.039,0.70%,0.041,0.031
+Friday,07/15/22,7:30,US,Retail Sales MoM JUN,0.01,-0.10%,0.008,0.005
+Friday,07/15/22,9:00,US,Michigan Consumer Sentiment Prel JUL,51.1,50,49.9,49.3
+Tuesday,07/19/22,1:00,GB,Claimant Count Change JUN,-20.1K,-34.7K,,-25K
+Tuesday,07/19/22,7:30,US,Building Permits JUN,1.685M,1.695M,1.65M,1.68M
+Wednesday,07/20/22,1:00,GB,Inflation Rate YoY JUN,0.094,9.10%,0.093,0.095
+Wednesday,07/20/22,7:30,CA,Inflation Rate YoY JUN,0.081,7.70%,0.084,0.08
+Wednesday,07/20/22,18:50,JP,Balance of Trade JUN,-1383.8B,-2385.8B,-1509.7B,-2500B
+Thursday,07/21/22,18:01,GB,Gfk Consumer Confidence JUL,-41,-41,-42,-44
+Thursday,07/21/22,18:30,JP,Inflation Rate YoY JUN,0.024,2.50%,,0.026
+Friday,07/22/22,1:00,GB,Retail Sales MoM JUN,-0.001,-0.80%,-0.003,-0.002
+Friday,07/22/22,3:30,GB,S&P Global/CIPS Manufacturing PMI Flash JUL,52.2,52.8,52,51.9
+Wednesday,07/27/22,7:30,US,Durable Goods Orders MoM JUN,0.019,0.80%,-0.005,-0.003
+Wednesday,07/27/22,13:30,US,Fed Press Conference,,,,
+Friday,07/29/22,0:00,JP,Consumer Confidence JUL,30.2,32.1,,33
+Friday,07/29/22,4:00,EA,Inflation Rate YoY Flash JUL,0.089,8.60%,0.086,0.09
+Friday,07/29/22,7:30,US,Personal Income MoM JUN,0.006,0.60%,0.005,0.005
+Friday,07/29/22,7:30,US,Personal Spending MoM JUN,0.011,0.30%,0.009,0.006
+Saturday,07/30/22,20:30,CN,NBS Manufacturing PMI JUL,49,50.2,50.4,50.9
+Sunday,07/31/22,20:45,CN,Caixin Manufacturing PMI JUL,50.4,51.7,51.5,52
+Monday,08/01/22,9:00,US,ISM Manufacturing PMI JUL,52.8,53,52,52.2
+Tuesday,08/02/22,9:00,US,JOLTs Job Openings JUN,10.698M,11.303M,11M,11M
+Wednesday,08/03/22,3:30,GB,S&P Global/CIPS UK Services PMI Final JUL,52.6,54.3,53.3,53.3
+Wednesday,08/03/22,9:00,US,ISM Non-Manufacturing PMI JUL,56.7,55.3,53.5,52.5
+Thursday,08/04/22,7:30,CA,Balance of Trade JUN,5.05B,4.77B,4.8B,6B
+Thursday,08/04/22,7:30,US,Balance of Trade JUN,-79.6B,-84.9B,-80.1B, -83B
+Friday,08/05/22,7:30,US,Non Farm Payrolls JUL,528K,398K,250K,290K
+Friday,08/05/22,9:00,CA,Ivey PMI s.a JUL,49.6,62.2,,61
+Saturday,08/06/22,22:00,CN,Balance of Trade JUL,101.26B,97.94B,90B,99B
+Tuesday,08/09/22,20:30,CN,Inflation Rate YoY JUL,0.027,2.50%,0.029,0.025
+Wednesday,08/10/22,7:30,US,Core Inflation Rate YoY JUL,0.059,5.90%,0.061,0.059
+Wednesday,08/10/22,7:30,US,Inflation Rate YoY JUL,0.085,9.10%,0.087,0.091
+Thursday,08/11/22,7:30,US,PPI MoM JUL,-0.005,1%,0.002,0.004
+Friday,08/12/22,1:00,GB,GDP MoM JUN,-0.006,0.40%,-0.013,-0.013
+Friday,08/12/22,9:00,US,Michigan Consumer Sentiment Prel AUG,55.1,51.5,52.5,51.3
+Sunday,08/14/22,21:00,CN,Industrial Production YoY JUL,0.038,3.90%,0.046,0.05
+Tuesday,08/16/22,1:00,GB,Claimant Count Change JUL,-10.5K,-26.8K,,-10K
+Tuesday,08/16/22,7:30,CA,Inflation Rate YoY JUL,0.076,8.10%,0.076,0.076
+Tuesday,08/16/22,7:30,US,Building Permits JUL,1.674M,1.696M,1.65M,1.67M
+Tuesday,08/16/22,18:50,JP,Balance of Trade JUL,-1436.8B,-1398.5B,-1405B,-1300B
+Wednesday,08/17/22,1:00,GB,Inflation Rate YoY JUL,0.101,9.40%,0.098,0.099
+Wednesday,08/17/22,7:30,US,Retail Sales MoM JUL,0,0.80%,0.001,0.002
+Wednesday,08/17/22,13:00,US,FOMC Minutes,,,,
+Thursday,08/18/22,18:01,GB,Gfk Consumer Confidence AUG,-44,-41,-42,-43
+Thursday,08/18/22,18:30,JP,Inflation Rate YoY JUL,0.026,2.40%,,0.022
+Friday,08/19/22,1:00,GB,Retail Sales MoM JUL,0.003,-0.20%,-0.002,-0.001
+Tuesday,08/23/22,3:30,GB,S&P Global/CIPS Manufacturing PMI Flash AUG,46,52.1,51.1,51.3
+Wednesday,08/24/22,7:30,US,Durable Goods Orders MoM JUL,0,2.20%,0.006,0.008
+Friday,08/26/22,7:30,US,Personal Income MoM JUL,0.002,0.70%,0.006,0.005
+Friday,08/26/22,7:30,US,Personal Spending MoM JUL,0.001,1%,0.004,0.002
+Friday,08/26/22,9:00,US,Fed Chair Powell Speech ,,,,
+Tuesday,08/30/22,9:00,US,JOLTs Job Openings JUL,11.239M,11.040M,10.45M,10.5M
+Tuesday,08/30/22,20:30,CN,NBS Manufacturing PMI AUG,49.4,49,49.2,48.5
+Wednesday,08/31/22,0:00,JP,Consumer Confidence AUG,32.5,30.2,,31
+Wednesday,08/31/22,4:00,EA,Inflation Rate YoY Flash AUG,0.091,8.90%,0.09,0.091
+Wednesday,08/31/22,20:45,CN,Caixin Manufacturing PMI AUG,49.5,50.4,50.2,50
+Thursday,09/01/22,9:00,US,ISM Manufacturing PMI AUG,52.8,52.8,52,52
+Friday,09/02/22,7:30,US,Non Farm Payrolls AUG,315K,526K,300K,310K
+Monday,09/05/22,3:30,GB,S&P Global/CIPS UK Services PMI Final AUG,50.9,52.6,52.5,52.5
+Tuesday,09/06/22,9:00,US,ISM Non-Manufacturing PMI AUG,56.9,56.7,55.1,55
+Tuesday,09/06/22,22:00,CN,Balance of Trade AUG,79.39B,101.26B,92.7B,90B
+Wednesday,09/07/22,7:30,CA,Balance of Trade JUL,4.05B,4.88B,3.8B,4.7B
+Wednesday,09/07/22,7:30,US,Balance of Trade JUL,-70.7B,-80.9B,-70.3B,-70B
+Wednesday,09/07/22,9:00,CA,Ivey PMI s.a AUG,60.9,49.6,,48.8
+Thursday,09/08/22,20:30,CN,Inflation Rate YoY AUG,0.025,2.70%,0.028,0.029
+Monday,09/12/22,1:00,GB,GDP MoM JUL,0.002,-0.60%,0.004,0.001
+Tuesday,09/13/22,1:00,GB,Claimant Count Change AUG,6.3K,-10.5K,,-4K
+Tuesday,09/13/22,7:30,US,Core Inflation Rate YoY AUG,0.063,5.90%,0.061,0.059
+Tuesday,09/13/22,7:30,US,Inflation Rate YoY AUG,0.083,8.50%,0.081,0.081
+Wednesday,09/14/22,1:00,GB,Inflation Rate YoY AUG,0.099,10.10%,0.102,0.106
+Wednesday,09/14/22,7:30,US,PPI MoM AUG,-0.001,-0.40%,-0.001,0.001
+Wednesday,09/14/22,18:50,JP,Balance of Trade AUG,-2817.3B,-1436.8B,-2398.2B,
+Thursday,09/15/22,7:30,US,Retail Sales MoM AUG,0.003,-0.40%,0,0.001
+Thursday,09/15/22,21:00,CN,Industrial Production YoY AUG,0.042,3.80%,0.038,0.039
+Friday,09/16/22,1:00,GB,Retail Sales MoM AUG,-0.016,0.40%,-0.005,-0.004
+Friday,09/16/22,9:00,US,Michigan Consumer Sentiment Prel SEP,59.5,58.2,60,58.6
+Monday,09/19/22,18:30,JP,Inflation Rate YoY AUG,0.03,2.60%,,0.026
+Tuesday,09/20/22,7:30,CA,Inflation Rate YoY AUG,0.07,7.60%,0.073,0.075
+Tuesday,09/20/22,7:30,US,Building Permits AUG,1.517M,1.685M,1.61M,1.63M
+Wednesday,09/21/22,13:30,US,Fed Press Conference,,,,
+Thursday,09/22/22,18:01,GB,Gfk Consumer Confidence SEP,-49,-44,-42,-35
+Tuesday,09/27/22,6:00,GB,BoE Pill Speech ,,,,
+Tuesday,09/27/22,7:30,US,Durable Goods Orders MoM AUG,-0.002,-0.10%,-0.004,-0.009
+Thursday,09/29/22,20:30,CN,NBS Manufacturing PMI SEP,50.1,49.4,49.6,49.8
+Thursday,09/29/22,20:45,CN,Caixin Manufacturing PMI SEP,48.1,49.5,49.5,49.8
+Friday,09/30/22,0:00,JP,Consumer Confidence SEP,30.8,32.5,,34
+Friday,09/30/22,4:00,EA,Inflation Rate YoY Flash SEP,0.1,9.10%,0.097,0.097
+Friday,09/30/22,7:30,US,Personal Income MoM AUG,0.003,0.30%,0.003,0.002
+Friday,09/30/22,7:30,US,Personal Spending MoM AUG,0.004,-0.20%,0.002,0.002
+Sunday,10/02/22,18:50,JP,Tankan Large Manufacturers Index Q3,8,9,11,10
+Monday,10/03/22,9:00,US,ISM Manufacturing PMI SEP,50.9,52.8,52.2,52.9
+Tuesday,10/04/22,9:00,US,JOLTs Job Openings AUG,10.053M,11.17M,10.775M,11.1M
+Wednesday,10/05/22,7:30,CA,Balance of Trade AUG,1.52B,2.37B,3.45B,3.9B
+Wednesday,10/05/22,7:30,US,Balance of Trade AUG,-67.4B,-70.5B,-67.7B,-68B
+Wednesday,10/05/22,9:00,US,ISM Non-Manufacturing PMI SEP,56.7,56.9,56,56.4
+Thursday,10/06/22,9:00,CA,Ivey PMI s.a SEP,59.5,60.9,,55
+Friday,10/07/22,7:30,US,Non Farm Payrolls SEP,263K,315K,250K,290K
+Tuesday,10/11/22,1:00,GB,Claimant Count Change SEP,25.5K,6.3K,,10K
+Wednesday,10/12/22,1:00,GB,GDP MoM AUG,-0.003,0.10%,0,0.001
+Wednesday,10/12/22,7:30,US,PPI MoM SEP,0.004,-0.20%,0.002,0
+Wednesday,10/12/22,13:00,US,FOMC Minutes,,,,
+Thursday,10/13/22,7:30,US,Core Inflation Rate YoY SEP,0.066,6.30%,0.065,0.064
+Thursday,10/13/22,7:30,US,Inflation Rate YoY SEP,0.082,8.30%,0.081,0.082
+Thursday,10/13/22,20:30,CN,Inflation Rate YoY SEP,0.028,2.50%,0.028,0.027
+Friday,10/14/22,7:30,US,Retail Sales MoM SEP,0,0.40%,0.002,0.002
+Friday,10/14/22,8:30,GB,PM Liz Truss Speech ,,,,
+Friday,10/14/22,9:00,US,Michigan Consumer Sentiment Prel OCT,59.8,58.6,59,58.3
+Saturday,10/15/22,,CN,20th National Congress of the Chinese Communist Party,,,,
+Sunday,10/16/22,,CN,20th National Congress of the Chinese Communist Party,,,,
+Monday,10/17/22,5:15,GB,Chancellor Jeremy Hunt Statement,,,,
+Monday,10/17/22,,CN,20th National Congress of the Chinese Communist Party,,,,
+Tuesday,10/18/22,,CN,20th National Congress of the Chinese Communist Party,,,,
+Wednesday,10/19/22,1:00,GB,Inflation Rate YoY SEP,0.101,9.90%,0.1,0.099
+Wednesday,10/19/22,7:30,CA,Inflation Rate YoY SEP,0.069,7%,0.068,0.068
+Wednesday,10/19/22,7:30,US,Building Permits SEP,1.564M,1.542M,1.53M,1.487M
+Wednesday,10/19/22,18:50,JP,Balance of Trade SEP,-2094B,-2820B,-2167.4B,-2100B
+Wednesday,10/19/22,,CN,20th National Congress of the Chinese Communist Party,,,,
+Thursday,10/20/22,18:01,GB,Gfk Consumer Confidence OCT,-47,-49,-52,-53
+Thursday,10/20/22,18:30,JP,Inflation Rate YoY SEP,0.03,3%,,0.032
+Thursday,10/20/22,,CN,20th National Congress of the Chinese Communist Party,,,,
+Friday,10/21/22,1:00,GB,Retail Sales MoM SEP,-0.014,-1.70%,-0.005,-0.003
+Friday,10/21/22,,CN,20th National Congress of the Chinese Communist Party,,,,
+Sunday,10/23/22,20:45,CN,Industrial Production YoY SEP,0.063,4.20%,0.045,0.044
+Sunday,10/23/22,21:00,CN,Balance of Trade SEP,84.74B,79.39B,81B,80B
+Wednesday,10/26/22,9:00,CA,BoC Monetary Policy Report,,,,
+Thursday,10/27/22,7:30,US,Durable Goods Orders MoM SEP,0.004,0.20%,0.006,0.002
+Friday,10/28/22,7:30,US,Personal Income MoM SEP,0.004,0.40%,0.003,0.002
+Friday,10/28/22,7:30,US,Personal Spending MoM SEP,0.006,0.60%,0.004,0.003
+Sunday,10/30/22,20:30,CN,NBS Manufacturing PMI OCT,49.2,50.1,50,50
+Monday,10/31/22,0:00,JP,Consumer Confidence OCT,29.9,30.8,,30
+Monday,10/31/22,5:00,EA,Inflation Rate YoY Flash OCT,0.107,9.90%,0.102,0.104
+Monday,10/31/22,20:45,CN,Caixin Manufacturing PMI OCT,49.2,48.1,49,48.4
+Tuesday,11/01/22,9:00,US,ISM Manufacturing PMI OCT,50.2,50.9,50,50.1
+Tuesday,11/01/22,9:00,US,JOLTs Job Openings SEP,10.717M,10.28M,10M,10.2M
+Wednesday,11/02/22,13:30,US,Fed Press Conference,,,,
+Thursday,11/03/22,7:30,CA,Balance of Trade SEP,1.14B,0.55B,1.34B, 3.6B
+Thursday,11/03/22,7:30,US,Balance of Trade SEP,-73.3B,-65.7B,-72.2B,-72B
+Thursday,11/03/22,9:00,US,ISM Non-Manufacturing PMI OCT,54.4,56.7,55.5,54.5
+Friday,11/04/22,7:30,US,Non Farm Payrolls OCT,261K,315K,200K,240K
+Friday,11/04/22,9:00,CA,Ivey PMI s.a OCT,50.1,59.5,,57
+Sunday,11/06/22,22:00,CN,Balance of Trade OCT,85.15B,84.74B,95.95B,91B
+Tuesday,11/08/22,20:30,CN,Inflation Rate YoY OCT,0.021,2.80%,0.024,0.026
+Thursday,11/10/22,8:30,US,Core Inflation Rate YoY OCT,0.063,6.60%,0.065,0.067
+Thursday,11/10/22,8:30,US,Inflation Rate YoY OCT,0.077,8.20%,0.08,0.081
+Friday,11/11/22,2:00,GB,GDP MoM SEP,-0.006,-0.10%,-0.004,-0.005
+Friday,11/11/22,10:00,US,Michigan Consumer Sentiment Prel NOV,54.7,59.9,59.5,59.3
+Monday,11/14/22,21:00,CN,Industrial Production YoY OCT,0.05,6.30%,0.052,0.056
+Tuesday,11/15/22,2:00,GB,Claimant Count Change OCT,3.3K,3.9K,,27K
+Tuesday,11/15/22,8:30,US,PPI MoM OCT,0.002,0.20%,0.004,0.003
+Wednesday,11/16/22,2:00,GB,Inflation Rate YoY OCT,0.111,10.10%,0.107,0.11
+Wednesday,11/16/22,8:30,CA,Inflation Rate YoY OCT,0.069,6.90%,0.069,0.07
+Wednesday,11/16/22,8:30,US,Retail Sales MoM OCT,0.013,0%,0.01,0.009
+Wednesday,11/16/22,18:50,JP,Balance of Trade OCT,-2162.3B,-2094.3B,-1610B,-1400B
+Thursday,11/17/22,7:00,GB,UK Autumn Statement,,,,
+Thursday,11/17/22,8:30,US,Building Permits Prel OCT,1.526M,1.564M,,1.465M
+Thursday,11/17/22,18:30,JP,Inflation Rate YoY OCT,0.037,3%,,0.032
+Thursday,11/17/22,19:01,GB,GfK Consumer Confidence NOV,-44,-47,,-51
+Friday,11/18/22,2:00,GB,Retail Sales MoM OCT,0.006,-1.50%,0.003,-0.001
+Wednesday,11/23/22,8:30,US,Durable Goods Orders MoM OCT,0.01,0.30%,0.004,0.003
+Wednesday,11/23/22,14:00,US,FOMC Minutes,,,,
+Tuesday,11/29/22,20:30,CN,NBS Manufacturing PMI NOV,48,49.2,49,49
+Wednesday,11/30/22,5:00,EA,Inflation Rate YoY Flash NOV,0.1,10.60%,0.104,0.103
+Wednesday,11/30/22,10:00,US,JOLTs Job Openings OCT,10.334M,10.687M,10.3M,10.4M
+Wednesday,11/30/22,13:30,US,Fed Chair Powell Speech ,,,,
+Wednesday,11/30/22,20:45,CN,Caixin Manufacturing PMI NOV,49.4,49.2,48.9,48.4
+Thursday,12/01/22,0:00,JP,Consumer Confidence NOV,28.6,29.9,,29.1
+Thursday,12/01/22,8:30,US,Personal Income MoM OCT,0.007,0.40%,0.004,0.003
+Thursday,12/01/22,8:30,US,Personal Spending MoM OCT,0.008,0.60%,0.008,0.006
+Thursday,12/01/22,10:00,US,ISM Manufacturing PMI NOV,49,50.2,49.8,50
+Friday,12/02/22,8:30,US,Non Farm Payrolls NOV,263K,284K,200K,210K
+Monday,12/05/22,10:00,US,ISM Non-Manufacturing PMI NOV,56.5,54.4,53.3,53
+Tuesday,12/06/22,8:30,CA,Balance of Trade OCT,1.21B,0.61B,1.2B,3.4B
+Tuesday,12/06/22,8:30,US,Balance of Trade OCT,-78.2B,-74.1B,-80B,-73B
+Tuesday,12/06/22,10:00,CA,Ivey PMI s.a NOV,51.4,50.1,,49
+Tuesday,12/06/22,22:00,CN,Balance of Trade NOV,69.84B,85.15B,78.1B,81B
+Thursday,12/08/22,20:30,CN,Inflation Rate YoY NOV,0.016,2.10%,0.016,0.018
+Friday,12/09/22,8:30,US,PPI MoM NOV,0.003,0.30%,0.002,0.003
+Friday,12/09/22,10:00,US,Michigan Consumer Sentiment Prel DEC,59.1,56.8,56.9,56.4
+Monday,12/12/22,2:00,GB,GDP MoM OCT,0.005,-0.60%,0.004,0.004
+Tuesday,12/13/22,2:00,GB,Claimant Count Change NOV,30.5K,-6.4K,3.5K,8K
+Tuesday,12/13/22,8:30,US,Core Inflation Rate YoY NOV,0.06,6.30%,0.061,0.062
+Tuesday,12/13/22,8:30,US,Inflation Rate YoY NOV,0.071,7.70%,0.073,0.076
+Tuesday,12/13/22,18:50,JP,Tankan Large Manufacturers Index Q4,7,8,6,6
+Wednesday,12/14/22,2:00,GB,Inflation Rate YoY NOV,0.107,11.10%,0.109,0.11
+Wednesday,12/14/22,14:00,US,Fed Interest Rate Decision,0.045,4%,0.045,0.045
+Wednesday,12/14/22,14:30,US,Fed Press Conference,,,,
+Wednesday,12/14/22,18:50,JP,Balance of Trade NOV,-2027.4B,-2166.2B,-1680.3B,-1800B
+Wednesday,12/14/22,21:00,CN,Industrial Production YoY NOV,0.022,5%,0.036,0.04
+Thursday,12/15/22,7:00,GB,BoE Interest Rate Decision,0.035,3%,0.035,0.035
+Thursday,12/15/22,8:15,EA,Deposit Facility Rate,0.02,1.50%,0.02,0.02
+Thursday,12/15/22,8:15,EA,ECB Interest Rate Decision,0.025,2%,0.025,0.025
+Thursday,12/15/22,8:30,US,Retail Sales MoM NOV,-0.006,1.30%,-0.001,0.002
+Thursday,12/15/22,19:01,GB,GfK Consumer Confidence DEC,-42,-44,-43,-43
+Friday,12/16/22,2:00,GB,Retail Sales MoM NOV,-0.004,0.90%,0.003,0.003
+Monday,12/19/22,22:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,-0.001,-0.001
+Tuesday,12/20/22,8:30,US,Building Permits Prel NOV,1.342M,1.512M,1.485M,1.48M
+Wednesday,12/21/22,8:30,CA,Inflation Rate YoY NOV,0.068,6.90%,0.067,0.067
+Thursday,12/22/22,18:30,JP,Inflation Rate YoY NOV,0.038,3.70%,,0.039
+Friday,12/23/22,8:30,US,Durable Goods Orders MoM NOV,-0.021,0.70%,-0.006,-0.005
+Friday,12/23/22,8:30,US,Personal Income MoM NOV,0.004,0.70%,0.003,0.003
+Friday,12/23/22,8:30,US,Personal Spending MoM NOV,0.001,0.90%,0.002,0.003
+Friday,12/30/22,20:30,CN,NBS Manufacturing PMI DEC,47,48,48,49.5
+Monday,01/02/23,20:45,CN,Caixin Manufacturing PMI DEC,49,49.4,48.8,48
+Wednesday,01/04/23,10:00,US,ISM Manufacturing PMI DEC,48.4,49,48.5,49
+Wednesday,01/04/23,10:00,US,JOLTs Job Openings NOV,10.458M,10.512M,10M,10.1M
+Wednesday,01/04/23,14:00,US,FOMC Minutes,,,,
+Thursday,01/05/23,0:00,JP,Consumer Confidence DEC,30.3,28.6,,29
+Thursday,01/05/23,8:30,CA,Balance of Trade NOV,-0.04B,0.13B,0.61B,1.3B
+Thursday,01/05/23,8:30,US,Balance of Trade NOV,-61.5B,-77.8B,-73B,-72B
+Friday,01/06/23,5:00,EA,Inflation Rate YoY Flash DEC,0.092,10.10%,0.097,0.098
+Friday,01/06/23,8:30,US,Non Farm Payrolls DEC,223K,256K,200K,220K
+Friday,01/06/23,8:30,US,Unemployment Rate DEC,0.035,3.60%,0.037,0.037
+Friday,01/06/23,10:00,CA,Ivey PMI s.a DEC,33.4,51.4,,51
+Friday,01/06/23,10:00,US,ISM Non-Manufacturing PMI DEC,49.6,56.5,55,53
+Wednesday,01/11/23,20:30,CN,Inflation Rate YoY DEC,0.018,1.60%,0.018,0.02
+Thursday,01/12/23,8:30,US,Core Inflation Rate YoY DEC,0.057,6%,0.057,0.058
+Thursday,01/12/23,8:30,US,Inflation Rate YoY DEC,0.065,7.10%,0.065,0.067
+Thursday,01/12/23,22:00,CN,Balance of Trade DEC,78B,69.25B,76.2B, 80B
+Friday,01/13/23,2:00,GB,GDP MoM NOV,0.001,0.50%,-0.002,-0.002
+Friday,01/13/23,10:00,US,Michigan Consumer Sentiment Prel JAN,64.6,59.7,60.5,59
+Monday,01/16/23,21:00,CN,GDP Growth Rate YoY Q4,0.029,3.90%,0.018,0.015
+Monday,01/16/23,21:00,CN,Industrial Production YoY DEC,0.013,2.20%,0.002,0.008
+Tuesday,01/17/23,2:00,GB,Claimant Count Change DEC,19.7K,16.1K,,16K
+Tuesday,01/17/23,2:00,GB,Unemployment Rate NOV,0.037,3.70%,0.037,0.037
+Tuesday,01/17/23,8:30,CA,Inflation Rate YoY DEC,0.063,6.80%,0.064,0.064
+Tuesday,01/17/23,22:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,,-0.001
+Wednesday,01/18/23,2:00,GB,Inflation Rate YoY DEC,0.105,10.70%,0.105,0.105
+Wednesday,01/18/23,8:30,US,PPI MoM DEC,-0.005,0.20%,-0.001,-0.001
+Wednesday,01/18/23,8:30,US,Retail Sales MoM DEC,-0.011,-1%,-0.008,-0.004
+Wednesday,01/18/23,18:50,JP,Balance of Trade DEC,-1448.5B,-2029B,-1652.8B, -1900B
+Thursday,01/19/23,8:30,US,Building Permits Prel DEC,1.33M,1.351M,1.37M,1.4M
+Thursday,01/19/23,18:30,JP,Inflation Rate YoY DEC,0.04,3.80%,,0.04
+Thursday,01/19/23,19:01,GB,Gfk Consumer Confidence JAN,-45,-42,-40,-38
+Friday,01/20/23,2:00,GB,Retail Sales MoM DEC,-0.01,-0.50%,0.005,0.003
+Wednesday,01/25/23,10:00,CA,BoC Interest Rate Decision,0.045,4.25%,0.045,0.045
+Wednesday,01/25/23,10:00,CA,BoC Monetary Policy Report,,,,
+Thursday,01/26/23,8:30,US,Durable Goods Orders MoM DEC,0.056,-1.70%,0.025,0.022
+Thursday,01/26/23,8:30,US,GDP Growth Rate QoQ Adv Q4,0.029,3.20%,0.026,0.027
+Friday,01/27/23,8:30,US,Core PCE Price Index MoM DEC,0.003,0.20%,0.003,0.001
+Friday,01/27/23,8:30,US,Personal Income MoM DEC,0.002,0.30%,0.002,0.003
+Friday,01/27/23,8:30,US,Personal Spending MoM DEC,-0.002,-0.10%,-0.001,-0.001
+Monday,01/30/23,20:30,CN,NBS Manufacturing PMI JAN,50.1,47,49.8,49.5
+Tuesday,01/31/23,0:00,JP,Consumer Confidence JAN,31,30.3,30.5,30
+Tuesday,01/31/23,5:00,EA,GDP Growth Rate QoQ Flash Q4,0.001,0.30%,-0.001,0
+Tuesday,01/31/23,5:00,EA,GDP Growth Rate YoY Flash Q4,0.019,2.30%,0.018,0.016
+Tuesday,01/31/23,20:45,CN,Caixin Manufacturing PMI JAN,49.2,49,49.5,50
+Wednesday,02/01/23,5:00,EA,Inflation Rate YoY Flash JAN,0.085,9.20%,0.09,0.089
+Wednesday,02/01/23,5:00,EA,Unemployment Rate DEC,0.066,6.60%,0.065,0.065
+Wednesday,02/01/23,10:00,US,ISM Manufacturing PMI JAN,47.4,48.4,48,48
+Wednesday,02/01/23,10:00,US,JOLTs Job Openings DEC,11.012M,10.44M,10.25M,9.5M
+Wednesday,02/01/23,14:00,US,Fed Interest Rate Decision,0.0475,4.50%,0.0475,0.0475
+Wednesday,02/01/23,14:30,US,Fed Press Conference,,,,
+Thursday,02/02/23,7:00,GB,BoE Interest Rate Decision,0.04,3.50%,0.04,0.04
+Thursday,02/02/23,8:15,EA,Deposit Facility Rate,0.025,2%,0.025,0.025
+Thursday,02/02/23,8:15,EA,ECB Interest Rate Decision,0.03,2.50%,0.03,0.03
+Thursday,02/02/23,8:45,EA,ECB Press Conference,,,,
+Friday,02/03/23,8:30,US,Non Farm Payrolls JAN,517K,260K,185K,190K
+Friday,02/03/23,8:30,US,Unemployment Rate JAN,0.034,3.50%,0.036,0.036
+Friday,02/03/23,10:00,US,ISM Non-Manufacturing PMI JAN,55.2,49.2,50.4,50.6
+Monday,02/06/23,10:00,CA,Ivey PMI s.a JAN,60.1,49.3,42.3,40
+Tuesday,02/07/23,8:30,CA,Balance of Trade DEC,-0.16B,-0.22B,-0.5B,-0.4B
+Tuesday,02/07/23,8:30,US,Balance of Trade DEC,-67.4B,-61B,-68.5B,-68.8B
+Thursday,02/09/23,20:30,CN,Inflation Rate YoY JAN,0.021,1.80%,0.022,0.02
+Friday,02/10/23,2:00,GB,GDP Growth Rate QoQ Prel Q4,0,-0.20%,0,0.001
+Friday,02/10/23,2:00,GB,GDP Growth Rate YoY Prel Q4,0.004,1.90%,0.004,0.002
+Friday,02/10/23,2:00,GB,GDP MoM DEC,-0.005,0.10%,-0.003,-0.001
+Friday,02/10/23,8:30,CA,Unemployment Rate JAN,0.05,5%,0.051,0.052
+Friday,02/10/23,10:00,US,Michigan Consumer Sentiment Prel FEB,66.4,64.9,65,65
+Monday,02/13/23,18:50,JP,GDP Growth Annualized Prel Q4,0.006,-1%,0.02,0.016
+Monday,02/13/23,18:50,JP,GDP Growth Rate QoQ Prel Q4,0.002,-0.30%,0.005,0.004
+Tuesday,02/14/23,2:00,GB,Claimant Count Change JAN,-12.9K,-3.2K,,25.0K
+Tuesday,02/14/23,2:00,GB,Unemployment Rate DEC,0.037,3.70%,0.037,0.038
+Tuesday,02/14/23,8:30,US,Core Inflation Rate YoY JAN,0.056,5.70%,0.055,0.054
+Tuesday,02/14/23,8:30,US,Inflation Rate YoY JAN,0.064,6.50%,0.062,0.063
+Wednesday,02/15/23,2:00,GB,Inflation Rate YoY JAN,0.101,10.50%,0.103,0.103
+Wednesday,02/15/23,8:30,US,Retail Sales MoM JAN,0.03,-1.10%,0.018,0.012
+Wednesday,02/15/23,18:50,JP,Balance of Trade JAN,-3496.6B,-1451.8B,-3871.5B,-2200.0B
+Thursday,02/16/23,8:30,US,Building Permits Prel JAN,1.339M,1.337M,1.35M,1.374M
+Thursday,02/16/23,8:30,US,PPI MoM JAN,0.007,-0.20%,0.004,0.002
+Friday,02/17/23,2:00,GB,Retail Sales MoM JAN,0.005,-1.20%,-0.003,-0.008
+Tuesday,02/21/23,8:30,CA,Inflation Rate YoY JAN,0.059,6.30%,0.061,0.059
+Wednesday,02/22/23,14:00,US,FOMC Minutes,,,,
+Thursday,02/23/23,18:30,JP,Inflation Rate YoY JAN,0.043,4%,,0.042
+Thursday,02/23/23,19:01,GB,Gfk Consumer Confidence FEB,-38,-45,-43,-42
+Friday,02/24/23,8:30,US,Core PCE Price Index MoM JAN,0.006,0.40%,0.004,0.003
+Friday,02/24/23,8:30,US,Personal Income MoM JAN,0.006,0.30%,0.01,0.007
+Friday,02/24/23,8:30,US,Personal Spending MoM JAN,0.018,-0.10%,0.013,0.011
+Monday,02/27/23,8:30,US,Durable Goods Orders MoM JAN,-0.045,5.10%,-0.04,-0.035
+Tuesday,02/28/23,8:30,CA,GDP Growth Rate QoQ Q4,0,0.60%,,0.004
+Tuesday,02/28/23,20:30,CN,NBS Manufacturing PMI FEB,52.6,50.1,50.5,50.8
+Tuesday,02/28/23,20:45,CN,Caixin Manufacturing PMI FEB,51.6,49.2,50.2,50.3
+Wednesday,03/01/23,10:00,US,ISM Manufacturing PMI FEB,47.7,47.4,48,48
+Thursday,03/02/23,0:00,JP,Consumer Confidence FEB,31.1,31,32,32
+Thursday,03/02/23,5:00,EA,Inflation Rate YoY Flash FEB,0.085,8.60%,0.082,0.084
+Thursday,03/02/23,5:00,EA,Unemployment Rate JAN,0.067,6.70%,0.066,0.066
+Friday,03/03/23,10:00,US,ISM Non-Manufacturing PMI FEB,55.1,55.2,54.5,54.6
+Monday,03/06/23,10:00,CA,Ivey PMI s.a FEB,51.6,60.1,55.9,55
+Monday,03/06/23,23:30,CN,Balance of Trade JAN-FEB,116.88B,78B,81.8B,78.2B
+Tuesday,03/07/23,10:00,US,Fed Chair Powell Testimony,,,,
+Wednesday,03/08/23,8:30,CA,Balance of Trade JAN,1.92B,1.19B,-0.06B,0.1B
+Wednesday,03/08/23,8:30,US,Balance of Trade JAN,-68.3B,-67.2B,-68.9B,-69.0B
+Wednesday,03/08/23,10:00,CA,BoC Interest Rate Decision,0.045,4.50%,0.045,0.045
+Wednesday,03/08/23,10:00,US,Fed Chair Powell Testimony,,,,
+Wednesday,03/08/23,10:00,US,JOLTs Job Openings JAN,10.824M,11.234M,10.5M,10.6M
+Wednesday,03/08/23,20:30,CN,Inflation Rate YoY FEB,0.01,2.10%,0.019,0.023
+Thursday,03/09/23,22:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,-0.001,-0.001
+Friday,03/10/23,2:00,GB,GDP MoM JAN,0.003,-0.50%,0.001,0
+Friday,03/10/23,8:30,CA,Unemployment Rate FEB,0.05,5%,0.051,0.052
+Friday,03/10/23,8:30,US,Non Farm Payrolls FEB,311K,504K,205K,210.0K
+Friday,03/10/23,8:30,US,Unemployment Rate FEB,0.036,3.40%,0.034,0.034
+Monday,03/13/23,8:00,US,President Biden Speech on Banking System ,,,,
+Monday,03/13/23,10:30,US,Closed-door Fed Emergency Meeting,,,,
+Tuesday,03/14/23,2:00,GB,Claimant Count Change FEB,-11.2K,-30.3K,,-27.0K
+Tuesday,03/14/23,2:00,GB,Unemployment Rate JAN,0.037,3.70%,0.038,0.038
+Tuesday,03/14/23,7:30,US,Core Inflation Rate YoY FEB,0.055,5.60%,0.055,0.056
+Tuesday,03/14/23,7:30,US,Inflation Rate YoY FEB,0.06,6.40%,0.06,0.061
+Tuesday,03/14/23,21:00,CN,Industrial Production YoY JAN-FEB,0.024,1.30%,0.026,0.025
+Wednesday,03/15/23,7:30,US,PPI MoM FEB,-0.001,0.30%,0.003,0.004
+Wednesday,03/15/23,7:30,US,Retail Sales MoM FEB,-0.004,3.20%,-0.003,-0.002
+Wednesday,03/15/23,18:50,JP,Balance of Trade FEB,-897.7B,-3498.6B,-1069.4B,-1300.0B
+Thursday,03/16/23,7:30,US,Building Permits Prel FEB,1.524M,1.339M,1.34M,1.33M
+Thursday,03/16/23,8:15,EA,Deposit Facility Rate,0.03,2.50%,0.03,0.03
+Thursday,03/16/23,8:15,EA,ECB Interest Rate Decision,0.035,3%,0.035,0.035
+Thursday,03/16/23,8:45,EA,ECB Press Conference,,,,
+Friday,03/17/23,9:00,US,Michigan Consumer Sentiment Prel MAR,63.4,67,67,68
+Tuesday,03/21/23,7:30,CA,Inflation Rate YoY FEB,0.052,5.90%,0.054,0.052
+Wednesday,03/22/23,2:00,GB,Inflation Rate YoY FEB,0.104,10.10%,0.099,0.097
+Wednesday,03/22/23,13:00,US,Fed Interest Rate Decision,0.05,4.75%,0.05,0.05
+Wednesday,03/22/23,13:30,US,Fed Press Conference,,,,
+Thursday,03/23/23,7:00,GB,BoE Interest Rate Decision,0.0425,4%,0.0425,0.0425
+Thursday,03/23/23,18:30,JP,Inflation Rate YoY FEB,0.033,4.30%,,0.033
+Thursday,03/23/23,19:01,GB,Gfk Consumer Confidence MAR,-36,-38,-36,-36
+Friday,03/24/23,2:00,GB,Retail Sales MoM FEB,0.012,0.90%,0.002,0.003
+Friday,03/24/23,7:30,US,Durable Goods Orders MoM FEB,-0.01,-5%,0.006,0.007
+Thursday,03/30/23,20:30,CN,NBS Manufacturing PMI MAR,51.9,52.6,51.5,51.2
+Friday,03/31/23,4:00,EA,Inflation Rate YoY Flash MAR,0.069,8.50%,0.071,0.074
+Friday,03/31/23,4:00,EA,Unemployment Rate FEB,0.066,6.60%,0.067,0.067
+Friday,03/31/23,7:30,US,Core PCE Price Index MoM FEB,0.003,0.50%,0.004,0.006
+Friday,03/31/23,7:30,US,Personal Income MoM FEB,0.003,0.60%,0.002,0.004
+Friday,03/31/23,7:30,US,Personal Spending MoM FEB,0.002,2%,0.003,0.005
+Sunday,04/02/23,18:50,JP,Tankan Large Manufacturers Index Q1,1,7,3,1
+Sunday,04/02/23,20:45,CN,Caixin Manufacturing PMI MAR,50,51.6,51.7,52.2
+Monday,04/03/23,9:00,US,ISM Manufacturing PMI MAR,46.3,47.7,47.5,49
+Tuesday,04/04/23,9:00,US,JOLTs Job Openings FEB,9.931M,10.563M,10.4M,10.8M
+Wednesday,04/05/23,7:30,CA,Balance of Trade FEB,0.42B,1.2B,1.8B,1.4B
+Wednesday,04/05/23,7:30,US,Balance of Trade FEB,-70.5B,-68.7B,-69B,-69.0B
+Wednesday,04/05/23,9:00,US,ISM Non-Manufacturing PMI MAR,51.2,55.1,54.5,54
+Thursday,04/06/23,7:30,CA,Unemployment Rate MAR,0.05,5%,0.051,0.052
+Thursday,04/06/23,9:00,CA,Ivey PMI s.a MAR,58.2,51.6,56.1,49
+Friday,04/07/23,7:30,US,Non Farm Payrolls MAR,236K,326K,239K,250.0K
+Friday,04/07/23,7:30,US,Unemployment Rate MAR,0.035,3.60%,0.036,0.035
+Monday,04/10/23,0:00,JP,Consumer Confidence MAR,33.9,31.1,31.9,35
+Monday,04/10/23,20:30,CN,Inflation Rate YoY MAR,0.007,1%,0.01,0.02
+Wednesday,04/12/23,7:30,US,Core Inflation Rate YoY MAR,0.056,5.50%,0.056,0.055
+Wednesday,04/12/23,7:30,US,Inflation Rate MoM MAR,0.001,0.40%,0.002,0.003
+Wednesday,04/12/23,7:30,US,Inflation Rate YoY MAR,0.05,6%,0.052,0.053
+Wednesday,04/12/23,9:00,CA,BoC Monetary Policy Report,,,,
+Wednesday,04/12/23,13:00,US,FOMC Minutes,,,,
+Wednesday,04/12/23,22:00,CN,Balance of Trade MAR,88.19B,116.88B,39.2B, 52.0B
+Thursday,04/13/23,1:00,GB,GDP MoM FEB,0,0.40%,0.001,0.001
+Thursday,04/13/23,7:30,US,PPI MoM MAR,-0.005,0%,0,0.001
+Friday,04/14/23,7:30,US,Retail Sales MoM MAR,-0.01,-0.20%,-0.004,-0.009
+Friday,04/14/23,9:00,US,Michigan Consumer Sentiment Prel APR,63.5,62,62,62.4
+Monday,04/17/23,21:00,CN,GDP Growth Rate YoY Q1,0.045,2.90%,0.04,0.032
+Monday,04/17/23,21:00,CN,Industrial Production YoY MAR,0.039,2.40%,0.04,0.027
+Tuesday,04/18/23,1:00,GB,Claimant Count Change MAR,28.2K,-18.8K,,-9.5K
+Tuesday,04/18/23,1:00,GB,Unemployment Rate FEB,0.038,3.70%,0.037,0.038
+Tuesday,04/18/23,7:30,CA,Inflation Rate YoY MAR,0.043,5.20%,0.043,0.041
+Tuesday,04/18/23,7:30,US,Building Permits Prel MAR,1.413M,1.55M,1.45M,1.45M
+Wednesday,04/19/23,1:00,GB,Inflation Rate YoY MAR,0.101,10.40%,0.098,0.102
+Wednesday,04/19/23,18:50,JP,Balance of Trade MAR,-754.5B,-898.1B,-1294.8B, -1100.0B
+Thursday,04/20/23,18:01,GB,Gfk Consumer Confidence APR,-30,-36,-35,-34
+Thursday,04/20/23,18:30,JP,Inflation Rate YoY MAR,0.032,3.30%,,0.032
+Friday,04/21/23,1:00,GB,Retail Sales MoM MAR,-0.009,1.10%,-0.005,-0.005
+Wednesday,04/26/23,7:30,US,Durable Goods Orders MoM MAR,0.032,-1.20%,0.007,0.006
+Thursday,04/27/23,7:30,US,GDP Growth Rate QoQ Adv Q1,0.011,2.60%,0.02,0.023
+Thursday,04/27/23,23:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,-0.001,-0.001
+Friday,04/28/23,4:00,EA,GDP Growth Rate QoQ Flash Q1,0.001,0%,0.002,0.001
+Friday,04/28/23,4:00,EA,GDP Growth Rate YoY Flash Q1,0.013,1.80%,0.014,0.01
+Friday,04/28/23,7:30,US,Core PCE Price Index MoM MAR,0.003,0.30%,0.003,0.004
+Friday,04/28/23,7:30,US,Personal Income MoM MAR,0.003,0.30%,0.002,0.004
+Friday,04/28/23,7:30,US,Personal Spending MoM MAR,0,0.10%,-0.001,-0.002
+Saturday,04/29/23,20:30,CN,NBS Manufacturing PMI APR,49.2,51.9,51.4,51.5
+Saturday,04/29/23,0:00,JP,Consumer Confidence APR,35.4,33.9,,32
+Saturday,04/29/23,9:00,US,ISM Manufacturing PMI APR,47.1,46.3,46.8,46.5
+Tuesday,05/02/23,4:00,EA,Inflation Rate YoY Flash APR,0.07,6.90%,0.07,0.069
+Tuesday,05/02/23,9:00,US,JOLTs Job Openings MAR,9.59M,9.974M,9.775M,9.7M
+Wednesday,05/03/23,4:00,EA,Unemployment Rate MAR,0.065,6.60%,0.066,0.066
+Wednesday,05/03/23,9:00,US,ISM Services PMI APR,51.9,51.2,51.8,51.5
+Wednesday,05/03/23,13:00,US,Fed Interest Rate Decision,0.0525,5%,0.0525,0.0525
+Wednesday,05/03/23,13:30,US,Fed Press Conference,,,,
+Wednesday,05/03/23,20:45,CN,Caixin Manufacturing PMI APR,49.5,50,50.3,50.4
+Thursday,05/04/23,7:15,EA,Deposit Facility Rate,0.0325,3%,0.0325,0.0325
+Thursday,05/04/23,7:15,EA,ECB Interest Rate Decision,0.0375,3.50%,0.0375,0.0375
+Thursday,05/04/23,7:30,CA,Balance of Trade MAR,0.97B,-0.49B,0.2B,0.3B
+Thursday,05/04/23,7:30,US,Balance of Trade MAR,-64.2B,-70.6B,-63.3B,-63.1B
+Thursday,05/04/23,7:45,EA,ECB Press Conference,,,,
+Thursday,05/04/23,9:00,CA,Ivey PMI s.a APR,56.8,58.2,59,53
+Thursday,05/04/23,7:30,CA,Unemployment Rate APR,0.05,5%,0.051,0.052
+Thursday,05/04/23,7:30,US,Non Farm Payrolls APR,253K,165K,180K,190.0K
+Thursday,05/04/23,7:30,US,Unemployment Rate APR,0.034,3.50%,0.036,0.036
+Thursday,05/04/23,22:00,CN,Balance of Trade APR,90.21B,88.19B,71.6B,76.0B
+Wednesday,05/10/23,7:30,US,Core Inflation Rate YoY APR,0.055,5.60%,0.055,0.056
+Wednesday,05/10/23,7:30,US,Inflation Rate MoM APR,0.004,0.10%,0.004,0.003
+Wednesday,05/10/23,7:30,US,Inflation Rate YoY APR,0.049,5%,0.05,0.049
+Wednesday,05/10/23,20:30,CN,Inflation Rate YoY APR,0.001,0.70%,0.004,0.004
+Thursday,05/11/23,6:00,GB,BoE Interest Rate Decision,0.045,4.25%,0.045,0.045
+Thursday,05/11/23,7:30,US,PPI MoM APR,0.002,-0.40%,0.003,0.001
+Thursday,05/11/23,1:00,GB,GDP Growth Rate QoQ Prel Q1,0.001,0.10%,0.001,0.001
+Thursday,05/11/23,1:00,GB,GDP Growth Rate YoY Prel Q1,0.002,0.60%,0.002,0.003
+Thursday,05/11/23,1:00,GB,GDP MoM MAR,-0.003,0%,0,0.001
+Thursday,05/11/23,9:00,US,Michigan Consumer Sentiment Prel 05,57.7,63.5,63,64
+Thursday,05/11/23,21:00,CN,Industrial Production YoY APR,0.056,3.90%,0.109,0.098
+Tuesday,05/16/23,1:00,GB,Claimant Count Change APR,46.7K,26.5K,,-15.0K
+Tuesday,05/16/23,1:00,GB,Unemployment Rate MAR,0.039,3.80%,0.038,0.038
+Tuesday,05/16/23,7:30,CA,Inflation Rate YoY APR,0.044,4.30%,0.041,0.039
+Tuesday,05/16/23,7:30,US,Retail Sales MoM APR,0.004,-0.70%,0.008,0.007
+Tuesday,05/16/23,18:50,JP,GDP Growth Annualized Prel Q1,0.016,-0.10%,0.007,0.008
+Tuesday,05/16/23,18:50,JP,GDP Growth Rate QoQ Prel Q1,0.004,0%,0.001,0.002
+Wednesday,05/17/23,7:30,US,Building Permits Prel APR,1.416M,1.437M,1.437M,1.43M
+Wednesday,05/17/23,18:50,JP,Balance of Trade APR,-432.4B,-755.1B,-613.8B,-690B
+Thursday,05/18/23,18:01,GB,Gfk Consumer Confidence 05,-27,-30,-27,-32
+Thursday,05/18/23,18:30,JP,Inflation Rate YoY APR,0.035,3.20%,0.025,0.032
+Thursday,05/18/23,10:00,US,Fed Chair Powell Speech ,,,,
+Wednesday,05/24/23,1:00,GB,Inflation Rate YoY APR,0.087,10.10%,0.082,0.085
+Wednesday,05/24/23,13:00,US,FOMC Minutes,,,,
+Wednesday,05/24/23,1:00,GB,Retail Sales MoM APR,0.005,-1.20%,0.003,0.003
+Wednesday,05/24/23,7:30,US,Core PCE Price Index MoM APR,0.004,0.30%,0.003,0.003
+Wednesday,05/24/23,7:30,US,Durable Goods Orders MoM APR,0.011,3.30%,-0.01,-0.011
+Wednesday,05/24/23,7:30,US,Personal Income MoM APR,0.004,0.30%,0.004,0.003
+Wednesday,05/24/23,7:30,US,Personal Spending MoM APR,0.008,0.10%,0.004,0.003
+Tuesday,05/30/23,20:30,CN,NBS Manufacturing PMI 05,48.8,49.2,49.4,49.8
+Wednesday,05/31/23,0:00,JP,Consumer Confidence 05,36,35.4,36.1,36
+Wednesday,05/31/23,7:30,CA,GDP Growth Rate QoQ Q1,0.008,0%,0.004,0.005
+Wednesday,05/31/23,9:00,US,JOLTs Job Openings APR,10.103M,9.745M,9.375M,9.2M
+Wednesday,05/31/23,20:45,CN,Caixin Manufacturing PMI 05,50.9,49.5,49.5,49.6
+Thursday,06/01/23,4:00,EA,Inflation Rate YoY Flash 05,0.061,7%,0.063,0.065
+Thursday,06/01/23,4:00,EA,Unemployment Rate APR,0.065,6.60%,0.065,0.065
+Thursday,06/01/23,9:00,US,ISM Manufacturing PMI 05,46.9,47.1,47,48
+Friday,06/02/23,7:30,US,Non Farm Payrolls 05,339K,294K,190K,180.0K
+Friday,06/02/23,7:30,US,Unemployment Rate 05,0.037,3.40%,0.035,0.035
+Monday,06/05/23,9:00,US,ISM Services PMI 05,50.3,51.9,52.2,52.4
+Tuesday,06/06/23,9:00,CA,Ivey PMI s.a 05,53.5,56.8,57.2,56.5
+Tuesday,06/06/23,22:00,CN,Balance of Trade 05,65.81B,90.21B,92B,91.0B
+Wednesday,06/07/23,7:30,US,Balance of Trade APR,-74.6B,-60.6B,-75.2B,-78.2B
+Thursday,06/08/23,20:30,CN,Inflation Rate YoY 05,0.002,0.10%,0.003,0.002
+Friday,06/09/23,7:30,CA,Unemployment Rate 05,0.052,5%,0.051,0.051
+Tuesday,06/13/23,1:00,GB,Claimant Count Change 05,-13.6K,23.4K,,22.0K
+Tuesday,06/13/23,1:00,GB,Unemployment Rate APR,0.038,3.90%,0.04,0.039
+Tuesday,06/13/23,7:30,US,Core Inflation Rate YoY 05,0.053,5.50%,0.053,0.054
+Tuesday,06/13/23,7:30,US,Inflation Rate MoM 05,0.001,0.40%,0.002,0.003
+Tuesday,06/13/23,7:30,US,Inflation Rate YoY 05,0.04,4.90%,0.041,0.043
+Wednesday,06/14/23,1:00,GB,GDP MoM APR,0.002,-0.30%,0.002,0.002
+Wednesday,06/14/23,7:30,US,PPI MoM 05,-0.003,0.20%,-0.001,0.001
+Wednesday,06/14/23,13:00,US,Fed Interest Rate Decision,0.0525,5.25%,0.0525,0.0525
+Wednesday,06/14/23,13:30,US,Fed Press Conference,,,,
+Wednesday,06/14/23,18:50,JP,Balance of Trade 05,-1372.5B,-432.3B,-1331.9B,-1310.0B
+Wednesday,06/14/23,21:00,CN,Industrial Production YoY 05,0.035,5.60%,0.036,0.05
+Thursday,06/15/23,7:15,EA,Deposit Facility Rate,0.035,3.25%,0.035,0.035
+Thursday,06/15/23,7:15,EA,ECB Interest Rate Decision,0.04,3.75%,0.04,0.04
+Thursday,06/15/23,7:30,US,Retail Sales MoM 05,0.003,0.40%,-0.001,0.002
+Thursday,06/15/23,7:45,EA,ECB Press Conference,,,,
+Thursday,06/15/23,22:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,-0.001,-0.001
+Friday,06/16/23,9:00,US,Michigan Consumer Sentiment Prel JUN,63.9,59.2,60,60.8
+Tuesday,06/20/23,7:30,US,Building Permits Prel 05,1.491M,1.417M,1.42M,1.425M
+Wednesday,06/21/23,1:00,GB,Inflation Rate YoY 05,0.087,8.70%,0.084,0.085
+Wednesday,06/21/23,9:00,US,Fed Chair Powell Testimony,,,,
+Thursday,06/22/23,6:00,GB,BoE Interest Rate Decision,0.05,4.50%,0.0475,0.0475
+Thursday,06/22/23,9:00,US,Fed Chair Powell Testimony,,,,
+Thursday,06/22/23,18:01,GB,Gfk Consumer Confidence JUN,-24,-27,-26,-27
+Thursday,06/22/23,18:30,JP,Inflation Rate YoY 05,0.032,3.50%,0.041,0.032
+Friday,06/23/23,1:00,GB,Retail Sales MoM 05,0.003,0.50%,-0.002,-0.003
+Sunday,06/25/23,,EA,ECB Forum on Central Banking,,,,
+Monday,06/26/23,12:30,EA,ECB President Lagarde Speech ,,,,
+Monday,06/26/23,,EA,ECB Forum on Central Banking,,,,
+Tuesday,06/27/23,3:00,EA,ECB President Lagarde Speech ,,,,
+Tuesday,06/27/23,7:30,CA,Inflation Rate YoY 05,0.034,4.40%,0.034,0.036
+Tuesday,06/27/23,7:30,US,Durable Goods Orders MoM 05,0.017,1.20%,-0.01,-0.009
+Tuesday,06/27/23,,EA,ECB Forum on Central Banking,,,,
+Wednesday,06/28/23,8:30,US,Fed Chair Powell Speech ,,,,
+Thursday,06/29/23,0:00,JP,Consumer Confidence JUN,36.2,36,36.2,38
+Thursday,06/29/23,1:30,US,Fed Chair Powell Speech ,,,,
+Thursday,06/29/23,20:30,CN,NBS Manufacturing PMI JUN,49,48.8,49,51
+Friday,06/30/23,4:00,EA,Inflation Rate YoY Flash JUN,0.055,6.10%,0.056,0.056
+Friday,06/30/23,4:00,EA,Unemployment Rate 05,0.065,6.50%,0.065,0.065
+Friday,06/30/23,7:30,US,Core PCE Price Index MoM 05,0.003,0.40%,0.003,0.003
+Friday,06/30/23,7:30,US,Personal Income MoM 05,0.004,0.30%,0.003,0.003
+Friday,06/30/23,7:30,US,Personal Spending MoM 05,0.001,0.60%,0.002,0.004
+Sunday,07/02/23,18:50,JP,Tankan Large Manufacturers Index Q2,5,1,3,3
+Sunday,07/02/23,20:45,CN,Caixin Manufacturing PMI JUN,50.5,50.9,50.2,50.4
+Monday,07/03/23,9:00,US,ISM Manufacturing PMI JUN,46,46.9,47,48
+Wednesday,07/05/23,13:00,US,FOMC Minutes,,,,
+Thursday,07/06/23,9:00,US,ISM Services PMI JUN,53.9,50.3,51,50
+Thursday,07/06/23,9:00,US,JOLTs Job Openings 05,9.8M,10.32M,9.935M,9.9M
+Friday,07/07/23,7:30,CA,Unemployment Rate JUN,0.054,5.20%,0.053,0.054
+Friday,07/07/23,7:30,US,Non Farm Payrolls JUN,209K,306K,225K,250.0K
+Friday,07/07/23,7:30,US,Unemployment Rate JUN,0.036,3.70%,0.036,0.037
+Friday,07/07/23,9:00,CA,Ivey PMI s.a JUN,50.2,53.5,,52.3
+Sunday,07/09/23,20:30,CN,Inflation Rate YoY JUN,0,0.20%,0.002,0.001
+Tuesday,07/11/23,1:00,GB,Unemployment Rate 05,0.04,3.80%,0.038,0.039
+Wednesday,07/12/23,7:30,US,Core Inflation Rate MoM JUN,0.002,0.40%,0.003,0.003
+Wednesday,07/12/23,7:30,US,Core Inflation Rate YoY JUN,0.048,5.30%,0.05,0.05
+Wednesday,07/12/23,7:30,US,Inflation Rate MoM JUN,0.002,0.10%,0.003,0.002
+Wednesday,07/12/23,7:30,US,Inflation Rate YoY JUN,0.03,4%,0.031,0.032
+Wednesday,07/12/23,9:00,CA,BoC Interest Rate Decision,0.05,4.75%,0.05,0.05
+Wednesday,07/12/23,9:00,CA,BoC Monetary Policy Report,,,,
+Wednesday,07/12/23,22:00,CN,Balance of Trade JUN,70.62B,65.81B,74.8B, 90.0B
+Thursday,07/13/23,1:00,GB,GDP MoM 05,-0.001,0.20%,-0.003,-0.002
+Thursday,07/13/23,7:30,US,PPI MoM JUN,0.001,-0.40%,0.002,0.001
+Friday,07/14/23,9:00,US,Michigan Consumer Sentiment Prel JUL,72.6,64.4,65.5,64.5
+Sunday,07/16/23,21:00,CN,GDP Growth Rate YoY Q2,0.063,4.50%,0.073,0.071
+Sunday,07/16/23,21:00,CN,Industrial Production YoY JUN,0.044,3.50%,0.027,0.024
+Tuesday,07/18/23,7:30,CA,Inflation Rate YoY JUN,0.028,3.40%,0.03,0.03
+Tuesday,07/18/23,7:30,US,Retail Sales MoM JUN,0.002,0.50%,0.005,0.003
+Wednesday,07/19/23,1:00,GB,Inflation Rate YoY JUN,0.079,8.70%,0.082,0.083
+Wednesday,07/19/23,7:30,US,Building Permits Prel JUN,1.44M,1.496M,1.49M,1.462M
+Wednesday,07/19/23,18:50,JP,Balance of Trade JUN,43B,-1381.9B,-46.7B, -48B
+Thursday,07/20/23,18:30,JP,Inflation Rate YoY JUN,0.033,3.20%,0.035,0.033
+Friday,07/21/23,1:00,GB,Retail Sales MoM JUN,0.007,0.10%,0.002,0.001
+Wednesday,07/26/23,13:00,US,Fed Interest Rate Decision,0.055,5.25%,0.055,0.055
+Wednesday,07/26/23,13:30,US,Fed Press Conference,,,,
+Thursday,07/27/23,7:15,EA,ECB Interest Rate Decision,0.0425,4%,0.0425,0.0425
+Thursday,07/27/23,7:30,US,Durable Goods Orders MoM JUN,0.047,2%,0.01,0.006
+Thursday,07/27/23,7:30,US,GDP Growth Rate QoQ Adv Q2,0.024,2%,0.018,0.018
+Thursday,07/27/23,7:45,EA,ECB Press Conference,,,,
+Thursday,07/27/23,22:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,-0.001,-0.001
+Friday,07/28/23,7:30,US,Core PCE Price Index MoM JUN,0.002,0.30%,0.002,0.002
+Friday,07/28/23,7:30,US,Personal Income MoM JUN,0.003,0.50%,0.005,0.004
+Friday,07/28/23,7:30,US,Personal Spending MoM JUN,0.005,0.20%,0.004,0.003
+Sunday,07/30/23,20:30,CN,NBS Manufacturing PMI JUL,49.3,49,49.2,48.9
+Monday,07/31/23,4:00,EA,GDP Growth Rate QoQ Flash Q2,0.003,0%,0.002,0.003
+Monday,07/31/23,4:00,EA,GDP Growth Rate YoY Flash Q2,0.006,1.10%,0.005,0.006
+Monday,07/31/23,4:00,EA,Inflation Rate YoY Flash JUL,0.053,5.50%,0.053,0.052
+Monday,07/31/23,20:45,CN,Caixin Manufacturing PMI JUL,49.2,50.5,50.3,50.1
+Tuesday,08/01/23,9:00,US,ISM Manufacturing PMI JUL,46.4,46,46.8,48
+Tuesday,08/01/23,9:00,US,JOLTs Job Openings JUN,9.582M,9.616M,9.61M,9.5M
+Thursday,08/03/23,6:00,GB,BoE Interest Rate Decision,0.0525,5%,0.0525,0.0525
+Thursday,08/03/23,9:00,US,ISM Services PMI JUL,52.7,53.9,53,52
+Friday,08/04/23,7:30,CA,Unemployment Rate JUL,0.055,5.40%,0.055,0.054
+Friday,08/04/23,7:30,US,Non Farm Payrolls JUL,187K,185K,200K,190K
+Friday,08/04/23,7:30,US,Unemployment Rate JUL,0.035,3.60%,0.036,0.036
+Friday,08/04/23,9:00,CA,Ivey PMI s.a JUL,48.6,50.2,52.7,49.7
+Monday,08/07/23,22:00,CN,Balance of Trade JUL,80.6B,70.62B,70.6B,69B
+Tuesday,08/08/23,20:30,CN,Inflation Rate YoY JUL,-0.003,0%,-0.004,-0.003
+Thursday,08/10/23,7:30,US,Core Inflation Rate MoM JUL,0.002,0.20%,0.002,0.002
+Thursday,08/10/23,7:30,US,Core Inflation Rate YoY JUL,0.047,4.80%,0.048,0.048
+Thursday,08/10/23,7:30,US,Inflation Rate MoM JUL,0.002,0.20%,0.002,0.002
+Thursday,08/10/23,7:30,US,Inflation Rate YoY JUL,0.032,3%,0.033,0.031
+Friday,08/11/23,1:00,GB,GDP Growth Rate QoQ Prel Q2,0.002,0.10%,0,0.001
+Friday,08/11/23,1:00,GB,GDP Growth Rate YoY Prel Q2,0.004,0.20%,0.002,0.001
+Friday,08/11/23,1:00,GB,GDP MoM JUN,0.005,-0.10%,0.002,0.001
+Friday,08/11/23,7:30,US,PPI MoM JUL,0.003,0%,0.002,0.002
+Friday,08/11/23,9:00,US,Michigan Consumer Sentiment Prel AUG,71.2,71.6,71,71.3
+Monday,08/14/23,18:50,JP,GDP Growth Annualized Prel Q2,0.06,3.70%,0.031,0.032
+Monday,08/14/23,18:50,JP,GDP Growth Rate QoQ Prel Q2,0.015,0.90%,0.008,0.01
+Monday,08/14/23,21:00,CN,Industrial Production YoY JUL,0.037,4.40%,0.044,0.047
+Tuesday,08/15/23,1:00,GB,Unemployment Rate JUN,0.042,4%,0.04,0.04
+Tuesday,08/15/23,7:30,CA,Inflation Rate YoY JUL,0.033,2.80%,0.03,0.031
+Tuesday,08/15/23,7:30,US,Retail Sales MoM JUL,0.007,0.30%,0.004,0.003
+Wednesday,08/16/23,1:00,GB,Inflation Rate YoY JUL,0.068,7.90%,0.068,0.069
+Wednesday,08/16/23,7:30,US,Building Permits Prel JUL,1.442M,1.441M,1.463M,1.457M
+Wednesday,08/16/23,13:00,US,FOMC Minutes,,,,
+Wednesday,08/16/23,18:50,JP,Balance of Trade JUL,-78.7B,43.1B,24.6B,26B
+Thursday,08/17/23,18:30,JP,Inflation Rate YoY JUL,0.033,3.30%,0.025,0.031
+Friday,08/18/23,1:00,GB,Retail Sales MoM JUL,-0.012,0.60%,-0.005,-0.003
+Thursday,08/24/23,7:30,US,Durable Goods Orders MoM JUL,-0.052,4.40%,-0.04,0.005
+Friday,08/25/23,9:05,US,Fed Chair Powell Speech ,,,,
+Friday,08/25/23,14:00,EA,ECB President Lagarde Speech ,,,,
+Tuesday,08/29/23,9:00,US,JOLTs Job Openings JUL,8.827M,9.165M,9.465M,9.57M
+Wednesday,08/30/23,7:30,US,GDP Growth Rate QoQ 2nd Est Q2,0.021,2%,0.024,0.024
+Wednesday,08/30/23,20:30,CN,NBS Manufacturing PMI AUG,49.7,49.3,49.4,49.5
+Thursday,08/31/23,4:00,EA,Inflation Rate YoY Flash AUG,0.053,5.30%,0.051,0.05
+Thursday,08/31/23,7:30,US,Core PCE Price Index MoM JUL,0.002,0.20%,0.002,0.002
+Thursday,08/31/23,7:30,US,Personal Income MoM JUL,0.002,0.30%,0.003,0.003
+Thursday,08/31/23,7:30,US,Personal Spending MoM JUL,0.008,0.50%,0.007,0.004
+Thursday,08/31/23,20:45,CN,Caixin Manufacturing PMI AUG,51,49.2,49.3,49.3
+Friday,09/01/23,7:30,CA,GDP Growth Rate QoQ Q2,0,0.60%,0.003,0.001
+Friday,09/01/23,7:30,US,Non Farm Payrolls AUG,187K,157K,170K,180.0K
+Friday,09/01/23,7:30,US,Unemployment Rate AUG,0.038,3.50%,0.035,0.035
+Friday,09/01/23,9:00,US,ISM Manufacturing PMI AUG,47.6,46.4,47,47
+Wednesday,09/06/23,9:00,US,ISM Services PMI AUG,54.5,52.7,52.5,52.4
+Wednesday,09/06/23,22:00,CN,Balance of Trade AUG,68.36B,80.6B,73.9B,81B
+Thursday,09/07/23,9:00,CA,Ivey PMI s.a AUG,53.5,48.6,49.2,48
+Friday,09/08/23,7:30,CA,Unemployment Rate AUG,0.055,5.50%,0.056,0.057
+Friday,09/08/23,20:30,CN,Inflation Rate YoY AUG,0.001,-0.30%,0.002,0.001
+Tuesday,09/12/23,1:00,GB,Unemployment Rate JUL,0.043,4.20%,0.043,0.042
+Wednesday,09/13/23,1:00,GB,GDP MoM JUL,-0.005,0.50%,-0.002,-0.003
+Wednesday,09/13/23,7:30,US,Core Inflation Rate MoM AUG,0.003,0.20%,0.002,0.002
+Wednesday,09/13/23,7:30,US,Core Inflation Rate YoY AUG,0.043,4.70%,0.043,0.044
+Wednesday,09/13/23,7:30,US,Inflation Rate MoM AUG,0.006,0.20%,0.006,0.005
+Wednesday,09/13/23,7:30,US,Inflation Rate YoY AUG,0.037,3.20%,0.036,0.035
+Thursday,09/14/23,7:15,EA,ECB Interest Rate Decision,0.045,4.25%,0.0425,0.045
+Thursday,09/14/23,7:30,US,PPI MoM AUG,0.007,0.40%,0.004,0.004
+Thursday,09/14/23,7:30,US,Retail Sales MoM AUG,0.006,0.50%,0.002,0.004
+Thursday,09/14/23,7:45,EA,ECB Press Conference,,,,
+Thursday,09/14/23,21:00,CN,Industrial Production YoY AUG,0.045,3.70%,0.039,0.035
+Thursday,09/14/23,21:00,CN,Retail Sales YoY AUG,0.046,2.50%,0.03,0.026
+Friday,09/15/23,9:00,US,Michigan Consumer Sentiment Prel SEP,67.7,69.5,69.1,70
+Tuesday,09/19/23,7:30,CA,Inflation Rate YoY AUG,0.04,3.30%,0.038,0.039
+Tuesday,09/19/23,7:30,US,Building Permits Prel AUG,1.543M,1.443M,1.443M,1.43M
+Tuesday,09/19/23,18:50,JP,Balance of Trade AUG,-930.5B,-66.3B,-659.1B,-950.0B
+Wednesday,09/20/23,1:00,GB,Inflation Rate YoY AUG,0.067,6.80%,0.07,0.071
+Wednesday,09/20/23,13:00,US,Fed Interest Rate Decision,0.055,5.50%,0.055,0.055
+Wednesday,09/20/23,13:30,US,Fed Press Conference,,,,
+Thursday,09/21/23,6:00,GB,BoE Interest Rate Decision,0.0525,5.25%,0.055,0.055
+Thursday,09/21/23,18:30,JP,Inflation Rate YoY AUG,0.032,3.30%,,0.033
+Thursday,09/21/23,22:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,-0.001,-0.001
+Friday,09/22/23,1:00,GB,Retail Sales MoM AUG,0.004,-1.10%,0.005,0.004
+Wednesday,09/27/23,7:30,US,Durable Goods Orders MoM AUG,0.002,-5.60%,-0.005,-0.014
+Thursday,09/28/23,7:30,US,GDP Growth Rate QoQ Final Q2,0.021,2.20%,0.021,0.021
+Friday,09/29/23,4:00,EA,Inflation Rate YoY Flash SEP,0.043,5.20%,0.045,0.047
+Friday,09/29/23,7:30,US,Core PCE Price Index MoM AUG,0.001,0.20%,0.002,0.002
+Friday,09/29/23,7:30,US,Personal Income MoM AUG,0.004,0.20%,0.004,0.003
+Friday,09/29/23,7:30,US,Personal Spending MoM AUG,0.004,0.90%,0.004,0.006
+Friday,09/29/23,20:30,CN,NBS Manufacturing PMI SEP,50.2,49.7,50,50.4
+Saturday,09/30/23,20:45,CN,Caixin Manufacturing PMI SEP,50.6,51,51.2,51.2
+Sunday,10/01/23,18:50,JP,Tankan Large Manufacturers Index Q3,9,5,6,7
+Monday,10/02/23,9:00,US,ISM Manufacturing PMI SEP,49,47.6,47.8,48.1
+Tuesday,10/03/23,9:00,US,JOLTs Job Openings AUG,9.61M,8.92M,8.8M,8.6M
+Wednesday,10/04/23,9:00,US,ISM Services PMI SEP,53.6,54.5,53.6,53.7
+Thursday,10/05/23,9:00,CA,Ivey PMI s.a SEP,53.1,53.5,50.8,49.6
+Friday,10/06/23,7:30,CA,Unemployment Rate SEP,0.055,5.50%,0.056,0.056
+Friday,10/06/23,7:30,US,Non Farm Payrolls SEP,336K,227K,170K,150.0K
+Friday,10/06/23,7:30,US,Unemployment Rate SEP,0.038,3.80%,0.037,0.038
+Wednesday,10/11/23,7:30,US,PPI MoM SEP,0.005,0.70%,0.003,0.004
+Wednesday,10/11/23,13:00,US,FOMC Minutes,,,,
+Thursday,10/12/23,1:00,GB,GDP MoM AUG,0.002,-0.60%,0.002,0.001
+Thursday,10/12/23,7:30,US,Core Inflation Rate MoM SEP,0.003,0.30%,0.003,0.003
+Thursday,10/12/23,7:30,US,Core Inflation Rate YoY SEP,0.041,4.30%,0.041,0.041
+Thursday,10/12/23,7:30,US,Inflation Rate MoM SEP,0.004,0.60%,0.003,0.004
+Thursday,10/12/23,7:30,US,Inflation Rate YoY SEP,0.037,3.70%,0.036,0.037
+Thursday,10/12/23,20:30,CN,Inflation Rate YoY SEP,0,0.10%,0.002,0.003
+Thursday,10/12/23,22:00,CN,Balance of Trade SEP,77.71B,68.36B,70B,72.1B
+Friday,10/13/23,9:00,US,Michigan Consumer Sentiment Prel OCT,63,68.1,67.2,68
+Tuesday,10/17/23,7:30,CA,Inflation Rate YoY SEP,0.038,4%,0.04,0.045
+Tuesday,10/17/23,7:30,US,Retail Sales MoM SEP,0.007,0.80%,0.003,0.003
+Tuesday,10/17/23,21:00,CN,GDP Growth Rate YoY Q3,0.049,6.30%,0.044,0.046
+Tuesday,10/17/23,21:00,CN,Industrial Production YoY SEP,0.045,4.50%,0.043,0.043
+Tuesday,10/17/23,21:00,CN,Retail Sales YoY SEP,0.055,4.60%,0.049,0.047
+Wednesday,10/18/23,1:00,GB,Inflation Rate YoY SEP,0.067,6.70%,0.066,0.065
+Wednesday,10/18/23,7:30,US,Building Permits Prel SEP,1.473M,1.541M,1.45M,1.46M
+Wednesday,10/18/23,18:50,JP,Balance of Trade SEP,62.4B,-937.8B,-425B, -500.0B
+Thursday,10/19/23,11:00,US,Fed Chair Powell Speech ,,,,
+Thursday,10/19/23,18:30,JP,Inflation Rate YoY SEP,0.03,3.20%,,0.031
+Friday,10/20/23,1:00,GB,Retail Sales MoM SEP,-0.009,0.40%,-0.002,-0.002
+Tuesday,10/24/23,1:00,GB,Unemployment Rate - Adjusted AUG,0.042,,,
+Wednesday,10/25/23,9:00,CA,BoC Monetary Policy Report,,,,
+Wednesday,10/25/23,15:35,US,Fed Chair Powell Speech ,,,,
+Thursday,10/26/23,7:15,EA,ECB Interest Rate Decision,0.045,4.50%,0.045,0.045
+Thursday,10/26/23,7:30,US,Durable Goods Orders MoM SEP,0.047,-0.10%,0.017,0.011
+Thursday,10/26/23,7:30,US,GDP Growth Rate QoQ Adv Q3,0.049,2.10%,0.043,0.04
+Thursday,10/26/23,7:45,EA,ECB Press Conference,,,,
+Friday,10/27/23,7:30,US,Core PCE Price Index MoM SEP,0.003,0.10%,0.003,0.002
+Friday,10/27/23,7:30,US,Personal Income MoM SEP,0.003,0.40%,0.004,0.003
+Friday,10/27/23,7:30,US,Personal Spending MoM SEP,0.007,0.40%,0.005,0.005
+Monday,10/30/23,20:30,CN,NBS Manufacturing PMI OCT,49.5,50.2,50.2,50.5
+Monday,10/30/23,22:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,-0.001,-0.001
+Tuesday,10/31/23,5:00,EA,GDP Growth Rate QoQ Flash Q3,-0.001,0.20%,0,0
+Tuesday,10/31/23,5:00,EA,GDP Growth Rate YoY Flash Q3,0.001,0.50%,0.002,0.001
+Tuesday,10/31/23,5:00,EA,Inflation Rate YoY Flash OCT,0.029,4.30%,0.031,0.033
+Tuesday,10/31/23,20:45,CN,Caixin Manufacturing PMI OCT,49.5,50.6,50.8,50.7
+Wednesday,11/01/23,9:00,US,ISM Manufacturing PMI OCT,46.7,49,49,49.5
+Wednesday,11/01/23,9:00,US,JOLTs Job Openings SEP,9.553M,9.497M,9.25M,9.2M
+Wednesday,11/01/23,13:00,US,Fed Interest Rate Decision,0.055,5.50%,0.055,0.055
+Wednesday,11/01/23,13:30,US,Fed Press Conference,,,,
+Thursday,11/02/23,7:00,GB,BoE Interest Rate Decision,0.0525,5.25%,0.0525,0.0525
+Friday,11/03/23,7:30,CA,Unemployment Rate OCT,0.057,5.50%,0.056,0.055
+Friday,11/03/23,7:30,US,Non Farm Payrolls OCT,150K,297K,180K,190K
+Friday,11/03/23,7:30,US,Unemployment Rate OCT,0.039,3.80%,0.038,0.038
+Friday,11/03/23,9:00,US,ISM Services PMI OCT,51.8,53.6,53,53.7
+Monday,11/06/23,10:00,CA,Ivey PMI s.a OCT,53.4,53.1,54,52.1
+Monday,11/06/23,22:00,CN,Balance of Trade OCT,56.53B,77.71B,82B,81.0B
+Wednesday,11/08/23,9:15,US,Fed Chair Powell Speech ,,,,
+Wednesday,11/08/23,20:30,CN,Inflation Rate YoY OCT,-0.002,0%,-0.001,0
+Thursday,11/09/23,14:00,US,Fed Chair Powell Speech ,,,,
+Friday,11/10/23,2:00,GB,GDP Growth Rate QoQ Prel Q3,0,0.20%,-0.001,0
+Friday,11/10/23,2:00,GB,GDP Growth Rate YoY Prel Q3,0.006,0.60%,0.005,0.006
+Friday,11/10/23,2:00,GB,GDP MoM SEP,0.002,0.10%,0,0
+Friday,11/10/23,7:30,EA,ECB President Lagarde Speech ,,,,
+Friday,11/10/23,10:00,US,Michigan Consumer Sentiment Prel NOV,60.4,63.8,63.7,64.2
+Tuesday,11/14/23,2:00,GB,Unemployment Rate SEP,0.042,4.20%,0.043,0.043
+Tuesday,11/14/23,8:30,US,Core Inflation Rate MoM OCT,0.002,0.30%,0.003,0.003
+Tuesday,11/14/23,8:30,US,Core Inflation Rate YoY OCT,0.04,4.10%,0.041,0.04
+Tuesday,11/14/23,8:30,US,Inflation Rate MoM OCT,0,0.40%,0.001,0.001
+Tuesday,11/14/23,8:30,US,Inflation Rate YoY OCT,0.032,3.70%,0.033,0.033
+Tuesday,11/14/23,18:50,JP,GDP Growth Annualized Prel Q3,-0.021,4.50%,-0.006,-0.006
+Tuesday,11/14/23,18:50,JP,GDP Growth Rate QoQ Prel Q3,-0.005,1.10%,-0.001,-0.002
+Tuesday,11/14/23,21:00,CN,Industrial Production YoY OCT,0.046,4.50%,0.044,0.044
+Tuesday,11/14/23,21:00,CN,Retail Sales YoY OCT,0.076,5.50%,0.07,0.067
+Wednesday,11/15/23,2:00,GB,Inflation Rate YoY OCT,0.046,6.70%,0.048,0.049
+Wednesday,11/15/23,8:30,US,PPI MoM OCT,-0.005,0.40%,0.001,0.001
+Wednesday,11/15/23,8:30,US,Retail Sales MoM OCT,-0.001,0.90%,-0.003,0
+Wednesday,11/15/23,18:50,JP,Balance of Trade OCT,-662.5B,72.1B,-735.7B,-500B
+Friday,11/17/23,2:00,GB,Retail Sales MoM OCT,-0.003,-1.10%,0.003,0.002
+Friday,11/17/23,8:30,US,Building Permits Prel OCT,1.487M,1.471M,1.45M,1.45M
+Tuesday,11/21/23,8:30,CA,Inflation Rate YoY OCT,0.031,3.80%,0.032,0.033
+Tuesday,11/21/23,14:00,US,FOMC Minutes,,,,
+Wednesday,11/22/23,8:30,US,Durable Goods Orders MoM OCT,-0.054,4%,-0.031,-0.028
+Wednesday,11/22/23,,GB,Autumn Statement,,,,
+Thursday,11/23/23,18:30,JP,Inflation Rate YoY OCT,0.033,3%,,0.032
+Wednesday,11/29/23,8:30,US,GDP Growth Rate QoQ 2nd Est Q3,0.052,2.10%,0.05,0.049
+Wednesday,11/29/23,20:30,CN,NBS Manufacturing PMI NOV,49.4,49.5,49.7,49.9
+Thursday,11/30/23,5:00,EA,Inflation Rate YoY Flash NOV,0.024,2.90%,0.027,0.027
+Thursday,11/30/23,8:30,CA,GDP Growth Rate QoQ Q3,-0.003,0.30%,,0
+Thursday,11/30/23,8:30,US,Core PCE Price Index MoM OCT,0.002,0.30%,0.002,0.003
+Thursday,11/30/23,8:30,US,Personal Income MoM OCT,0.002,0.40%,0.002,0.003
+Thursday,11/30/23,8:30,US,Personal Spending MoM OCT,0.002,0.70%,0.002,0.004
+Thursday,11/30/23,20:45,CN,Caixin Manufacturing PMI NOV,50.7,49.5,49.8,49.8
+Friday,12/01/23,8:30,CA,Unemployment Rate NOV,0.058,5.70%,0.058,0.058
+Friday,12/01/23,10:00,US,ISM Manufacturing PMI NOV,46.7,46.7,47.6,47.2
diff --git a/The Effect of Economic News on Gold Prices Analysis/Dataset/gold_price_19_24.csv b/The Effect of Economic News on Gold Prices Analysis/Dataset/gold_price_19_24.csv
new file mode 100644
index 000000000..b0dda1293
--- /dev/null
+++ b/The Effect of Economic News on Gold Prices Analysis/Dataset/gold_price_19_24.csv	
@@ -0,0 +1,1280 @@
+Date,Price,Open,High,Low,Vol_K,Change_percent
+12/01/2023,2089.7,2056.5,2095.7,2052.6,241.62,1.58
+11/30/2023,2057.2,2065.4,2067.4,2051.2,151.92,-0.48
+11/29/2023,2067.1,2062,2072.7,2055.9,197.79,0.81
+11/28/2023,2050.5,2025,2054.4,2022.9,1.86,1.35
+11/27/2023,2023.1,2012.9,2027.5,2012.7,1.06,0.47
+11/24/2023,2013.7,2002.5,2014.1,2002,0.52,0.95
+11/23/2023,1994.75,1991.6,1999.4,1990.85,,-0.43
+11/22/2023,2003.4,2010.4,2015,1999.8,0.67,-0.43
+11/21/2023,2012,1994.1,2019.5,1993.2,0.67,1.07
+11/20/2023,1990.7,1997.9,1997.9,1978.1,0.31,0.30
+11/17/2023,1984.7,1984.2,1996.4,1981.1,133.12,-0.13
+11/16/2023,1987.3,1963,1991.1,1959,186.81,1.17
+11/15/2023,1964.3,1966.9,1979.2,1958.8,142.92,-0.11
+11/14/2023,1966.5,1950.3,1975.3,1938.8,180.74,0.84
+11/13/2023,1950.2,1943.4,1953.5,1935.6,183.7,0.65
+11/10/2023,1937.7,1964.1,1965.6,1936.9,229.64,-1.63
+11/09/2023,1969.8,1955.5,1971.5,1948.3,214.08,0.61
+11/08/2023,1957.8,1975.3,1977.5,1953.2,189.36,-0.80
+11/07/2023,1973.5,1984.8,1985.2,1962.8,218.95,-0.76
+11/06/2023,1988.6,1999.4,2000.1,1984.2,146.28,-0.53
+11/03/2023,1999.2,1993.5,2011.9,1989.3,222.19,0.29
+11/02/2023,1993.5,1992,1999.2,1986.3,158.65,0.30
+11/01/2023,1987.5,1993.3,2005.9,1978.2,197.63,-0.34
+10/31/2023,1994.3,2005.6,2017.7,1987.4,214.78,-0.56
+10/30/2023,2005.6,2013.5,2016.8,1999.7,181.34,0.83
+10/27/2023,1989,1987.5,2009.8,1978.5,0.37,0.06
+10/26/2023,1987.9,1981.6,1992.5,1974.4,0.2,0.12
+10/25/2023,1985.5,1972,1988.8,1971,0.16,0.44
+10/24/2023,1976.8,1975.1,1980.3,1958.3,1.23,-0.07
+10/23/2023,1978.2,1977.9,1983.1,1963.6,0.45,-0.81
+10/20/2023,1994.4,1988,2009.2,1983.7,,0.70
+10/19/2023,1980.5,1960.1,1990.2,1957,264.82,0.62
+10/18/2023,1968.3,1936.7,1975.8,1935.9,270.05,1.68
+10/17/2023,1935.7,1933.3,1944.5,1924.6,165.06,0.07
+10/16/2023,1934.3,1941.3,1943,1921.2,182.82,-0.37
+10/13/2023,1941.5,1881.7,1946.2,1881.5,312.99,3.11
+10/12/2023,1883,1888.1,1898.3,1880.6,163.48,-0.23
+10/11/2023,1887.3,1873.7,1890.9,1871.7,169.96,0.64
+10/10/2023,1875.3,1875.4,1879.1,1866.1,157.34,0.59
+10/09/2023,1864.3,1861,1877.3,1857.5,187.8,1.04
+10/06/2023,1845.2,1834.3,1849,1823.5,231.02,0.73
+10/05/2023,1831.8,1837.6,1843.5,1826.2,172.46,-0.16
+10/04/2023,1834.8,1838.7,1846.8,1831.6,195.05,-0.36
+10/03/2023,1841.5,1844.9,1849.3,1830.9,216.78,-0.31
+10/02/2023,1847.2,1864.4,1864.7,1842.7,202.15,-1.01
+09/29/2023,1866.1,1882.3,1896.7,1862.3,245.13,-0.67
+09/28/2023,1878.6,1893.3,1896.8,1874.5,231.42,-0.65
+09/27/2023,1890.9,1918.8,1921.7,1890.3,238.53,-1.51
+09/26/2023,1919.8,1935.1,1935.5,1917.2,212.26,-0.87
+09/25/2023,1936.6,1944.7,1946.8,1933.8,164.26,-0.46
+09/22/2023,1945.6,1939.6,1949.1,1939.6,139.93,0.31
+09/21/2023,1939.6,1952,1952.2,1933.1,225.91,-1.40
+09/20/2023,1967.1,1953,1968.9,1948.6,220.98,0.69
+09/19/2023,1953.7,1955.3,1958.9,1950.9,131.1,0.02
+09/18/2023,1953.4,1945.7,1955.7,1943.8,138.03,0.37
+09/15/2023,1946.2,1932.5,1952.4,1931.2,199.77,0.69
+09/14/2023,1932.8,1930.7,1934.5,1921.7,201.74,0.02
+09/13/2023,1932.5,1935.2,1938.4,1927.2,161,-0.13
+09/12/2023,1935.1,1945.6,1947.5,1929.9,161.99,-0.62
+09/11/2023,1947.2,1943.3,1954.6,1939.5,131.08,0.23
+09/08/2023,1942.7,1943.8,1954,1940.8,138.69,0.01
+09/07/2023,1942.5,1942.2,1947.9,1940.3,117.17,-0.09
+09/06/2023,1944.2,1951.5,1954.5,1940,148.78,-0.43
+09/05/2023,1952.6,1966.7,1972.6,1950.6,192.79,-0.54
+09/04/2023,1963.25,1966.6,1972.55,1962.55,,-0.17
+09/03/2023,1966.65,1966.4,1967.05,1965.5,,-0.02
+09/01/2023,1967.1,1966.4,1980.2,1960.7,160.73,0.06
+08/31/2023,1965.9,1970.2,1974.9,1965.5,133.71,-0.36
+08/30/2023,1973,1966,1977.1,1962.8,142.38,0.40
+08/29/2023,1965.1,1948.1,1966.5,1941.7,174.22,0.94
+08/28/2023,1946.8,1944,1954.2,1940.1,115.55,0.36
+08/25/2023,1939.9,1944.9,1950.4,1931,166.99,-0.37
+08/24/2023,1947.1,1944.9,1951.3,1939.2,137.39,-0.05
+08/23/2023,1948.1,1926.8,1949.7,1926.2,170.04,1.15
+08/22/2023,1926,1924,1933.2,1917.5,131.09,0.16
+08/21/2023,1923,1918.4,1927.9,1913.6,138.11,0.34
+08/18/2023,1916.5,1919.2,1926,1915.9,114.74,0.07
+08/17/2023,1915.2,1922.4,1933.5,1914.2,152.33,-0.68
+08/16/2023,1928.3,1933.1,1938.2,1922,128.61,-0.36
+08/15/2023,1935.2,1939.4,1944.3,1927.5,167.15,-0.45
+08/14/2023,1944,1945.6,1948.2,1934.2,120.98,-0.13
+08/11/2023,1946.6,1944.9,1953.6,1942.7,122.32,-0.12
+08/10/2023,1948.9,1947.7,1963.5,1944.4,168.26,-0.09
+08/09/2023,1950.6,1959.3,1966.1,1947.2,139.26,-0.47
+08/08/2023,1959.9,1971.5,1972.8,1956.5,142.34,-0.51
+08/07/2023,1970,1977.6,1981.7,1966.1,104.41,-0.31
+08/04/2023,1976.1,1969.6,1984.2,1954.5,156.42,0.37
+08/03/2023,1968.8,1970.8,1974.5,1964.5,141.35,-0.31
+08/02/2023,1975,1988.9,1992.2,1969.1,169.66,-0.19
+08/01/2023,1978.8,2004.2,2004.4,1978.3,167.76,-1.51
+07/31/2023,2009.2,1997.9,2010.9,1986.7,139.96,0.47
+07/28/2023,1999.9,1985.3,2002,1983.9,159.6,1.76
+07/27/2023,1965.3,1991.8,2002,1961.4,16.91,-1.23
+07/26/2023,1989.7,1985.9,1999.3,1982.8,11.94,0.33
+07/25/2023,1983.1,1976.1,1986.2,1971.1,8.63,0.08
+07/24/2023,1981.6,1983.2,1988.7,1974.7,6.44,0.76
+07/21/2023,1966.6,1972.1,1975.9,1958.8,156.54,-0.22
+07/20/2023,1970.9,1980,1989.8,1967.7,189.93,-0.50
+07/19/2023,1980.8,1982.5,1984.6,1973.3,159.41,0.00
+07/18/2023,1980.8,1958.3,1988.3,1958.1,264.09,1.25
+07/17/2023,1956.4,1958.6,1963.6,1949,165.83,-0.41
+07/14/2023,1964.4,1965.2,1967.8,1954.7,209.31,0.03
+07/13/2023,1963.8,1962.7,1968.5,1956.6,241.22,0.11
+07/12/2023,1961.7,1938,1965.1,1937.5,270.87,1.27
+07/11/2023,1937.1,1930.8,1944.5,1929.8,189.37,0.32
+07/10/2023,1931,1930.7,1933.7,1918,208.09,-0.08
+07/07/2023,1932.5,1916.6,1941.1,1915.4,214.27,0.89
+07/06/2023,1915.4,1922.4,1934,1908.5,231.51,-0.61
+07/05/2023,1927.1,1929.1,1942.9,1922.1,245.93,-0.35
+07/04/2023,1933.95,1928.85,1938.05,1927.75,,0.23
+07/03/2023,1929.5,1927.8,1939.9,1917.7,152.96,0.01
+06/30/2023,1929.4,1916.4,1930.8,1908.1,180.69,0.60
+06/29/2023,1917.9,1916.5,1921.3,1900.6,205.25,0.24
+06/28/2023,1913.4,1915.2,1916.7,1903.6,0.63,-0.09
+06/27/2023,1915.1,1927.4,1930.2,1912.3,0.23,-0.52
+06/26/2023,1925.1,1926.4,1934.5,1923,0.77,0.21
+06/23/2023,1921,1915,1939.3,1911.3,0.75,0.31
+06/22/2023,1915,1935.9,1935.9,1914,0.37,-1.09
+06/21/2023,1936.1,1939.5,1940.7,1922.2,0.81,-0.14
+06/20/2023,1938.9,1961.7,1961.7,1932.4,0.74,-1.28
+06/19/2023,1964.05,1969.55,1970.85,1959.9,,-0.27
+06/18/2023,1969.45,1970.85,1971.7,1968.65,,0.37
+06/16/2023,1962.2,1961.3,1970.6,1956.7,0.62,0.02
+06/15/2023,1961.8,1948.8,1963.7,1929.6,0.82,-0.36
+06/14/2023,1968.9,1957.2,1973.9,1952.5,199.71,0.53
+06/13/2023,1958.6,1971.4,1985.9,1953,198.4,-0.56
+06/12/2023,1969.7,1975.6,1981.4,1963.1,122.54,-0.38
+06/09/2023,1977.2,1980.5,1987.8,1971,130.41,-0.07
+06/08/2023,1978.6,1956.2,1985.7,1955.2,191.84,1.03
+06/07/2023,1958.4,1980,1986.5,1955.4,189.53,-1.17
+06/06/2023,1981.5,1978,1982.9,1970.3,136,0.36
+06/05/2023,1974.3,1962.3,1980.4,1953.8,179.99,0.24
+06/02/2023,1969.6,1994.6,2000.5,1963.7,209.69,-1.30
+06/01/2023,1995.5,1981.3,2000.7,1970.1,176.91,0.68
+05/31/2023,1982.1,1977.5,1993.1,1971.8,207.75,0.25
+05/30/2023,1977.1,1961.3,1981.9,1949.6,264.37,0.89
+05/29/2023,1959.75,1961.45,1968.15,1958.1,,-0.09
+05/28/2023,1961.5,1964.55,1964.55,1960.05,,-0.08
+05/26/2023,1963.1,1961.8,1975.7,1954.7,130.07,1.03
+05/25/2023,1943.1,1959.5,1965.4,1939,0,-1.00
+05/24/2023,1962.8,1975.4,1975.4,1969.2,0.19,-0.49
+05/23/2023,1972.4,1973.9,1980,1955.8,0,-0.12
+05/22/2023,1974.8,1980.5,1980.5,1980.5,0.01,-0.20
+05/19/2023,1978.7,1960,1976.7,1960,0.11,1.13
+05/18/2023,1956.5,1956.8,1956.8,1956.8,0.02,-1.22
+05/17/2023,1980.7,1983.6,1983.6,1983.6,0.01,-0.39
+05/16/2023,1988.4,2021.3,2022.7,1989.1,0.05,-1.47
+05/15/2023,2018,2013.8,2017.1,2013.8,0,-0.09
+05/12/2023,2019.8,2020.5,2027.8,2005.7,220.5,-0.03
+05/11/2023,2020.5,2036.8,2047.6,2016.7,296.98,-0.81
+05/10/2023,2037.1,2041.6,2056,2028.3,260.81,-0.28
+05/09/2023,2042.9,2028.4,2045.1,2026.4,199.7,0.48
+05/08/2023,2033.2,2024.6,2037.1,2022,182.21,0.41
+05/05/2023,2024.8,2058,2061.3,2007,283.3,-1.50
+05/04/2023,2055.7,2054.7,2085.4,2038.5,311,0.92
+05/03/2023,2037,2026.4,2050,2016,229.67,0.68
+05/02/2023,2023.3,1990.5,2028.8,1986.9,245.64,1.56
+05/01/2023,1992.2,2000.2,2015.4,1985.7,173.02,-0.35
+04/28/2023,1999.1,1997.2,2004.1,1984.4,172.45,0.01
+04/27/2023,1999,1999.8,2013.3,1982,203.9,0.61
+04/26/2023,1986.9,2000,2009.8,1986.6,0.62,-0.41
+04/25/2023,1995.1,1995.4,2005,1979.3,0.85,0.23
+04/24/2023,1990.6,1983.2,1991,1975.3,0.54,0.47
+04/21/2023,1981.3,2005.1,2007,1973,0.62,-1.42
+04/20/2023,2009.8,1996.5,2014.5,1994.2,0.42,0.59
+04/19/2023,1998,2008.5,2009.7,1971.9,0.92,-0.61
+04/18/2023,2010.3,1997.1,2013.4,1994.5,0.22,0.81
+04/17/2023,1994.2,2002.7,2007.6,1983.2,0.55,-0.40
+04/14/2023,2002.2,2041,2047.8,1995,0.72,-1.92
+04/13/2023,2041.3,2015.6,2048.6,2015.6,1.04,1.51
+04/12/2023,2010.9,2005.2,2025.7,2005.2,0.17,0.30
+04/11/2023,2004.8,1991.4,2006.5,1991.4,0.07,0.79
+04/10/2023,1989.1,2000,2006.6,1984,0.65,-1.13
+04/06/2023,2011.9,2022.2,2023.3,2005,0.49,-0.45
+04/05/2023,2020.9,2022.1,2033.8,2013.6,0.53,-0.06
+04/04/2023,2022.2,1984.6,2027.1,1979,0.81,1.93
+04/03/2023,1983.9,1968.1,1991.7,1950,0.74,0.76
+03/31/2023,1969,1981.3,1986.8,1968,0.96,-0.57
+03/30/2023,1980.3,1965.9,1984.4,1954.9,10.12,0.68
+03/29/2023,1966.9,1975.4,1976,1959.5,88.56,-0.33
+03/28/2023,1973.5,1957.8,1977.1,1949.9,183.58,0.10
+03/27/2023,1971.5,2000.3,2001.5,1962.7,107.04,-1.51
+03/24/2023,2001.7,2013.3,2023.9,1995.7,118.69,-0.58
+03/23/2023,2013.3,1992.5,2023.3,1984.4,74.55,2.37
+03/22/2023,1966.6,1959.7,1999.4,1953.7,60.53,0.42
+03/21/2023,1958.3,2000.7,2005.7,1955.9,65.17,-2.07
+03/20/2023,1999.7,2008.6,2031.7,1987,69.06,0.48
+03/17/2023,1990.2,1942.7,2010.4,1939.1,67.46,2.60
+03/16/2023,1939.7,1940.2,1954.6,1928.4,34.77,-0.43
+03/15/2023,1948.1,1924.5,1959.1,1906,84.73,1.95
+03/14/2023,1910.9,1919.4,1919.4,1899.8,261.28,-0.29
+03/13/2023,1916.5,1877.1,1919.5,1875.7,452.33,2.64
+03/10/2023,1867.2,1835.1,1874.3,1830,345.81,1.78
+03/09/2023,1834.6,1818,1839.4,1815.4,228.47,0.88
+03/08/2023,1818.6,1818,1828.7,1813.4,208.29,-0.08
+03/07/2023,1820,1852.6,1856.9,1817.1,248.23,-1.87
+03/06/2023,1854.6,1861,1864.3,1850.6,136.22,0.00
+03/03/2023,1854.6,1842.1,1864.4,1842,158.96,0.77
+03/02/2023,1840.5,1843.8,1845.3,1835.9,139.76,-0.27
+03/01/2023,1845.4,1834,1852.5,1829.6,182.58,0.47
+02/28/2023,1836.7,1823.9,1838.6,1810.8,184.51,0.65
+02/27/2023,1824.9,1818,1827.3,1812,130.43,0.87
+02/24/2023,1809.2,1825.2,1827.1,1808.8,0.4,-0.53
+02/23/2023,1818.8,1823.6,1832.7,1818.3,0.65,-0.79
+02/22/2023,1833.3,1837,1846.4,1825.1,0.57,-0.50
+02/21/2023,1842.5,1850.5,1856.4,1839,210.17,-0.43
+02/20/2023,1850.5,1847.55,1856.35,1846.3,,0.15
+02/19/2023,1847.75,1851.2,1852.15,1847.55,,0.40
+02/17/2023,1840.4,1827.4,1842.2,1818.4,0.04,-0.09
+02/16/2023,1842,1838.6,1843.7,1827.2,0.22,0.43
+02/15/2023,1834.2,1842,1842,1828.2,0.37,-1.07
+02/14/2023,1854,1854.1,1862,1846.2,0.66,0.11
+02/13/2023,1851.9,1859,1861,1850,0.57,-0.59
+02/10/2023,1862.8,1861.6,1863.5,1852.4,0.03,-0.18
+02/09/2023,1866.2,1875.3,1884.6,1859.8,0.22,-0.60
+02/08/2023,1877.4,1872.1,1880.4,1872.1,0.23,0.30
+02/07/2023,1871.7,1870,1875.7,1868,0.3,0.29
+02/06/2023,1866.2,1865.6,1880,1863.4,0.42,0.18
+02/03/2023,1862.9,1912.4,1917,1861.5,0.99,-2.79
+02/02/2023,1916.3,1952.3,1959.1,1911.3,0.75,-0.60
+02/01/2023,1927.8,1927.2,1955,1922,2.29,-0.09
+01/31/2023,1929.5,1923,1930.4,1900.6,1.91,0.34
+01/30/2023,1922.9,1928.3,1933.6,1920.3,27.22,-0.71
+01/27/2023,1936.6,1936.8,1943,1923.7,2.33,-0.05
+01/26/2023,1937.6,1955.3,1957,1926.5,2.1,-0.65
+01/25/2023,1950.3,1946,1956,1928.7,1.27,0.37
+01/24/2023,1943.1,1940.5,1950.6,1926.3,1.08,0.36
+01/23/2023,1936.2,1936.1,1943.7,1920.1,0.97,0.41
+01/20/2023,1928.2,1933.7,1939,1922,165.27,0.22
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+06/28/2019,1413.7,1413.3,1427.8,1408.6,306.62,0.12
+06/27/2019,1412,1412.7,1415.3,1401.4,336.36,-0.24
+06/26/2019,1415.4,1427.2,1427.9,1405,421.95,-0.23
+06/25/2019,1418.7,1423.4,1442.9,1415.1,643.59,0.04
+06/24/2019,1418.2,1403.9,1425.1,1403.6,375.15,1.29
+06/21/2019,1400.1,1391.2,1415.4,1386.1,518.89,0.23
+06/20/2019,1396.9,1364.5,1397.7,1361.3,542.9,3.57
+06/19/2019,1348.8,1350.4,1366.6,1344.8,332.61,-0.14
+06/18/2019,1350.7,1343.9,1358.5,1342.1,376.27,0.58
+06/17/2019,1342.9,1345.5,1347.1,1336.6,238.71,-0.12
+06/14/2019,1344.5,1346.5,1362.2,1341.4,358.45,0.06
+06/13/2019,1343.7,1337.8,1347,1335.9,204.83,0.52
+06/12/2019,1336.8,1330.6,1342.3,1329.8,234.46,0.42
+06/11/2019,1331.2,1331.8,1333.8,1323.6,215.15,0.14
+06/10/2019,1329.3,1341.2,1341.7,1329,228.03,-1.25
+06/07/2019,1346.1,1339.7,1352.7,1334.3,331.29,0.25
+06/06/2019,1342.7,1336.1,1344.2,1331.3,263.09,0.68
+06/05/2019,1333.6,1330.2,1348.9,1329.3,413.47,0.37
+06/04/2019,1328.7,1329.7,1334.1,1324.7,319.96,0.06
+06/03/2019,1327.9,1312.5,1333,1310.9,363.4,1.28
+05/31/2019,1311.1,1293.2,1311.9,1292.5,341.18,1.45
+05/30/2019,1292.4,1285.1,1293.9,1279.2,284.02,0.89
+05/29/2019,1281,1278.9,1285.2,1278.4,189.69,0.07
+05/28/2019,1280.1,1287.2,1289.6,1278.5,0.78,0.23
+05/27/2019,1277.1,1283.5,1286.9,1275.1,362.16,-0.51
+05/24/2019,1283.6,1283.2,1284.7,1280.1,218.71,-0.14
+05/23/2019,1285.4,1273.6,1287.1,1272.1,330.16,0.88
+05/22/2019,1274.2,1274.4,1277.1,1272,191.37,0.08
+05/21/2019,1273.2,1277.7,1277.7,1269,213.17,-0.32
+05/20/2019,1277.3,1277.6,1278.8,1273.3,212.18,0.13
+05/17/2019,1275.7,1287.2,1289,1274.6,264.57,-0.82
+05/16/2019,1286.2,1296.9,1299.3,1284.2,282.07,-0.89
+05/15/2019,1297.8,1298.3,1301.7,1293.6,247.52,0.12
+05/14/2019,1296.3,1302,1302.6,1294.3,222.05,-0.42
+05/13/2019,1301.8,1288.4,1302.2,1282.4,379.44,1.12
+05/10/2019,1287.4,1285.1,1290.3,1284,238.64,0.17
+05/09/2019,1285.2,1282.9,1289.2,1280.4,306.55,0.30
+05/08/2019,1281.4,1287.4,1292.8,1280.2,302.69,-0.33
+05/07/2019,1285.6,1284.1,1287.3,1279.1,251.09,0.14
+05/06/2019,1283.8,1286.4,1286.4,1278.1,244.34,0.20
+05/03/2019,1281.3,1272.9,1283.9,1269,280.32,0.73
+05/02/2019,1272,1278.2,1278.4,1267.3,282.5,-0.95
+05/01/2019,1284.2,1284.2,1289.4,1274.5,275.43,-0.12
+04/30/2019,1285.7,1283.5,1288.2,1281.6,239.44,0.33
+04/29/2019,1281.5,1287,1288.6,1279.9,208.96,-0.57
+04/26/2019,1288.8,1280.1,1290.9,1276,278.89,0.71
+04/25/2019,1279.7,1276.3,1284.8,1275.4,237.15,0.02
+04/24/2019,1279.4,1272.3,1280.7,1270.5,246.05,0.49
+04/23/2019,1273.2,1277.2,1278.5,1267.9,280.34,-0.34
+04/22/2019,1277.6,1277.9,1281.9,1275.7,136.44,0.13
+04/18/2019,1276,1276.3,1279.7,1273,229.63,-0.06
+04/17/2019,1276.8,1278.7,1282.1,1275.2,223.36,-0.03
+04/16/2019,1277.2,1290,1290.3,1275.5,326.51,-1.09
+04/15/2019,1291.3,1293.2,1293.5,1285.3,232.99,-0.30
+04/12/2019,1295.2,1296.8,1299.1,1293.2,192.49,0.15
+04/11/2019,1293.3,1311.4,1312.1,1292.9,324.74,-1.57
+04/10/2019,1313.9,1307.6,1314.7,1304.7,218.88,0.43
+04/09/2019,1308.3,1303.2,1310.4,1301.1,200.34,0.49
+04/08/2019,1301.9,1297.6,1307.9,1297,207.57,0.49
+04/05/2019,1295.6,1295.8,1297.4,1288.3,231.45,0.10
+04/04/2019,1294.3,1296.3,1298.7,1284.9,262.54,-0.08
+04/03/2019,1295.3,1295.6,1299,1292.7,190.37,-0.01
+04/02/2019,1295.4,1292.7,1297.1,1289.5,196.4,0.09
+04/01/2019,1294.2,1295.9,1301.7,1291,236.66,-0.33
+03/29/2019,1298.5,1296.3,1304.6,1291.3,270.18,0.25
+03/28/2019,1295.3,1315.9,1317.6,1293.3,426.82,-1.15
+03/27/2019,1310.4,1316.7,1318.8,1307.3,206.26,-0.35
+03/26/2019,1315,1320.5,1321.9,1312.1,267.17,-0.57
+03/25/2019,1322.6,1313.2,1324.5,1312.6,251.98,0.78
+03/22/2019,1312.3,1308.2,1314.7,1307,271.38,0.38
+03/21/2019,1307.3,1316.1,1320.2,1302.8,332.61,0.43
+03/20/2019,1301.7,1304.3,1317.2,1298.1,370.4,-0.37
+03/19/2019,1306.5,1304.8,1310.8,1303.4,206.9,0.38
+03/18/2019,1301.5,1299.3,1306.7,1298,176.49,-0.11
+03/15/2019,1302.9,1295.4,1306.3,1293.7,234.65,0.60
+03/14/2019,1295.1,1308.1,1308.6,1292.5,248.21,-1.08
+03/13/2019,1309.3,1303.7,1311.6,1303.4,214.24,0.86
+03/12/2019,1298.1,1293.1,1302.6,1292.9,203.89,0.54
+03/11/2019,1291.1,1298.5,1299.2,1290.6,196.86,-0.63
+03/08/2019,1299.3,1286.8,1301.3,1286.5,283.84,1.03
+03/07/2019,1286.1,1288.6,1289.6,1280.8,257.92,-0.12
+03/06/2019,1287.6,1288.5,1291.8,1284.3,192.93,0.23
+03/05/2019,1284.7,1288.5,1290.6,1282,216.93,-0.22
+03/04/2019,1287.5,1297.4,1298.1,1283.8,268.39,-0.90
+03/01/2019,1299.2,1315.9,1315.9,1291.3,343.47,-1.28
+02/28/2019,1316.1,1319.6,1328.9,1314,252.24,-0.39
+02/27/2019,1321.2,1331,1331.1,1318.4,198.04,-0.55
+02/26/2019,1328.5,1329.9,1332.4,1325.5,185.56,-0.08
+02/25/2019,1329.5,1332.7,1334.9,1327.3,181.78,-0.25
+02/22/2019,1332.8,1327.2,1335.6,1323.8,241.8,0.38
+02/21/2019,1327.8,1340.5,1343.7,1323.3,285.81,-1.49
+02/20/2019,1347.9,1347.8,1349.8,1339.8,246.72,0.23
+02/19/2019,1344.8,1325,1345,1323.8,348.64,0.00
+02/18/2019,1344.8,1327.9,1345,1324.4,348.64,1.72
+02/15/2019,1322.1,1314.7,1325.8,1314.3,200.28,0.62
+02/14/2019,1313.9,1311.8,1317.4,1304.7,228.46,-0.09
+02/13/2019,1315.1,1315.2,1321.7,1308.1,213.96,0.08
+02/12/2019,1314,1311.4,1318.3,1310.7,146.45,0.16
+02/11/2019,1311.9,1318.1,1318.7,1307.1,150.61,-0.50
+02/08/2019,1318.5,1313.2,1319.5,1311.5,150.61,0.33
+02/07/2019,1314.2,1308.1,1315.8,1306.4,166.76,-0.02
+02/06/2019,1314.4,1317.6,1319.7,1309.6,137.25,-0.36
+02/05/2019,1319.2,1317.1,1321,1314.8,129.01,-0.01
+02/04/2019,1319.3,1319.6,1320.1,1312.7,159.56,-0.21
+02/01/2019,1322.1,1323,1328.2,1320.6,200,-0.23
+01/31/2019,1325.2,1323,1331.1,1322.6,224.75,0.74
+01/30/2019,1315.5,1318.4,1328.6,1313.5,272.11,0.50
+01/29/2019,1308.9,1302.2,1310.8,1302,213.61,0.45
+01/28/2019,1303.1,1301,1303.7,1296.5,243.07,0.39
+01/25/2019,1298.1,1279.2,1303.4,1278.9,303.84,1.43
+01/24/2019,1279.8,1283.6,1283.6,1275.3,225.77,-0.33
+01/23/2019,1284,1284.4,1286,1277.7,217.13,-0.14
+01/22/2019,1285.8,1284.5,1287.2,1279,1.27,0.19
+01/21/2019,1283.4,1282.4,1285,1276,318.85,0.06
+01/18/2019,1282.6,1290.4,1292,1280.1,225.57,-0.75
+01/17/2019,1292.3,1294.6,1295,1288.3,191.98,-0.12
+01/16/2019,1293.8,1289.1,1295.4,1287.6,181.39,0.42
+01/15/2019,1288.4,1293.1,1294.8,1286.5,242.07,-0.22
+01/14/2019,1291.3,1292.7,1296.6,1288.6,221.89,0.14
+01/11/2019,1289.5,1290.2,1295.7,1287.2,210.64,0.16
+01/10/2019,1287.4,1293.6,1298,1286.7,239.92,-0.36
+01/09/2019,1292,1287,1295,1280.9,245.97,0.47
+01/08/2019,1285.9,1287.4,1288.4,1280.2,221.92,-0.31
+01/07/2019,1289.9,1290.2,1297,1287.3,204.68,0.32
+01/04/2019,1285.8,1298.9,1300,1278.1,316.06,-0.70
+01/03/2019,1294.8,1290.4,1296.9,1286.4,244.54,0.83
+01/02/2019,1284.1,1285,1291,1280.6,235.33,0.22
diff --git a/The Effect of Economic News on Gold Prices Analysis/Dataset/sentiment_labeled_data.csv b/The Effect of Economic News on Gold Prices Analysis/Dataset/sentiment_labeled_data.csv
new file mode 100644
index 000000000..e680182aa
--- /dev/null
+++ b/The Effect of Economic News on Gold Prices Analysis/Dataset/sentiment_labeled_data.csv	
@@ -0,0 +1,1280 @@
+Date,Price,Vol_K,Change_percent,Country,Event,D_Consensus,D_Forecast,Sentiment
+2023-12-01,2089.7,241.62,1.58,US,ISM Manufacturing PMI ,1.8887722980062926,1.053740779768177,Positive
+2023-11-30,2057.2,151.92,-0.48,US,Core PCE Price Index MoM ,0.0,0.19900497512437815,Negative
+2023-11-29,2067.1,197.79,0.81,US,GDP Growth Rate QoQ 2nd Est,0.3629764065335743,0.5449591280653943,Positive
+2023-11-28,2050.5,1.86,1.35,,,1.097918675666989,1.4835862307477667,Neutral
+2023-11-27,2023.1,1.06,0.47,,,1.097918675666989,1.4835862307477667,Neutral
+2023-11-24,2013.7,0.52,0.95,,,1.097918675666989,1.4835862307477667,Neutral
+2023-11-23,1994.75,200.515,-0.43,JP,Inflation Rate YoY ,1.097918675666989,0.1877934272300471,Negative
+2023-11-22,2003.4,0.67,-0.43,US,Durable Goods Orders MoM ,5.027322404371584,5.664488017429194,Negative
+2023-11-21,2012.0,0.67,1.07,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Positive
+2023-11-20,1990.7,0.31,0.3,,,1.097918675666989,1.4835862307477667,Neutral
+2023-11-17,1984.7,133.12,-0.13,US,Building Permits Prel ,1.8796037592075254,1.8796037592075254,Negative
+2023-11-16,1987.3,186.81,1.17,,,1.097918675666989,1.4835862307477667,Neutral
+2023-11-15,1964.3,142.92,-0.11,US,PPI MoM ,1.2048192771084338,1.2048192771084338,Negative
+2023-11-14,1966.5,180.74,0.84,US,Core Inflation Rate MoM ,0.19900497512437815,0.19900497512437815,Positive
+2023-11-13,1950.2,183.7,0.65,,,1.097918675666989,1.4835862307477667,Neutral
+2023-11-10,1937.7,229.64,-1.63,US,Michigan Consumer Sentiment Prel ,5.275779376498808,6.050955414012746,Negative
+2023-11-09,1969.8,214.08,0.61,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Positive
+2023-11-08,1957.8,189.36,-0.8,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Negative
+2023-11-07,1973.5,218.95,-0.76,,,1.097918675666989,1.4835862307477667,Neutral
+2023-11-06,1988.6,146.28,-0.53,CA,Ivey PMI s.a ,1.1070110701107037,2.441314553990605,Negative
+2023-11-03,1999.2,222.19,0.29,US,Non Farm Payrolls ,18.12688821752266,23.46041055718475,Positive
+2023-11-02,1993.5,158.65,0.3,GB,BoE Interest Rate Decision,0.0,0.0,Positive
+2023-11-01,1987.5,197.63,-0.34,US,ISM Manufacturing PMI ,4.7569803516028895,5.761316872427978,Negative
+2023-10-31,1994.3,214.78,-0.56,EA,GDP Growth Rate QoQ Flash,0.20020020020020018,0.20020020020020018,Negative
+2023-10-30,2005.6,181.34,0.83,JP,BoJ Interest Rate Decision,0.0,0.0,Positive
+2023-10-27,1989.0,0.37,0.06,US,Core PCE Price Index MoM ,0.0,0.19900497512437815,Positive
+2023-10-26,1987.9,0.2,0.12,US,Durable Goods Orders MoM ,5.639097744360902,6.8052930056710785,Positive
+2023-10-25,1985.5,0.16,0.44,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Positive
+2023-10-24,1976.8,1.23,-0.07,GB,Unemployment Rate - Adjusted ,1.097918675666989,1.4835862307477667,Negative
+2023-10-23,1978.2,0.45,-0.81,,,1.097918675666989,1.4835862307477667,Neutral
+2023-10-20,1994.4,200.515,0.7,GB,Retail Sales MoM ,1.415571284125379,1.415571284125379,Positive
+2023-10-19,1980.5,264.82,0.62,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Positive
+2023-10-18,1968.3,270.05,1.68,US,Building Permits Prel ,1.172572011215913,0.6610729722857932,Positive
+2023-10-17,1935.7,165.06,0.07,US,Retail Sales MoM ,0.7920792079207921,0.7920792079207921,Positive
+2023-10-16,1934.3,182.82,-0.37,,,1.097918675666989,1.4835862307477667,Neutral
+2023-10-13,1941.5,312.99,3.11,US,Michigan Consumer Sentiment Prel ,6.402439024390248,7.575757575757576,Positive
+2023-10-12,1883.0,163.48,-0.23,US,Core Inflation Rate MoM ,0.0,0.0,Negative
+2023-10-11,1887.3,169.96,0.64,US,PPI MoM ,0.3968253968253968,0.1982160555004956,Positive
+2023-10-10,1875.3,157.34,0.59,,,1.097918675666989,1.4835862307477667,Neutral
+2023-10-09,1864.3,187.8,1.04,,,1.097918675666989,1.4835862307477667,Neutral
+2023-10-06,1845.2,231.02,0.73,US,Non Farm Payrolls ,65.48323471400394,76.38603696098562,Positive
+2023-10-05,1831.8,172.46,-0.16,CA,Ivey PMI s.a ,4.385128693994289,6.750241080038573,Negative
+2023-10-04,1834.8,195.05,-0.36,US,ISM Services PMI ,0.0,0.18467220683287425,Negative
+2023-10-03,1841.5,216.78,-0.31,US,JOLTs Job Openings ,8.346213292117453,10.515356585111919,Negative
+2023-10-02,1847.2,202.15,-1.01,US,ISM Manufacturing PMI ,2.4539877300613555,1.8348623853210984,Negative
+2023-09-29,1866.1,245.13,-0.67,US,Core PCE Price Index MoM ,0.19940179461615157,0.19940179461615157,Negative
+2023-09-28,1878.6,231.42,-0.65,US,GDP Growth Rate QoQ Final,0.0,0.0,Negative
+2023-09-27,1890.9,238.53,-1.51,US,Durable Goods Orders MoM ,1.4042126379137412,3.2388663967611335,Negative
+2023-09-26,1919.8,212.26,-0.87,,,1.097918675666989,1.4835862307477667,Neutral
+2023-09-25,1936.6,164.26,-0.46,,,1.097918675666989,1.4835862307477667,Neutral
+2023-09-22,1945.6,139.93,0.31,GB,Retail Sales MoM ,0.1982160555004956,0.0,Positive
+2023-09-21,1939.6,225.91,-1.4,GB,BoE Interest Rate Decision,0.4514672686230252,0.4514672686230252,Negative
+2023-09-20,1967.1,220.98,0.69,US,Fed Interest Rate Decision,0.0,0.0,Positive
+2023-09-19,1953.7,131.1,0.02,US,Building Permits Prel ,5.017561465127941,5.688396677573622,Positive
+2023-09-18,1953.4,138.03,0.37,,,1.097918675666989,1.4835862307477667,Neutral
+2023-09-15,1946.2,199.77,0.69,US,Michigan Consumer Sentiment Prel ,2.0319303338171135,3.3165104542177324,Positive
+2023-09-14,1932.8,201.74,0.02,US,PPI MoM ,0.5934718100890208,0.5934718100890208,Positive
+2023-09-13,1932.5,161.0,-0.13,US,Core Inflation Rate MoM ,0.19900497512437815,0.19900497512437815,Negative
+2023-09-12,1935.1,161.99,-0.62,GB,Unemployment Rate ,0.0,0.18433179723502194,Negative
+2023-09-11,1947.2,131.08,0.23,,,1.097918675666989,1.4835862307477667,Neutral
+2023-09-08,1942.7,138.69,0.01,CA,Unemployment Rate ,0.18001800180018018,0.3597122302158276,Positive
+2023-09-07,1942.5,117.17,-0.09,CA,Ivey PMI s.a ,8.293153326904527,10.731707317073171,Negative
+2023-09-06,1944.2,148.78,-0.43,US,ISM Services PMI ,3.7037037037037033,3.8924930491195573,Negative
+2023-09-05,1952.6,192.79,-0.54,,,1.097918675666989,1.4835862307477667,Neutral
+2023-09-04,1963.25,200.515,-0.17,,,1.097918675666989,1.4835862307477667,Neutral
+2023-09-03,1966.65,200.515,-0.02,,,1.097918675666989,1.4835862307477667,Neutral
+2023-09-01,1967.1,160.73,0.06,US,Non Farm Payrolls ,9.497206703910614,3.804347826086957,Positive
+2023-08-31,1965.9,133.71,-0.36,US,Core PCE Price Index MoM ,0.0,0.0,Negative
+2023-08-30,1973.0,142.38,0.4,US,GDP Growth Rate QoQ 2nd Est,0.5741626794258372,0.5741626794258372,Positive
+2023-08-29,1965.1,174.22,0.94,US,JOLTs Job Openings ,6.614140576404726,7.660978501830185,Positive
+2023-08-28,1946.8,115.55,0.36,,,1.097918675666989,1.4835862307477667,Neutral
+2023-08-25,1939.9,166.99,-0.37,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Negative
+2023-08-24,1947.1,137.39,-0.05,US,Durable Goods Orders MoM ,2.6431718061674,11.962224554039874,Negative
+2023-08-23,1948.1,170.04,1.15,,,1.097918675666989,1.4835862307477667,Neutral
+2023-08-22,1926.0,131.09,0.16,,,1.097918675666989,1.4835862307477667,Neutral
+2023-08-21,1923.0,138.11,0.34,,,1.097918675666989,1.4835862307477667,Neutral
+2023-08-18,1916.5,114.74,0.07,GB,Retail Sales MoM ,1.4242115971515767,1.8274111675126905,Positive
+2023-08-17,1915.2,152.33,-0.68,JP,Inflation Rate YoY ,1.5122873345935728,0.37593984962406046,Negative
+2023-08-16,1928.3,128.61,-0.36,US,Building Permits Prel ,1.07554417413573,0.7694280584765388,Negative
+2023-08-15,1935.2,167.15,-0.45,US,Retail Sales MoM ,0.5934718100890208,0.7920792079207921,Negative
+2023-08-14,1944.0,120.98,-0.13,JP,GDP Growth Annualized Prel,5.316223648029331,5.128205128205128,Negative
+2023-08-11,1946.6,122.32,-0.12,US,PPI MoM ,0.19900497512437815,0.19900497512437815,Negative
+2023-08-10,1948.9,168.26,-0.09,US,Core Inflation Rate MoM ,0.0,0.0,Negative
+2023-08-09,1950.6,139.26,-0.47,,,1.097918675666989,1.4835862307477667,Neutral
+2023-08-08,1959.9,142.34,-0.51,CN,Inflation Rate YoY ,0.2014098690835851,0.0,Negative
+2023-08-07,1970.0,104.41,-0.31,CN,Balance of Trade ,13.14060446780552,15.405046480743684,Negative
+2023-08-04,1976.1,156.42,0.37,US,Non Farm Payrolls ,6.701030927835052,1.5873015873015872,Positive
+2023-08-03,1968.8,141.35,-0.31,US,ISM Services PMI ,0.5623242736644745,1.3245033112582836,Negative
+2023-08-02,1975.0,169.66,-0.19,,,1.097918675666989,1.4835862307477667,Neutral
+2023-08-01,1978.8,167.76,-1.51,US,ISM Manufacturing PMI ,0.8492569002123113,3.3542976939203384,Negative
+2023-07-31,2009.2,139.96,0.47,EA,GDP Growth Rate QoQ Flash,0.19900497512437815,0.0,Positive
+2023-07-28,1999.9,159.6,1.76,US,Core PCE Price Index MoM ,0.0,0.0,Positive
+2023-07-27,1965.3,16.91,-1.23,US,Durable Goods Orders MoM ,7.000946073793755,7.787274453941122,Negative
+2023-07-26,1989.7,11.94,0.33,US,Fed Interest Rate Decision,0.0,0.0,Positive
+2023-07-25,1983.1,8.63,0.08,,,1.097918675666989,1.4835862307477667,Neutral
+2023-07-24,1981.6,6.44,0.76,,,1.097918675666989,1.4835862307477667,Neutral
+2023-07-21,1966.6,156.54,-0.22,GB,Retail Sales MoM ,0.9910802775024778,1.1904761904761905,Negative
+2023-07-20,1970.9,189.93,-0.5,JP,Inflation Rate YoY ,0.3745318352059928,0.0,Negative
+2023-07-19,1980.8,159.41,0.0,US,Building Permits Prel ,2.5445292620865163,1.1276268580215285,Neutral
+2023-07-18,1980.8,264.09,1.25,US,Retail Sales MoM ,0.595829195630586,0.19900497512437815,Positive
+2023-07-17,1956.4,165.83,-0.41,,,1.097918675666989,1.4835862307477667,Neutral
+2023-07-14,1964.4,209.31,0.03,US,Michigan Consumer Sentiment Prel ,10.20848310567936,11.730629978276603,Positive
+2023-07-13,1963.8,241.22,0.11,US,PPI MoM ,0.19940179461615157,0.0,Positive
+2023-07-12,1961.7,270.87,1.27,US,Core Inflation Rate MoM ,0.19900497512437815,0.19900497512437815,Positive
+2023-07-11,1937.1,189.37,0.32,GB,Unemployment Rate,0.3710575139146571,0.18535681186283615,Positive
+2023-07-10,1931.0,208.09,-0.08,,,1.097918675666989,1.4835862307477667,Neutral
+2023-07-07,1932.5,214.27,0.89,US,Non Farm Payrolls ,7.35632183908046,17.82608695652174,Positive
+2023-07-06,1915.4,231.51,-0.61,US,ISM Services PMI ,5.47686496694995,7.435653002859863,Negative
+2023-07-05,1927.1,245.93,-0.35,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Negative
+2023-07-04,1933.95,200.515,0.23,,,1.097918675666989,1.4835862307477667,Neutral
+2023-07-03,1929.5,152.96,0.01,US,ISM Manufacturing PMI ,2.127659574468085,4.2105263157894735,Positive
+2023-06-30,1929.4,180.69,0.6,US,Core PCE Price Index MoM,0.0,0.0,Positive
+2023-06-29,1917.9,205.25,0.24,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Positive
+2023-06-28,1913.4,0.63,-0.09,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Negative
+2023-06-27,1915.1,0.23,-0.52,US,Durable Goods Orders MoM,5.362462760675274,5.158730158730159,Negative
+2023-06-26,1925.1,0.77,0.21,EA,ECB President Lagarde Speech ,1.097918675666989,1.4835862307477667,Positive
+2023-06-23,1921.0,0.75,0.31,GB,Retail Sales MoM,0.9990009990009991,1.2,Positive
+2023-06-22,1915.0,0.37,-1.09,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Negative
+2023-06-21,1936.1,0.81,-0.14,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Negative
+2023-06-20,1938.9,0.74,-1.28,US,Building Permits Prel,3.6307849654819826,3.3707865168539355,Negative
+2023-06-19,1964.05,200.515,-0.27,,,1.097918675666989,1.4835862307477667,Neutral
+2023-06-18,1969.45,200.515,0.37,,,1.097918675666989,1.4835862307477667,Neutral
+2023-06-16,1962.2,0.62,0.02,US,Michigan Consumer Sentiment Prel ,6.244995996797435,4.932378679395388,Positive
+2023-06-15,1961.8,0.82,-0.36,US,Retail Sales MoM,0.7984031936127743,0.19900497512437815,Negative
+2023-06-14,1968.9,199.71,0.53,US,PPI MoM,0.4016064257028113,0.8016032064128256,Positive
+2023-06-13,1958.6,198.4,-0.56,US,Core Inflation Rate YoY,0.0,0.18066847335140035,Negative
+2023-06-12,1969.7,122.54,-0.38,,,1.097918675666989,1.4835862307477667,Neutral
+2023-06-09,1977.2,130.41,-0.07,CA,Unemployment Rate,0.18132366273798747,0.18132366273798747,Negative
+2023-06-08,1978.6,191.84,1.03,CN,Inflation Rate YoY,0.19900497512437815,0.0,Positive
+2023-06-07,1958.4,189.53,-1.17,US,Balance of Trade ,0.8064516129032372,4.74308300395258,Negative
+2023-06-06,1981.5,136.0,0.36,CA,Ivey PMI s.a,6.62488809310654,5.405405405405405,Positive
+2023-06-05,1974.3,179.99,0.24,US,ISM Services PMI,3.6714975845410738,4.050144648023147,Positive
+2023-06-02,1969.6,209.69,-1.3,US,Non Farm Payrolls,56.22641509433962,61.15384615384616,Negative
+2023-06-01,1995.5,176.91,0.68,US,ISM Manufacturing PMI,0.21074815595363838,2.2940563086548513,Positive
+2023-05-31,1982.1,207.75,0.25,US,JOLTs Job Openings ,7.110069342709247,8.895237157070389,Positive
+2023-05-30,1977.1,264.37,0.89,CN,NBS Manufacturing PMI,1.2096774193548419,2.0080321285140563,Positive
+2023-05-29,1959.75,200.515,-0.09,,,1.097918675666989,1.4835862307477667,Neutral
+2023-05-28,1961.5,200.515,-0.08,,,1.097918675666989,1.4835862307477667,Neutral
+2023-05-26,1963.1,130.07,1.03,,,1.097918675666989,1.4835862307477667,Neutral
+2023-05-25,1943.1,0.0,-1.0,,,1.097918675666989,1.4835862307477667,Neutral
+2023-05-24,1962.8,0.19,-0.49,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Negative
+2023-05-23,1972.4,0.0,-0.12,,,1.097918675666989,1.4835862307477667,Neutral
+2023-05-22,1974.8,0.01,-0.2,,,1.097918675666989,1.4835862307477667,Neutral
+2023-05-19,1978.7,0.11,1.13,,,1.097918675666989,1.4835862307477667,Neutral
+2023-05-18,1956.5,0.02,-1.22,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Negative
+2023-05-17,1980.7,0.01,-0.39,US,Building Permits Prel ,1.0900596937451406,0.7280291211648473,Negative
+2023-05-16,1988.4,0.05,-1.47,US,Retail Sales MoM ,0.7905138339920948,0.5934718100890208,Negative
+2023-05-15,2018.0,0.0,-0.09,,,1.097918675666989,1.4835862307477667,Neutral
+2023-05-12,2019.8,220.5,-0.03,,,1.097918675666989,1.4835862307477667,Neutral
+2023-05-11,2020.5,296.98,-0.81,US,PPI MoM ,0.19900497512437815,0.19940179461615157,Negative
+2023-05-10,2037.1,260.81,-0.28,US,Core Inflation Rate YoY ,0.0,0.18001800180018018,Negative
+2023-05-09,2042.9,199.7,0.48,,,1.097918675666989,1.4835862307477667,Neutral
+2023-05-08,2033.2,182.21,0.41,,,1.097918675666989,1.4835862307477667,Neutral
+2023-05-05,2024.8,283.3,-1.5,,,1.097918675666989,1.4835862307477667,Neutral
+2023-05-04,2055.7,311.0,0.92,US,Balance of Trade ,1.4229249011857796,1.741884402216946,Positive
+2023-05-03,2037.0,229.67,0.68,US,ISM Services PMI ,0.19102196752626824,0.7662835249042118,Positive
+2023-05-02,2023.3,245.64,1.56,US,JOLTs Job Openings ,1.8168426221458434,1.08427796944307,Positive
+2023-05-01,1992.2,173.02,-0.35,,,1.097918675666989,1.4835862307477667,Neutral
+2023-04-28,1999.1,172.45,0.01,US,Core PCE Price Index MoM ,0.0,0.198609731876862,Positive
+2023-04-27,1999.0,203.9,0.61,US,GDP Growth Rate QoQ Adv,1.7458777885548016,2.321083172147002,Positive
+2023-04-26,1986.9,0.62,-0.41,US,Durable Goods Orders MoM ,4.8123195380173245,5.009633911368016,Negative
+2023-04-25,1995.1,0.85,0.23,,,1.097918675666989,1.4835862307477667,Neutral
+2023-04-24,1990.6,0.54,0.47,,,1.097918675666989,1.4835862307477667,Neutral
+2023-04-21,1981.3,0.62,-1.42,GB,Retail Sales MoM ,0.8113590263691681,0.8113590263691681,Negative
+2023-04-20,2009.8,0.42,0.59,GB,Gfk Consumer Confidence ,15.625,12.698412698412698,Positive
+2023-04-19,1998.0,0.92,-0.61,GB,Inflation Rate YoY ,0.5004170141784825,0.16625103906899202,Negative
+2023-04-18,2010.3,0.22,0.81,US,Building Permits Prel ,1.9156096298213785,1.9156096298213785,Positive
+2023-04-17,1994.2,0.55,-0.4,CN,GDP Growth Rate YoY,0.9216589861751149,2.4141132776230267,Negative
+2023-04-14,2002.2,0.72,-1.92,US,Retail Sales MoM ,1.2170385395537524,0.2038735983690114,Negative
+2023-04-13,2041.3,1.04,1.51,US,PPI MoM ,1.0050251256281406,1.2048192771084338,Positive
+2023-04-12,2010.9,0.17,0.3,US,Core Inflation Rate YoY ,0.0,0.18001800180018018,Positive
+2023-04-11,2004.8,0.07,0.79,,,1.097918675666989,1.4835862307477667,Neutral
+2023-04-10,1989.1,0.65,-1.13,JP,Consumer Confidence ,5.9880239520958085,3.147353361945641,Negative
+2023-04-06,2011.9,0.49,-0.45,CA,Unemployment Rate ,0.18165304268846394,0.3629764065335743,Negative
+2023-04-05,2020.9,0.53,-0.06,US,Balance of Trade ,2.166064981949458,2.166064981949458,Negative
+2023-04-04,2022.2,0.81,1.93,US,JOLTs Job Openings ,4.397355960808225,7.997791173899052,Positive
+2023-04-03,1983.9,0.74,0.76,US,ISM Manufacturing PMI ,2.5316455696202596,5.607476635514025,Positive
+2023-03-31,1969.0,0.96,-0.57,US,Core PCE Price Index MoM ,0.198609731876862,0.5946481665014867,Negative
+2023-03-30,1980.3,10.12,0.68,CN,NBS Manufacturing PMI ,0.7662835249042118,1.344860710854939,Positive
+2023-03-29,1966.9,88.56,-0.33,,,1.097918675666989,1.4835862307477667,Neutral
+2023-03-28,1973.5,183.58,0.1,,,1.097918675666989,1.4835862307477667,Neutral
+2023-03-27,1971.5,107.04,-1.51,,,1.097918675666989,1.4835862307477667,Neutral
+2023-03-24,2001.7,118.69,-0.58,US,Durable Goods Orders MoM ,3.2128514056224904,3.410230692076229,Negative
+2023-03-23,2013.3,74.55,2.37,GB,BoE Interest Rate Decision,0.0,0.0,Positive
+2023-03-22,1966.6,60.53,0.42,US,Fed Interest Rate Decision,0.0,0.0,Positive
+2023-03-21,1958.3,65.17,-2.07,CA,Inflation Rate YoY ,0.3616636528028936,0.0,Negative
+2023-03-20,1999.7,69.06,0.48,,,1.097918675666989,1.4835862307477667,Neutral
+2023-03-17,1990.2,67.46,2.6,US,Michigan Consumer Sentiment Prel ,5.479452054794522,6.948640483383688,Positive
+2023-03-16,1939.7,34.77,-0.43,US,Building Permits Prel ,9.52380952380952,10.067462376751424,Negative
+2023-03-15,1948.1,84.73,1.95,US,PPI MoM ,0.7984031936127743,0.9970089730807579,Positive
+2023-03-14,1910.9,261.28,-0.29,US,Core Inflation Rate YoY ,0.0,0.18001800180018018,Negative
+2023-03-13,1916.5,452.33,2.64,US,President Biden Speech on Banking System ,1.097918675666989,1.4835862307477667,Positive
+2023-03-10,1867.2,345.81,1.78,US,Non Farm Payrolls ,41.005802707930364,38.69731800766284,Positive
+2023-03-09,1834.6,228.47,0.88,JP,BoJ Interest Rate Decision,0.0,0.0,Positive
+2023-03-08,1818.6,208.29,-0.08,US,Balance of Trade ,0.8810572687224796,1.0271460014673555,Negative
+2023-03-07,1820.0,248.23,-1.87,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Negative
+2023-03-06,1854.6,136.22,0.0,CA,Ivey PMI s.a ,7.926267281105985,6.319702602230482,Neutral
+2023-03-03,1854.6,158.96,0.77,US,ISM Non-Manufacturing PMI ,1.0849909584086825,0.9033423667570009,Positive
+2023-03-02,1840.5,139.76,-0.27,EA,Inflation Rate YoY Flash ,0.5141388174807203,0.17108639863130895,Negative
+2023-03-01,1845.4,182.58,0.47,US,ISM Manufacturing PMI ,0.6204756980351543,0.6204756980351543,Positive
+2023-02-28,1836.7,184.51,0.65,CA,GDP Growth Rate QoQ,1.097918675666989,0.796812749003984,Positive
+2023-02-27,1824.9,130.43,0.87,US,Durable Goods Orders MoM ,1.0928961748633874,2.17391304347826,Positive
+2023-02-24,1809.2,0.4,-0.53,US,Core PCE Price Index MoM ,0.39603960396039606,0.5946481665014867,Negative
+2023-02-23,1818.8,0.65,-0.79,GB,Gfk Consumer Confidence ,12.5,10.126582278481013,Negative
+2023-02-22,1833.3,0.57,-0.5,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Negative
+2023-02-21,1842.5,210.17,-0.43,CA,Inflation Rate YoY ,0.35714285714285743,0.0,Negative
+2023-02-20,1850.5,200.515,0.15,,,1.097918675666989,1.4835862307477667,Neutral
+2023-02-19,1847.75,200.515,0.4,,,1.097918675666989,1.4835862307477667,Neutral
+2023-02-17,1840.4,0.04,-0.09,GB,Retail Sales MoM ,1.5968063872255487,2.607823470411234,Negative
+2023-02-16,1842.0,0.22,0.43,US,Building Permits Prel ,0.596367579289787,1.8852679773767917,Positive
+2023-02-15,1834.2,0.37,-1.07,US,Retail Sales MoM ,2.2900763358778624,3.4548944337811895,Negative
+2023-02-14,1854.0,0.66,0.11,US,Core Inflation Rate YoY ,0.18001800180018018,0.3603603603603607,Positive
+2023-02-13,1851.9,0.57,-0.59,JP,GDP Growth Annualized Prel,2.729044834307992,1.9569471624266144,Negative
+2023-02-10,1862.8,0.03,-0.18,US,Michigan Consumer Sentiment Prel ,2.114803625377652,2.114803625377652,Negative
+2023-02-09,1866.2,0.22,-0.6,CN,Inflation Rate YoY ,0.19175455417066106,0.19212295869356408,Negative
+2023-02-08,1877.4,0.23,0.3,,,1.097918675666989,1.4835862307477667,Neutral
+2023-02-07,1871.7,0.3,0.29,US,Balance of Trade ,1.6308376575240833,2.071005917159751,Positive
+2023-02-06,1866.2,0.42,0.18,CA,Ivey PMI s.a ,34.429400386847206,39.762611275964396,Positive
+2023-02-03,1862.9,0.99,-2.79,US,Non Farm Payrolls ,94.45234708392604,92.37288135593221,Negative
+2023-02-02,1916.3,0.75,-0.6,EA,Deposit Facility Rate,0.0,0.0,Negative
+2023-02-01,1927.8,2.29,-0.09,US,ISM Manufacturing PMI ,1.2448132780083017,1.2448132780083017,Negative
+2023-01-31,1929.5,1.91,0.34,EA,GDP Growth Rate QoQ Flash,0.4,0.19980019980019983,Positive
+2023-01-30,1922.9,27.22,-0.71,CN,NBS Manufacturing PMI ,0.594648166501495,1.1928429423459275,Negative
+2023-01-27,1936.6,2.33,-0.05,US,Core PCE Price Index MoM ,0.0,0.398406374501992,Negative
+2023-01-26,1937.6,2.1,-0.65,US,Durable Goods Orders MoM ,5.735430157261795,6.307977736549166,Negative
+2023-01-25,1950.3,1.27,0.37,CA,BoC Interest Rate Decision,0.0,0.0,Positive
+2023-01-24,1943.1,1.08,0.36,,,1.097918675666989,1.4835862307477667,Neutral
+2023-01-23,1936.2,0.97,0.41,,,1.097918675666989,1.4835862307477667,Neutral
+2023-01-20,1928.2,165.27,0.22,GB,Retail Sales MoM ,3.015075376884422,2.6183282980866065,Positive
+2023-01-19,1923.9,214.25,0.89,US,Building Permits Prel ,2.162162162162164,3.7533512064343078,Positive
+2023-01-18,1907.0,218.97,-0.01,US,PPI MoM ,0.8048289738430584,0.8048289738430584,Negative
+2023-01-17,1907.2,0.71,-0.14,GB,Claimant Count Change ,1.097918675666989,20.163487738419615,Negative
+2023-01-16,1909.9,268.37,-0.52,CN,GDP Growth Rate YoY,2.101241642788921,2.6819923371647514,Negative
+2023-01-15,1919.9,200.515,-0.09,,,1.097918675666989,1.4835862307477667,Neutral
+2023-01-13,1921.7,247.88,1.21,US,Michigan Consumer Sentiment Prel ,6.5027755749405145,8.988764044943812,Positive
+2023-01-12,1898.8,265.17,1.06,US,Core Inflation Rate YoY ,0.0,0.1793721973094172,Positive
+2023-01-11,1878.9,222.25,0.13,CN,Inflation Rate YoY ,0.0,0.3853564547206169,Positive
+2023-01-10,1876.5,170.51,-0.07,,,1.097918675666989,1.4835862307477667,Neutral
+2023-01-09,1877.8,204.55,0.43,,,1.097918675666989,1.4835862307477667,Neutral
+2023-01-06,1869.7,215.37,1.58,US,Non Farm Payrolls ,10.849056603773585,1.3513513513513513,Positive
+2023-01-05,1840.6,188.6,-0.99,US,Balance of Trade ,17.228464419475657,15.849056603773585,Negative
+2023-01-04,1859.0,198.35,0.7,US,ISM Manufacturing PMI ,0.2042900919305443,1.219512195121954,Positive
+2023-01-03,1846.1,212.27,0.56,,,1.097918675666989,1.4835862307477667,Neutral
+2023-01-02,1835.8,200.515,0.53,CN,Caixin Manufacturing PMI ,0.4048582995951474,2.0408163265306123,Positive
+2022-12-30,1826.2,107.5,0.01,CN,NBS Manufacturing PMI ,2.083333333333333,5.128205128205128,Positive
+2022-12-29,1826.0,105.99,0.56,,,1.097918675666989,1.4835862307477667,Neutral
+2022-12-28,1815.8,118.08,-0.4,,,1.097918675666989,1.4835862307477667,Neutral
+2022-12-27,1823.1,159.62,0.74,,,1.097918675666989,1.4835862307477667,Neutral
+2022-12-26,1809.7,200.515,0.3,,,1.097918675666989,1.4835862307477667,Neutral
+2022-12-23,1804.2,105.46,0.5,US,Durable Goods Orders MoM ,3.083247687564235,3.285420944558522,Positive
+2022-12-22,1795.3,175.77,-1.65,JP,Inflation Rate YoY ,1.097918675666989,0.18570102135561764,Negative
+2022-12-21,1825.4,110.18,0.0,CA,Inflation Rate YoY ,0.17621145374449354,0.17621145374449354,Neutral
+2022-12-20,1825.4,197.5,1.54,US,Building Permits Prel ,7.473216618761433,7.2213500784929305,Positive
+2022-12-19,1797.7,86.09,-0.14,JP,BoJ Interest Rate Decision,0.0,0.0,Negative
+2022-12-16,1800.2,128.75,0.69,GB,Retail Sales MoM ,1.4014014014014013,1.4014014014014013,Positive
+2022-12-15,1787.8,185.32,-1.7,US,Retail Sales MoM ,1.0070493454179255,1.6064257028112452,Negative
+2022-12-14,1818.7,143.8,-0.37,US,Fed Interest Rate Decision,0.0,0.0,Negative
+2022-12-13,1825.5,230.91,1.85,US,Core Inflation Rate YoY ,0.17841213202497785,0.3565062388591804,Positive
+2022-12-12,1792.3,107.78,-1.02,GB,GDP MoM ,0.1982160555004956,0.1982160555004956,Negative
+2022-12-09,1810.7,150.94,0.51,US,PPI MoM ,0.19900497512437815,0.0,Positive
+2022-12-08,1801.5,116.27,0.19,CN,Inflation Rate YoY ,0.0,0.3868471953578333,Positive
+2022-12-07,1798.0,155.57,0.88,,,1.097918675666989,1.4835862307477667,Neutral
+2022-12-06,1782.4,127.86,0.06,US,Balance of Trade ,2.2900763358778593,6.924101198402134,Positive
+2022-12-05,1781.3,179.82,-1.56,US,ISM Non-Manufacturing PMI ,5.776173285198561,6.334841628959276,Negative
+2022-12-02,1809.6,183.72,-0.31,US,Non Farm Payrolls ,27.155172413793103,22.362869198312236,Negative
+2022-12-01,1815.2,226.15,3.14,US,Personal Income MoM ,0.5934718100890208,0.7920792079207921,Positive
+2022-11-30,1759.9,192.24,-0.22,US,JOLTs Job Openings ,0.3143200517703515,0.6073433330266008,Negative
+2022-11-29,1763.7,127.32,1.34,CN,NBS Manufacturing PMI ,2.0408163265306123,2.0408163265306123,Positive
+2022-11-28,1740.3,132.77,-0.78,,,1.097918675666989,1.4835862307477667,Neutral
+2022-11-25,1754.0,134.3,0.0,,,1.097918675666989,1.4835862307477667,Neutral
+2022-11-24,1754.0,134.3,0.48,,,1.097918675666989,1.4835862307477667,Neutral
+2022-11-23,1745.6,167.77,0.33,US,Durable Goods Orders MoM ,1.183431952662722,1.3820335636722607,Positive
+2022-11-22,1739.9,153.09,0.02,,,1.097918675666989,1.4835862307477667,Neutral
+2022-11-21,1739.6,166.08,-0.84,,,1.097918675666989,1.4835862307477667,Neutral
+2022-11-18,1754.4,137.33,-0.49,GB,Retail Sales MoM ,0.5946481665014867,1.393034825870647,Negative
+2022-11-17,1763.0,169.1,-0.72,US,Building Permits Prel ,1.097918675666989,3.0568779754447477,Negative
+2022-11-16,1775.8,200.76,-0.06,US,Retail Sales MoM ,0.5865102639296187,0.7827788649706457,Negative
+2022-11-15,1776.8,283.02,-0.01,US,PPI MoM ,0.3976143141153082,0.19900497512437815,Negative
+2022-11-14,1776.9,191.35,0.42,CN,Industrial Production YoY ,0.3629764065335743,1.0849909584086797,Positive
+2022-11-11,1769.4,227.04,0.9,US,Michigan Consumer Sentiment Prel ,8.333333333333329,7.99999999999999,Positive
+2022-11-10,1753.7,305.72,2.33,US,Core Inflation Rate YoY ,0.3546099290780145,0.7079646017699122,Positive
+2022-11-09,1713.7,239.65,-0.13,,,1.097918675666989,1.4835862307477667,Neutral
+2022-11-08,1716.0,297.62,2.11,CN,Inflation Rate YoY ,0.5741626794258372,0.9551098376313272,Positive
+2022-11-07,1680.5,187.59,0.23,,,1.097918675666989,1.4835862307477667,Neutral
+2022-11-04,1676.6,293.52,2.8,US,Non Farm Payrolls ,26.406926406926406,8.366533864541832,Positive
+2022-11-03,1630.9,254.7,-1.16,US,Balance of Trade ,1.5224913494809609,1.8018018018017976,Negative
+2022-11-02,1650.0,220.93,0.02,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Positive
+2022-11-01,1649.7,197.98,0.55,US,ISM Manufacturing PMI ,0.39525691699605303,0.19743336623889712,Positive
+2022-10-31,1640.7,128.41,-0.25,EA,Inflation Rate YoY Flash ,0.8271298593879246,0.49545829892650745,Negative
+2022-10-28,1644.8,196.36,-1.25,US,Personal Income MoM ,0.198609731876862,0.3976143141153082,Negative
+2022-10-27,1665.6,189.29,-0.22,US,Durable Goods Orders MoM ,0.39603960396039606,0.3976143141153082,Negative
+2022-10-26,1669.2,186.93,0.68,CA,BoC Monetary Policy Report,1.097918675666989,1.4835862307477667,Positive
+2022-10-25,1658.0,182.8,0.24,,,1.097918675666989,1.4835862307477667,Neutral
+2022-10-24,1654.1,171.02,-0.13,,,1.097918675666989,1.4835862307477667,Neutral
+2022-10-21,1656.3,271.1,1.19,GB,Retail Sales MoM ,1.834862385321101,2.238046795523906,Positive
+2022-10-20,1636.8,163.73,0.16,GB,Gfk Consumer Confidence ,10.204081632653061,12.121212121212121,Positive
+2022-10-19,1634.2,179.25,-1.3,US,Building Permits ,1.6609672691744028,3.801530486299677,Negative
+2022-10-18,1655.8,163.17,-0.49,CN,20th National Congress of the Chinese Communist Party,1.097918675666989,1.4835862307477667,Negative
+2022-10-17,1664.0,148.89,0.92,GB,Chancellor Jeremy Hunt Statement,1.097918675666989,1.4835862307477667,Positive
+2022-10-14,1648.9,183.17,-1.68,US,Retail Sales MoM ,0.39920159680638717,0.39920159680638717,Negative
+2022-10-13,1677.0,237.01,-0.03,US,Core Inflation Rate YoY ,0.17683465959328046,0.3539823008849561,Negative
+2022-10-12,1677.5,131.77,-0.5,US,PPI MoM ,0.3976143141153082,0.796812749003984,Negative
+2022-10-11,1686.0,171.81,0.64,GB,Claimant Count Change ,1.097918675666989,84.93150684931507,Positive
+2022-10-10,1675.2,157.15,-1.99,,,1.097918675666989,1.4835862307477667,Neutral
+2022-10-07,1709.3,157.45,-0.67,US,Non Farm Payrolls ,5.058365758754864,9.747292418772563,Negative
+2022-10-06,1720.8,139.44,0.0,CA,Ivey PMI s.a ,1.097918675666989,7.792207792207792,Neutral
+2022-10-05,1720.8,173.22,-0.56,US,Balance of Trade ,0.4474272930648726,0.8928571428571344,Negative
+2022-10-04,1730.5,205.08,1.67,US,JOLTs Job Openings ,6.615356422943004,9.452444364194456,Positive
+2022-10-03,1702.0,215.49,1.79,US,ISM Manufacturing PMI ,2.4975984630163386,3.816793893129771,Positive
+2022-09-30,1672.0,179.99,0.2,US,Personal Income MoM ,0.0,0.19900497512437815,Positive
+2022-09-29,1668.6,201.96,-0.08,CN,NBS Manufacturing PMI ,0.9930486593843099,0.594648166501495,Negative
+2022-09-28,1670.0,279.82,2.07,,,1.097918675666989,1.4835862307477667,Neutral
+2022-09-27,1636.2,197.06,0.17,US,Durable Goods Orders MoM ,0.4024144869215292,1.415571284125379,Positive
+2022-09-26,1633.4,219.86,-1.34,,,1.097918675666989,1.4835862307477667,Neutral
+2022-09-23,1655.6,243.05,-1.52,,,1.097918675666989,1.4835862307477667,Neutral
+2022-09-22,1681.1,241.28,0.32,GB,Gfk Consumer Confidence ,15.555555555555555,33.734939759036145,Positive
+2022-09-21,1675.7,227.94,0.28,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Positive
+2022-09-20,1671.1,143.93,-0.42,US,Building Permits ,4.50690574267023,5.449722691102001,Negative
+2022-09-19,1678.2,141.17,-0.31,JP,Inflation Rate YoY ,1.097918675666989,0.7575757575757576,Negative
+2022-09-16,1683.5,217.23,0.37,US,Michigan Consumer Sentiment Prel ,0.8298755186721992,1.5113350125944562,Positive
+2022-09-15,1677.3,268.09,-1.86,US,Retail Sales MoM ,0.5982053838484547,0.398406374501992,Negative
+2022-09-14,1709.1,163.29,-0.48,US,PPI MoM ,0.0,0.4,Negative
+2022-09-13,1717.4,232.7,-1.33,US,Core Inflation Rate YoY ,0.35587188612099674,0.7130124777183608,Negative
+2022-09-12,1740.6,154.37,0.69,GB,GDP MoM ,0.3976143141153082,0.19940179461615157,Positive
+2022-09-09,1728.6,154.71,0.49,,,1.097918675666989,1.4835862307477667,Neutral
+2022-09-08,1720.2,184.18,-0.44,CN,Inflation Rate YoY ,0.5698005698005697,0.7590132827324478,Negative
+2022-09-07,1727.8,173.62,1.17,US,Balance of Trade ,0.5714285714285796,1.0021474588403765,Positive
+2022-09-06,1707.9,0.02,-0.29,US,ISM Non-Manufacturing PMI ,3.185840707964597,3.365810451727189,Negative
+2022-09-05,1712.9,206.27,-0.33,GB,S&P Global/CIPS UK Services PMI Final ,3.065134099616861,3.065134099616861,Negative
+2022-09-04,1718.65,200.515,-0.23,,,1.097918675666989,1.4835862307477667,Neutral
+2022-09-02,1722.6,174.68,0.78,US,Non Farm Payrolls ,4.870129870129871,1.5974440894568689,Positive
+2022-09-01,1709.3,198.62,-0.98,US,ISM Manufacturing PMI ,1.5122873345935675,1.5122873345935675,Negative
+2022-08-31,1726.2,176.73,-0.58,EA,Inflation Rate YoY Flash ,0.16934801016088075,0.0,Negative
+2022-08-30,1736.3,130.66,-0.77,US,JOLTs Job Openings ,6.954912071929141,6.499846079423024,Negative
+2022-08-29,1749.7,156.22,-0.01,,,1.097918675666989,1.4835862307477667,Neutral
+2022-08-26,1749.8,176.9,-1.22,US,Personal Income MoM ,0.7936507936507936,0.595829195630586,Negative
+2022-08-25,1771.4,117.57,0.56,,,1.097918675666989,1.4835862307477667,Neutral
+2022-08-24,1761.5,112.65,0.02,US,Durable Goods Orders MoM ,1.1928429423459244,1.5873015873015872,Positive
+2022-08-23,1761.2,145.26,0.73,GB,S&P Global/CIPS Manufacturing PMI Flash ,10.397553516819576,10.783316378433362,Positive
+2022-08-22,1748.4,142.86,-0.82,,,1.097918675666989,1.4835862307477667,Neutral
+2022-08-19,1762.9,138.7,-0.47,GB,Retail Sales MoM ,0.9990009990009991,0.7984031936127743,Negative
+2022-08-18,1771.2,124.32,-0.31,GB,Gfk Consumer Confidence ,4.705882352941177,2.3255813953488373,Negative
+2022-08-17,1776.7,137.83,-0.73,US,Retail Sales MoM ,0.19980019980019983,0.39920159680638717,Negative
+2022-08-16,1789.7,94.4,-0.47,US,Building Permits ,1.1100832562442193,0.18416206261510146,Negative
+2022-08-15,1798.1,137.77,-0.96,,,1.097918675666989,1.4835862307477667,Neutral
+2022-08-12,1815.5,118.65,0.46,US,Michigan Consumer Sentiment Prel ,4.788213627992636,7.076350093109878,Positive
+2022-08-11,1807.2,121.26,-0.36,US,PPI MoM ,1.4042126379137412,1.801801801801802,Negative
+2022-08-10,1813.7,154.59,0.08,US,Core Inflation Rate YoY ,0.35714285714285743,0.0,Positive
+2022-08-09,1812.3,120.51,0.39,CN,Inflation Rate YoY ,0.3787878787878791,0.3802281368821289,Positive
+2022-08-08,1805.2,103.68,0.78,,,1.097918675666989,1.4835862307477667,Neutral
+2022-08-05,1791.2,168.9,-0.87,US,Non Farm Payrolls ,71.37355584082157,58.119658119658126,Negative
+2022-08-04,1806.9,153.29,1.72,US,Balance of Trade ,0.6301197227473221,4.207920792079215,Positive
+2022-08-03,1776.4,151.73,-0.74,US,ISM Non-Manufacturing PMI ,5.7553956834532425,7.622504537205087,Negative
+2022-08-02,1789.7,174.17,0.11,US,JOLTs Job Openings ,2.661027403295441,2.661027403295441,Positive
+2022-08-01,1787.7,133.74,0.33,US,ISM Manufacturing PMI ,1.5122873345935675,1.1320754716981025,Positive
+2022-07-29,1781.8,136.89,0.71,US,Personal Income MoM ,0.1978239366963403,0.1978239366963403,Positive
+2022-07-28,1769.2,192.86,2.91,,,1.097918675666989,1.4835862307477667,Neutral
+2022-07-27,1719.1,144.87,0.08,US,Durable Goods Orders MoM ,4.733727810650888,4.330708661417323,Positive
+2022-07-26,1717.7,147.37,-0.08,,,1.097918675666989,1.4835862307477667,Neutral
+2022-07-25,1719.1,160.72,-0.48,,,1.097918675666989,1.4835862307477667,Neutral
+2022-07-22,1727.4,200.62,0.82,GB,Retail Sales MoM ,0.4016064257028113,0.20060180541624875,Positive
+2022-07-21,1713.4,248.88,0.78,GB,Gfk Consumer Confidence ,2.4390243902439024,7.142857142857142,Positive
+2022-07-20,1700.2,174.47,-0.61,GB,Inflation Rate YoY ,0.1684919966301602,0.16820857863751065,Negative
+2022-07-19,1710.7,131.77,0.03,US,Building Permits ,1.6147635524798218,0.22909507445590446,Positive
+2022-07-18,1710.2,157.54,0.39,,,1.097918675666989,1.4835862307477667,Neutral
+2022-07-15,1703.6,176.8,-0.13,US,Retail Sales MoM ,0.3929273084479371,0.9852216748768474,Negative
+2022-07-14,1705.8,266.35,-1.71,US,PPI MoM ,0.5888125613346418,0.39215686274509803,Negative
+2022-07-13,1735.5,300.55,0.62,US,Core Inflation Rate YoY ,0.3584229390680994,0.17905102954341878,Positive
+2022-07-12,1724.8,255.17,-0.4,,,1.097918675666989,1.4835862307477667,Neutral
+2022-07-11,1731.7,171.9,-0.61,,,1.097918675666989,1.4835862307477667,Neutral
+2022-07-08,1742.3,189.18,0.15,US,Non Farm Payrolls ,32.44929797191888,21.39673105497771,Positive
+2022-07-07,1739.7,151.26,0.18,US,Balance of Trade,0.708382526564338,0.5865102639296188,Positive
+2022-07-06,1736.5,258.82,-1.83,US,ISM Non-Manufacturing PMI ,1.8083182640144666,0.17937219730940684,Negative
+2022-07-05,1768.9,1.33,0.28,GB,S&P Global/CIPS UK Services PMI Final ,1.6559337626494914,1.6559337626494914,Positive
+2022-07-04,1763.9,310.37,-2.09,,,1.097918675666989,1.4835862307477667,Neutral
+2022-07-01,1801.5,249.49,-0.32,US,ISM Manufacturing PMI ,3.489439853076214,3.669724770642202,Negative
+2022-06-30,1807.3,208.9,-0.56,US,Personal Income MoM,0.0,0.3968253968253968,Negative
+2022-06-29,1817.5,155.54,-0.2,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Negative
+2022-06-28,1821.2,111.4,-0.2,EA,ECB Forum on Central Banking,1.097918675666989,1.4835862307477667,Negative
+2022-06-27,1824.8,143.82,-0.3,US,Durable Goods Orders MoM,1.1904761904761905,1.9920318725099602,Negative
+2022-06-24,1830.3,139.72,0.03,GB,Retail Sales MoM,0.4048582995951417,0.4032258064516129,Positive
+2022-06-23,1829.8,167.07,-0.47,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Negative
+2022-06-22,1838.4,149.55,-0.02,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Negative
+2022-06-21,1838.8,176.3,0.0,,,1.097918675666989,1.4835862307477667,Neutral
+2022-06-20,1838.8,176.3,-0.1,,,1.097918675666989,1.4835862307477667,Neutral
+2022-06-17,1840.6,141.72,-0.5,,,1.097918675666989,1.4835862307477667,Neutral
+2022-06-16,1849.9,180.89,1.67,US,Building Permits,4.017857142857136,4.236343366778148,Positive
+2022-06-15,1819.6,203.42,0.34,US,Retail Sales MoM,1.001001001001001,1.2,Positive
+2022-06-14,1813.5,165.15,-1.0,US,PPI MoM,0.0,0.1970443349753695,Negative
+2022-06-13,1831.8,252.54,-2.33,GB,GDP MoM ,0.8016032064128256,0.6018054162487463,Negative
+2022-06-10,1875.5,267.2,1.23,US,Core Inflation Rate YoY,0.1787310098302057,0.0,Positive
+2022-06-09,1852.8,131.29,-0.2,CN,Inflation Rate YoY,0.19175455417066106,0.19212295869356408,Negative
+2022-06-08,1856.5,114.14,0.24,CN,Balance of Trade,30.13937282229966,44.327990135635034,Positive
+2022-06-07,1852.1,119.21,0.46,US,Balance of Trade ,2.7334851936218745,4.404291360813106,Positive
+2022-06-06,1843.7,103.18,-0.35,,,1.097918675666989,1.4835862307477667,Neutral
+2022-06-03,1850.2,115.34,-1.13,US,Non Farm Payrolls,18.156424581005588,19.69057665260197,Negative
+2022-06-02,1871.4,127.47,1.23,,,1.097918675666989,1.4835862307477667,Neutral
+2022-06-01,1848.7,158.04,0.02,US,ISM Manufacturing PMI,2.8673835125448055,2.3235031277926796,Positive
+2022-05-31,1848.4,201.8,0.0,EA,Inflation Rate YoY Flash,0.6908462867012096,0.8643042350907527,Neutral
+2022-05-30,1848.4,201.8,-0.48,,,1.097918675666989,1.4835862307477667,Neutral
+2022-05-27,1857.3,123.76,0.53,,,1.097918675666989,1.4835862307477667,Neutral
+2022-05-26,1847.6,123.36,0.07,,,1.097918675666989,1.4835862307477667,Neutral
+2022-05-25,1846.3,182.82,-1.02,US,Durable Goods Orders MoM ,0.39603960396039606,0.0,Negative
+2022-05-24,1865.4,174.76,0.95,GB,S&P Global/CIPS Manufacturing PMI Flash,0.7233273056057841,1.0830324909747315,Positive
+2022-05-23,1847.8,163.27,0.31,,,1.097918675666989,1.4835862307477667,Neutral
+2022-05-20,1842.1,143.05,0.05,,,1.097918675666989,1.4835862307477667,Neutral
+2022-05-19,1841.2,175.24,1.39,GB,Gfk Consumer Confidence,2.564102564102564,0.0,Positive
+2022-05-18,1815.9,150.35,-0.16,US,Building Permits ,0.30231051608723364,0.04311273981462004,Negative
+2022-05-17,1818.9,137.29,0.27,US,Retail Sales MoM ,0.0,0.5911330049261082,Positive
+2022-05-16,1814.0,159.49,0.32,,,1.097918675666989,1.4835862307477667,Neutral
+2022-05-13,1808.2,179.48,-0.9,,,1.097918675666989,1.4835862307477667,Neutral
+2022-05-12,1824.6,255.61,-1.57,US,PPI MoM ,0.0,0.0,Negative
+2022-05-11,1853.7,243.56,0.69,US,Core Inflation Rate YoY ,0.3565062388591804,0.0,Positive
+2022-05-10,1841.0,260.81,-0.95,CN,Inflation Rate YoY ,0.5774783445620795,0.5774783445620795,Negative
+2022-05-09,1858.6,218.82,-1.29,,,1.097918675666989,1.4835862307477667,Neutral
+2022-05-06,1882.8,194.28,0.38,,,1.097918675666989,1.4835862307477667,Neutral
+2022-05-05,1875.7,218.39,0.37,,,1.097918675666989,1.4835862307477667,Neutral
+2022-05-04,1868.8,161.48,-0.1,US,Balance of Trade ,2.5949953660797007,17.729083665338642,Negative
+2022-05-03,1870.6,167.43,0.38,US,JOLTs Job Openings ,4.662618370206799,2.342667618287921,Positive
+2022-05-02,1863.6,193.83,-2.52,,,1.097918675666989,1.4835862307477667,Neutral
+2022-04-29,1911.7,177.14,1.08,US,Personal Income MoM ,0.1982160555004956,0.1982160555004956,Positive
+2022-04-28,1891.3,170.91,0.14,,,1.097918675666989,1.4835862307477667,Neutral
+2022-04-27,1888.7,178.2,-0.81,,,1.097918675666989,1.4835862307477667,Neutral
+2022-04-26,1904.1,166.2,0.43,US,Durable Goods Orders MoM ,0.3929273084479371,0.5888125613346418,Positive
+2022-04-25,1896.0,231.49,-1.98,,,1.097918675666989,1.4835862307477667,Neutral
+2022-04-22,1934.3,176.68,-0.71,GB,Retail Sales MoM ,2.238046795523906,2.639593908629442,Negative
+2022-04-21,1948.2,154.92,-0.38,GB,Gfk Consumer Confidence ,14.285714285714285,14.285714285714285,Negative
+2022-04-20,1955.6,139.51,-0.17,CA,Inflation Rate YoY ,1.0638297872340434,1.2422360248447217,Negative
+2022-04-19,1959.0,181.44,-1.38,US,Building Permits ,2.043422733077907,2.690582959641253,Negative
+2022-04-18,1986.4,138.13,0.58,,,1.097918675666989,1.4835862307477667,Neutral
+2022-04-14,1974.9,139.42,-0.49,US,Retail Sales MoM ,0.1978239366963403,0.1982160555004956,Negative
+2022-04-13,1984.7,132.03,0.44,US,PPI MoM ,0.5853658536585369,0.78125,Positive
+2022-04-12,1976.1,172.39,1.43,US,Core Inflation Rate YoY ,0.17683465959328046,0.3533568904593642,Positive
+2022-04-11,1948.2,184.39,0.13,GB,GDP MoM ,0.398406374501992,0.7952286282306164,Positive
+2022-04-08,1945.6,142.5,0.4,JP,Consumer Confidence ,1.097918675666989,3.5398230088495657,Positive
+2022-04-07,1937.8,122.81,0.76,,,1.097918675666989,1.4835862307477667,Neutral
+2022-04-06,1923.1,153.97,-0.23,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Negative
+2022-04-05,1927.5,147.26,-0.34,US,Balance of Trade ,0.7923033389926462,1.3620885357548274,Negative
+2022-04-04,1934.0,108.44,0.54,,,1.097918675666989,1.4835862307477667,Neutral
+2022-04-01,1923.7,135.15,-1.55,US,Non Farm Payrolls ,12.79826464208243,6.502242152466367,Negative
+2022-03-31,1954.0,155.3,0.77,US,Personal Income MoM ,0.0,0.1978239366963403,Positive
+2022-03-30,1939.0,136.04,1.4,CN,NBS Manufacturing PMI ,0.7968127490039812,0.8032128514056196,Positive
+2022-03-29,1912.2,128.05,-1.42,US,JOLTs Job Openings ,2.286598469870197,1.4208679277582843,Negative
+2022-03-28,1939.8,181.37,-0.74,,,1.097918675666989,1.4835862307477667,Neutral
+2022-03-25,1954.2,147.9,-0.41,GB,Retail Sales MoM ,1.7946161515453645,1.9920318725099602,Negative
+2022-03-24,1962.2,181.2,1.29,US,Durable Goods Orders MoM ,3.494347379239465,3.494347379239465,Positive
+2022-03-23,1937.3,153.31,0.82,GB,Inflation Rate YoY ,0.5352363960749336,0.17809439002671432,Positive
+2022-03-22,1921.5,153.28,-0.41,,,1.097918675666989,1.4835862307477667,Neutral
+2022-03-21,1929.5,146.41,0.01,,,1.097918675666989,1.4835862307477667,Neutral
+2022-03-18,1929.3,150.88,-0.72,,,1.097918675666989,1.4835862307477667,Neutral
+2022-03-17,1943.2,149.83,1.78,US,Building Permits ,0.3822467615204883,0.04238186056368349,Positive
+2022-03-16,1909.2,195.46,-1.06,US,Retail Sales MoM ,0.198609731876862,0.7920792079207921,Negative
+2022-03-15,1929.7,220.37,-1.59,US,PPI MoM ,0.19665683382497526,0.5888125613346418,Negative
+2022-03-14,1960.8,162.2,-1.22,CN,Industrial Production YoY JAN-FEB,6.463195691202872,6.64869721473495,Negative
+2022-03-11,1985.0,262.09,-0.77,US,Michigan Consumer Sentiment Prel ,2.784602784602778,3.7489812550937196,Negative
+2022-03-10,2000.4,303.27,0.61,US,Core Inflation Rate YoY ,0.0,0.0,Positive
+2022-03-09,1988.2,360.35,-2.7,US,JOLTs Job Openings ,2.9153010177678036,4.01508910375926,Negative
+2022-03-08,2043.3,447.65,2.37,US,Balance of Trade ,2.957906712172933,6.601042269832083,Positive
+2022-03-07,1995.9,372.19,1.49,,,1.097918675666989,1.4835862307477667,Neutral
+2022-03-04,1966.6,241.53,1.59,US,Non Farm Payrolls ,51.52919369786839,63.751214771622934,Positive
+2022-03-03,1935.9,180.21,0.71,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Positive
+2022-03-02,1922.3,227.98,-1.11,EA,Inflation Rate YoY Flash ,0.7194244604316552,1.081081081081082,Negative
+2022-03-01,1943.8,224.0,2.27,US,ISM Manufacturing PMI ,1.0204081632653086,0.8496176720475787,Positive
+2022-02-28,1900.7,249.27,0.69,CN,NBS Manufacturing PMI ,0.5934718100890292,0.39370078740156644,Positive
+2022-02-25,1887.6,229.78,-2.01,US,Durable Goods Orders MoM ,1.5625,2.3529411764705883,Negative
+2022-02-24,1926.3,423.05,0.83,GB,Gfk Consumer Confidence ,37.2093023255814,48.78048780487805,Positive
+2022-02-23,1910.4,154.84,0.16,,,1.097918675666989,1.4835862307477667,Neutral
+2022-02-22,1907.4,334.59,0.0,,,1.097918675666989,1.4835862307477667,Neutral
+2022-02-21,1907.4,334.59,0.4,GB,Markit/CIPS Manufacturing PMI Flash ,0.17316017316016333,0.5176876617774017,Positive
+2022-02-18,1899.8,161.75,-0.12,GB,Retail Sales MoM ,1.749271137026239,1.9455252918287937,Negative
+2022-02-17,1902.0,268.55,1.63,US,Building Permits ,5.966945696501396,4.6491789294092545,Positive
+2022-02-16,1871.5,141.49,0.82,US,Retail Sales MoM ,3.402646502835539,4.368471035137702,Positive
+2022-02-15,1856.2,214.88,-0.71,GB,Claimant Count Change ,13.242784380305597,16.925734024179615,Negative
+2022-02-14,1869.4,231.02,1.48,,,1.097918675666989,1.4835862307477667,Neutral
+2022-02-11,1842.1,239.09,0.26,US,Michigan Consumer Sentiment Prel ,8.909370199692777,8.909370199692777,Positive
+2022-02-10,1837.4,227.46,0.04,US,Core Inflation Rate YoY ,0.1787310098302057,0.5371530886302589,Positive
+2022-02-09,1836.6,136.72,0.48,,,1.097918675666989,1.4835862307477667,Neutral
+2022-02-08,1827.9,142.41,0.33,US,Balance of Trade ,2.8272894898586323,3.069367710251688,Positive
+2022-02-07,1821.8,139.81,0.77,,,1.097918675666989,1.4835862307477667,Neutral
+2022-02-04,1807.8,177.71,0.21,US,Non Farm Payrolls ,102.58899676375404,175.50200803212851,Positive
+2022-02-03,1804.1,173.72,-0.34,US,ISM Non-Manufacturing PMI ,0.6644518272425225,1.8047579983593132,Negative
+2022-02-02,1810.3,123.02,0.49,EA,Inflation Rate YoY Flash ,1.278538812785388,1.0948905109489049,Positive
+2022-02-01,1801.5,128.88,0.28,US,ISM Manufacturing PMI ,0.17226528854436077,0.6861063464837025,Positive
+2022-01-31,1796.4,139.42,0.55,JP,Consumer Confidence ,1.097918675666989,7.253886010362686,Positive
+2022-01-28,1786.6,217.15,-0.36,US,Personal Income MoM ,0.3968253968253968,0.3968253968253968,Negative
+2022-01-27,1793.1,196.04,-2.0,US,Durable Goods Orders MoM ,0.8113590263691681,1.415571284125379,Negative
+2022-01-26,1829.7,270.03,-1.23,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Negative
+2022-01-25,1852.5,197.8,0.59,,,1.097918675666989,1.4835862307477667,Neutral
+2022-01-24,1841.7,244.33,0.54,US,Markit Composite PMI Flash ,1.097918675666989,10.87557603686637,Positive
+2022-01-21,1831.8,225.25,-0.59,GB,Retail Sales MoM ,6.478578892371996,6.478578892371996,Negative
+2022-01-20,1842.6,233.86,-0.03,GB,Gfk Consumer Confidence ,24.242424242424242,5.555555555555555,Negative
+2022-01-19,1843.2,318.49,1.6,US,Building Permits ,7.520769567118493,6.66231221423906,Positive
+2022-01-18,1814.1,0.34,0.09,GB,Claimant Count Change ,1.097918675666989,18.64623243933588,Positive
+2022-01-17,1812.4,362.94,-0.23,,,1.097918675666989,1.4835862307477667,Neutral
+2022-01-14,1816.5,174.94,-0.27,US,Retail Sales MoM ,3.873598369011213,4.471544715447155,Negative
+2022-01-13,1821.4,215.52,-0.32,CN,Exports YoY ,1.277501774308017,0.14094432699083873,Negative
+2022-01-12,1827.3,192.98,0.48,US,Core Inflation Rate YoY ,0.18034265103697042,0.18034265103697042,Positive
+2022-01-11,1818.5,184.15,1.1,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Positive
+2022-01-10,1798.8,173.04,0.08,,,1.097918675666989,1.4835862307477667,Neutral
+2022-01-07,1797.4,238.93,0.46,US,Non Farm Payrolls ,67.0,72.32,Positive
+2022-01-06,1789.2,238.64,-1.97,US,Balance of Trade ,3.9667306461932292,1.9875776397515457,Negative
+2022-01-05,1825.1,173.34,0.58,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Positive
+2022-01-04,1814.6,167.71,0.81,US,ISM Manufacturing PMI ,2.1720969089390096,2.5020850708924103,Positive
+2022-01-03,1800.1,168.31,-1.56,CN,Caixin Manufacturing PMI ,1.7664376840039224,1.5686274509803866,Negative
+2021-12-31,1828.6,106.6,0.8,,,1.097918675666989,1.4835862307477667,Neutral
+2021-12-30,1814.1,113.43,0.46,CN,NBS Manufacturing PMI ,0.5923000987166774,0.39292730844794277,Positive
+2021-12-29,1805.8,138.69,-0.28,,,1.097918675666989,1.4835862307477667,Neutral
+2021-12-28,1810.9,100.54,0.12,,,1.097918675666989,1.4835862307477667,Neutral
+2021-12-27,1808.8,84.23,-0.16,,,1.097918675666989,1.4835862307477667,Neutral
+2021-12-23,1811.7,104.84,0.53,US,Durable Goods Orders MoM ,1.7291066282420755,2.7027027027027026,Positive
+2021-12-22,1802.2,110.41,0.75,,,1.097918675666989,1.4835862307477667,Neutral
+2021-12-21,1788.7,134.15,-0.33,,,1.097918675666989,1.4835862307477667,Neutral
+2021-12-20,1794.6,105.39,-0.57,,,1.097918675666989,1.4835862307477667,Neutral
+2021-12-17,1804.9,156.61,0.37,GB,Retail Sales MoM ,1.1741682974559686,0.78125,Positive
+2021-12-16,1798.2,167.78,1.91,US,Building Permits ,2.2399999999999967,3.777061262091206,Positive
+2021-12-15,1764.5,161.1,-0.44,US,Retail Sales MoM ,0.9891196834817014,1.3820335636722607,Negative
+2021-12-14,1772.3,153.25,-0.89,GB,Claimant Count Change ,1.097918675666989,86.62790697674419,Negative
+2021-12-13,1788.3,106.06,0.2,,,1.097918675666989,1.4835862307477667,Neutral
+2021-12-10,1784.8,142.0,0.46,US,Core Inflation Rate YoY ,0.0,0.0,Positive
+2021-12-09,1776.7,123.97,-0.49,,,1.097918675666989,1.4835862307477667,Neutral
+2021-12-08,1785.5,109.69,0.04,US,JOLTs Job Openings ,5.641736331530245,5.357142857142854,Positive
+2021-12-07,1784.7,129.89,0.29,US,Balance of Trade ,0.4514672686230206,1.6654049962149802,Positive
+2021-12-06,1779.5,104.48,-0.25,CN,Exports YoY ,4.255319148936169,8.695652173913043,Negative
+2021-12-03,1783.9,175.18,1.2,US,Non Farm Payrolls ,89.35611038107753,89.35611038107753,Positive
+2021-12-02,1762.7,172.72,-1.21,JP,Consumer Confidence ,1.097918675666989,1.9950124688279232,Negative
+2021-12-01,1784.3,180.34,0.44,US,ISM Manufacturing PMI ,0.16246953696182198,0.1622060016220623,Positive
+2021-11-30,1776.5,242.86,-0.49,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Negative
+2021-11-29,1785.2,151.37,-0.1,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Negative
+2021-11-26,1786.9,2.97,-0.07,,,1.097918675666989,1.4835862307477667,Neutral
+2021-11-25,1788.1,180.64,0.21,,,1.097918675666989,1.4835862307477667,Neutral
+2021-11-24,1784.3,203.24,0.03,US,Durable Goods Orders MoM ,1.4042126379137412,1.6032064128256511,Positive
+2021-11-23,1783.8,311.35,-1.25,US,Markit Manufacturing PMI Flash ,0.16792611251049777,0.5046257359125387,Negative
+2021-11-22,1806.3,352.86,-2.45,,,1.097918675666989,1.4835862307477667,Neutral
+2021-11-19,1851.6,234.08,-0.53,GB,Retail Sales MoM ,0.5923000987166832,0.1970443349753695,Negative
+2021-11-18,1861.4,186.06,-0.47,GB,GfK Consumer Confidence ,25.806451612903224,13.793103448275861,Negative
+2021-11-17,1870.2,172.42,0.87,US,Building Permits ,0.5597014925373139,0.510322430990495,Positive
+2021-11-16,1854.1,220.43,-0.67,US,Retail Sales MoM ,0.5819592628516006,0.9718172983479108,Negative
+2021-11-15,1866.6,221.21,-0.1,,,1.097918675666989,1.4835862307477667,Neutral
+2021-11-12,1868.5,201.36,0.25,US,JOLTs Job Openings ,1.2696660226331762,3.1386386851146897,Positive
+2021-11-11,1863.9,205.31,0.84,EA,ECB Macroeconomic Projections,1.097918675666989,1.4835862307477667,Positive
+2021-11-10,1848.3,352.79,0.96,US,Core Inflation Rate YoY ,0.5509641873278243,0.9199632014719408,Positive
+2021-11-09,1830.8,224.41,0.15,US,PPI MoM ,0.0,0.0,Positive
+2021-11-08,1828.0,200.41,0.62,,,1.097918675666989,1.4835862307477667,Neutral
+2021-11-05,1816.8,299.62,1.3,US,Non Farm Payrolls ,16.4969450101833,28.11158798283262,Positive
+2021-11-04,1793.5,222.61,1.68,US,Balance of Trade ,0.49875311720698967,7.617817947062629,Positive
+2021-11-03,1763.9,257.43,-1.43,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Negative
+2021-11-02,1789.4,145.79,-0.36,,,1.097918675666989,1.4835862307477667,Neutral
+2021-11-01,1795.8,143.33,0.67,US,ISM Manufacturing PMI ,0.4905968928863404,0.819000819000819,Positive
+2021-10-29,1783.9,254.51,-1.04,US,Personal Income MoM ,1.6194331983805668,2.4193548387096775,Negative
+2021-10-28,1802.6,220.88,0.21,,,1.097918675666989,1.4835862307477667,Neutral
+2021-10-27,1798.8,182.8,0.3,US,Durable Goods Orders MoM ,1.4213197969543145,0.8097165991902834,Positive
+2021-10-26,1793.4,197.93,-0.74,,,1.097918675666989,1.4835862307477667,Neutral
+2021-10-25,1806.8,153.59,0.58,,,1.097918675666989,1.4835862307477667,Neutral
+2021-10-22,1796.3,312.81,0.81,EA,Markit Composite PMI Flash ,1.6289592760181097,1.9873532068654047,Positive
+2021-10-21,1781.9,138.73,-0.17,GB,Gfk Consumer Confidence ,6.25,20.0,Negative
+2021-10-20,1784.9,174.08,0.81,GB,Inflation Rate YoY ,0.1881467544684856,0.1881467544684856,Positive
+2021-10-19,1770.5,166.97,0.27,US,Building Permits ,4.263293511360973,4.7207291423229725,Positive
+2021-10-18,1765.7,152.74,-0.15,,,1.097918675666989,1.4835862307477667,Neutral
+2021-10-15,1768.3,202.63,-1.65,US,Retail Sales MoM ,1.7910447761194035,1.5904572564612327,Negative
+2021-10-14,1797.9,164.65,0.18,,,1.097918675666989,1.4835862307477667,Neutral
+2021-10-13,1794.7,299.04,2.01,US,Core Inflation Rate YoY ,0.0,0.0,Positive
+2021-10-12,1759.3,168.11,0.21,US,JOLTs Job Openings ,4.346270792344845,3.2465488556140167,Positive
+2021-10-11,1755.7,114.77,-0.1,,,1.097918675666989,1.4835862307477667,Neutral
+2021-10-08,1757.4,240.37,-0.1,US,Non Farm Payrolls ,88.05755395683454,83.88059701492537,Negative
+2021-10-07,1759.2,146.41,-0.15,CA,Ivey PMI s.a ,1.097918675666989,9.14454277286136,Negative
+2021-10-06,1761.8,159.22,0.05,,,1.097918675666989,1.4835862307477667,Neutral
+2021-10-05,1760.9,151.42,-0.38,US,Balance of Trade ,3.9215686274509762,3.494060097833683,Negative
+2021-10-04,1767.6,166.18,0.52,,,1.097918675666989,1.4835862307477667,Neutral
+2021-10-01,1758.4,151.2,0.08,US,Personal Income MoM ,0.19900497512437815,0.0,Positive
+2021-09-30,1757.0,246.37,1.98,JP,Tankan Large Manufacturers Index,31.25,38.70967741935484,Positive
+2021-09-29,1722.9,177.39,-0.84,CN,NBS Manufacturing PMI ,0.9930486593843099,1.5841584158415787,Negative
+2021-09-28,1737.5,215.84,-0.83,,,1.097918675666989,1.4835862307477667,Neutral
+2021-09-27,1752.0,137.57,0.02,US,Durable Goods Orders MoM ,2.1463414634146343,2.7397260273972597,Positive
+2021-09-24,1751.7,151.55,0.11,,,1.097918675666989,1.4835862307477667,Neutral
+2021-09-23,1749.8,225.46,-1.63,GB,Gfk Consumer Confidence ,50.0,50.0,Negative
+2021-09-22,1778.8,172.35,0.03,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Positive
+2021-09-21,1778.2,141.62,0.82,CN,Loan Prime Rate 1Y,1.097918675666989,0.0,Positive
+2021-09-20,1763.8,152.45,0.71,,,1.097918675666989,1.4835862307477667,Neutral
+2021-09-17,1751.4,183.25,-0.3,,,1.097918675666989,1.4835862307477667,Neutral
+2021-09-16,1756.7,255.27,-2.12,US,Retail Sales MoM ,3.003003003003003,2.8000000000000003,Negative
+2021-09-15,1794.8,139.3,-0.68,GB,Inflation Rate YoY ,0.5655042412818094,0.5655042412818094,Negative
+2021-09-14,1807.1,197.95,0.71,US,Core Inflation Rate YoY ,0.369685767097967,0.5540166204986142,Positive
+2021-09-13,1794.4,114.31,0.13,,,1.097918675666989,1.4835862307477667,Neutral
+2021-09-10,1792.1,136.25,-0.44,GB,Balance of Trade ,1.097918675666989,53.658536585365866,Negative
+2021-09-09,1800.0,154.13,0.36,,,1.097918675666989,1.4835862307477667,Neutral
+2021-09-08,1793.5,161.26,-0.22,CA,Ivey PMI s.a ,1.097918675666989,16.260162601626014,Negative
+2021-09-07,1797.4,0.02,-0.06,,,1.097918675666989,1.4835862307477667,Neutral
+2021-09-06,1798.5,252.48,-1.92,,,1.097918675666989,1.4835862307477667,Neutral
+2021-09-03,1833.7,184.98,1.23,US,Non Farm Payrolls ,104.46247464503043,104.46247464503043,Positive
+2021-09-02,1811.5,113.03,-0.25,US,Balance of Trade ,1.4285714285714286,0.0,Negative
+2021-09-01,1816.0,140.12,-0.12,,,1.097918675666989,1.4835862307477667,Neutral
+2021-08-31,1818.1,170.39,0.33,JP,Consumer Confidence ,1.097918675666989,0.8032128514056148,Positive
+2021-08-30,1812.2,104.88,-0.4,CN,NBS Manufacturing PMI ,0.19743336623889712,0.3944773175542322,Negative
+2021-08-27,1819.5,203.64,1.35,US,Personal Income MoM ,1.7769002961500493,1.7769002961500493,Positive
+2021-08-26,1795.2,134.53,0.23,,,1.097918675666989,1.4835862307477667,Neutral
+2021-08-25,1791.0,163.46,-0.97,US,Durable Goods Orders MoM ,0.4016064257028113,0.20060180541624875,Negative
+2021-08-24,1808.5,114.79,0.12,,,1.097918675666989,1.4835862307477667,Neutral
+2021-08-23,1806.3,156.32,1.25,,,1.097918675666989,1.4835862307477667,Neutral
+2021-08-20,1784.0,107.97,0.05,,,1.097918675666989,1.4835862307477667,Neutral
+2021-08-19,1783.1,151.25,-0.07,GB,Gfk Consumer Confidence ,14.285714285714285,30.76923076923077,Negative
+2021-08-18,1784.4,132.73,-0.19,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Negative
+2021-08-17,1787.8,144.82,-0.11,US,Retail Sales MoM ,1.6227180527383367,1.6227180527383367,Negative
+2021-08-16,1789.8,137.7,0.65,,,1.097918675666989,1.4835862307477667,Neutral
+2021-08-13,1778.2,144.81,1.51,,,1.097918675666989,1.4835862307477667,Neutral
+2021-08-12,1751.8,137.12,-0.09,GB,Balance of Trade ,1.097918675666989,16.216216216216207,Negative
+2021-08-11,1753.3,185.44,1.25,US,Core Inflation Rate YoY ,0.0,0.1839926402943884,Positive
+2021-08-10,1731.7,182.56,0.3,,,1.097918675666989,1.4835862307477667,Neutral
+2021-08-09,1726.5,289.54,-2.08,,,1.097918675666989,1.4835862307477667,Neutral
+2021-08-06,1763.1,323.15,-2.53,US,Non Farm Payrolls ,8.04851157662624,4.663774403470716,Negative
+2021-08-05,1808.9,169.84,-0.31,US,Balance of Trade ,2.4226110363391613,1.8791946308724907,Negative
+2021-08-04,1814.5,244.68,0.02,,,1.097918675666989,1.4835862307477667,Neutral
+2021-08-03,1814.1,103.45,-0.44,,,1.097918675666989,1.4835862307477667,Neutral
+2021-08-02,1822.2,159.76,0.28,JP,Consumer Confidence ,1.097918675666989,1.3245033112582782,Positive
+2021-07-30,1817.2,157.14,-1.01,US,Personal Income MoM ,0.8016032064128256,0.8016032064128256,Negative
+2021-07-29,1835.8,212.07,2.01,,,1.097918675666989,1.4835862307477667,Neutral
+2021-07-28,1799.7,209.78,-0.01,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Negative
+2021-07-27,1799.8,177.04,0.03,US,Durable Goods Orders MoM ,2.526724975704568,2.142161635832522,Positive
+2021-07-26,1799.2,204.55,-0.14,,,1.097918675666989,1.4835862307477667,Neutral
+2021-07-23,1801.8,236.76,-0.2,,,1.097918675666989,1.4835862307477667,Neutral
+2021-07-22,1805.4,193.32,0.11,GB,Gfk Consumer Confidence ,14.285714285714285,0.0,Positive
+2021-07-21,1803.4,218.64,-0.44,,,1.097918675666989,1.4835862307477667,Neutral
+2021-07-20,1811.4,221.14,0.12,JP,Balance of Trade ,18.194740582800286,4.284621270084165,Positive
+2021-07-19,1809.2,249.68,-0.32,JP,Inflation Rate YoY ,1.097918675666989,0.39920159680638717,Negative
+2021-07-16,1815.0,184.66,-0.77,US,Retail Sales MoM ,1.996007984031936,2.197802197802198,Negative
+2021-07-15,1829.0,175.61,0.22,GB,Claimant Count Change ,1.097918675666989,4.448246364414031,Positive
+2021-07-14,1825.0,229.88,0.83,GB,Inflation Rate YoY ,0.5730659025787972,0.38167938931297746,Positive
+2021-07-13,1809.9,242.18,0.22,US,Core Inflation Rate YoY ,0.9216589861751149,1.1070110701107008,Positive
+2021-07-12,1805.9,201.42,-0.26,,,1.097918675666989,1.4835862307477667,Neutral
+2021-07-09,1810.6,185.58,0.58,GB,Balance of Trade,1.097918675666989,919.9999999999998,Positive
+2021-07-08,1800.2,249.34,-0.11,CN,Inflation Rate YoY ,0.390625,0.7797270955165692,Negative
+2021-07-07,1802.1,171.08,0.4,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Positive
+2021-07-06,1795.0,0.26,0.04,,,1.097918675666989,1.4835862307477667,Neutral
+2021-07-05,1794.2,276.6,0.61,,,1.097918675666989,1.4835862307477667,Neutral
+2021-07-02,1783.3,205.86,0.37,US,Balance of Trade,0.2824858757062187,0.5641748942171952,Positive
+2021-07-01,1776.8,171.44,0.29,,,1.097918675666989,1.4835862307477667,Neutral
+2021-06-30,1771.6,177.89,0.45,JP,Consumer Confidence ,1.097918675666989,12.32492997198879,Positive
+2021-06-29,1763.6,239.91,-0.96,CN,NBS Manufacturing PMI ,0.1947419668938684,0.0,Negative
+2021-06-28,1780.7,160.79,0.16,,,1.097918675666989,1.4835862307477667,Neutral
+2021-06-25,1777.8,161.2,0.06,US,Personal Income MoM,1.0471204188481678,2.1052631578947363,Positive
+2021-06-24,1776.7,152.23,-0.38,US,Durable Goods Orders MoM,0.9514747859181735,0.5752636625119846,Negative
+2021-06-23,1783.4,179.27,0.34,,,1.097918675666989,1.4835862307477667,Neutral
+2021-06-22,1777.4,172.75,-0.31,,,1.097918675666989,1.4835862307477667,Neutral
+2021-06-21,1782.9,195.52,0.79,,,1.097918675666989,1.4835862307477667,Neutral
+2021-06-18,1769.0,264.61,-0.33,,,1.097918675666989,1.4835862307477667,Neutral
+2021-06-17,1774.8,385.89,-4.65,JP,Inflation Rate YoY,1.097918675666989,0.4016064257028113,Negative
+2021-06-16,1861.4,234.1,0.27,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Positive
+2021-06-15,1856.4,155.34,-0.51,US,Retail Sales MoM,1.0214504596527068,2.0325203252032518,Negative
+2021-06-14,1865.9,242.3,-0.73,,,1.097918675666989,1.4835862307477667,Neutral
+2021-06-11,1879.6,220.46,-0.89,GB,Balance of Trade ,1.097918675666989,148.38709677419354,Negative
+2021-06-10,1896.4,250.55,0.05,US,Core Inflation Rate YoY,0.7462686567164172,1.1214953271028034,Positive
+2021-06-09,1895.5,147.33,0.06,,,1.097918675666989,1.4835862307477667,Neutral
+2021-06-08,1894.4,173.6,-0.23,US,Balance of Trade ,0.14609203798392156,0.14609203798392156,Negative
+2021-06-07,1898.8,146.02,0.36,,,1.097918675666989,1.4835862307477667,Neutral
+2021-06-04,1892.0,228.83,1.0,US,Non Farm Payrolls,15.041322314049587,8.717948717948717,Positive
+2021-06-03,1873.3,278.58,-1.92,,,1.097918675666989,1.4835862307477667,Neutral
+2021-06-02,1909.9,166.04,0.26,,,1.097918675666989,1.4835862307477667,Neutral
+2021-06-01,1905.0,290.65,0.0,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-31,1905.0,290.65,-0.02,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-28,1905.3,198.14,0.51,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-27,1895.7,35.79,-0.29,US,Durable Goods Orders MoM ,4.0241448692152915,4.0241448692152915,Negative
+2021-05-26,1901.2,170.53,0.17,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-25,1898.0,316.67,0.72,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-24,1884.5,183.31,0.42,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-21,1876.7,234.29,-0.28,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-20,1881.9,223.57,0.02,GB,Gfk Consumer Confidence,30.0,45.45454545454545,Positive
+2021-05-19,1881.5,398.21,0.72,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Positive
+2021-05-18,1868.0,229.02,0.02,GB,Claimant Count Change ,1.097918675666989,735.7798165137615,Positive
+2021-05-17,1867.6,267.71,1.6,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-14,1838.1,224.38,0.77,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-13,1824.0,249.93,0.07,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-12,1822.8,339.21,-0.72,US,Core Inflation Rate YoY ,1.3295346628679963,1.520912547528517,Negative
+2021-05-11,1836.1,311.1,-0.08,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-10,1837.6,269.71,0.34,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-07,1831.3,367.7,0.86,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-06,1815.7,287.63,1.76,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-05,1784.3,178.81,0.47,,,1.097918675666989,1.4835862307477667,Neutral
+2021-05-04,1776.0,246.59,-0.88,US,Balance of Trade ,0.1352265043948537,1.3623978201634876,Negative
+2021-05-03,1791.8,204.54,1.36,,,1.097918675666989,1.4835862307477667,Neutral
+2021-04-30,1767.7,167.29,-0.03,US,Personal Income MoM ,1.1315417256011284,0.8474576271186449,Negative
+2021-04-29,1768.3,231.52,-0.32,CN,NBS Manufacturing PMI ,1.1560693641618522,1.9193857965451053,Negative
+2021-04-28,1773.9,198.58,-0.28,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Negative
+2021-04-27,1778.8,147.95,-0.07,,,1.097918675666989,1.4835862307477667,Neutral
+2021-04-26,1780.1,143.36,0.13,US,Durable Goods Orders MoM ,3.8834951456310676,2.3483365949119372,Positive
+2021-04-23,1777.8,175.85,-0.24,,,1.097918675666989,1.4835862307477667,Neutral
+2021-04-22,1782.0,163.75,-0.62,GB,Gfk Consumer Confidence ,23.076923076923077,23.076923076923077,Negative
+2021-04-21,1793.1,173.97,0.83,GB,Inflation Rate YoY ,0.1970443349753695,0.1970443349753695,Positive
+2021-04-20,1778.4,169.04,0.44,GB,Claimant Count Change ,1.097918675666989,173.68094351334577,Positive
+2021-04-19,1770.6,180.73,-0.54,CN,Loan Prime Rate 1Y,0.0,0.0,Negative
+2021-04-16,1780.2,173.5,0.76,,,1.097918675666989,1.4835862307477667,Neutral
+2021-04-15,1766.8,198.14,1.76,US,Retail Sales MoM ,6.7415730337078665,9.273840769903764,Positive
+2021-04-14,1736.3,145.26,-0.65,,,1.097918675666989,1.4835862307477667,Neutral
+2021-04-13,1747.6,175.59,0.86,US,Core Inflation Rate YoY ,0.19398642095053367,0.0,Positive
+2021-04-12,1732.7,125.36,-0.69,,,1.097918675666989,1.4835862307477667,Neutral
+2021-04-09,1744.8,171.4,-0.76,,,1.097918675666989,1.4835862307477667,Neutral
+2021-04-08,1758.2,144.57,0.95,JP,Consumer Confidence ,1.097918675666989,0.27359781121751414,Positive
+2021-04-07,1741.6,122.8,-0.08,US,Balance of Trade ,0.8534850640113717,1.8584703359542494,Negative
+2021-04-06,1743.0,152.6,0.82,,,1.097918675666989,1.4835862307477667,Neutral
+2021-04-05,1728.8,101.75,0.02,,,1.097918675666989,1.4835862307477667,Neutral
+2021-04-01,1728.4,170.43,0.75,,,1.097918675666989,1.4835862307477667,Neutral
+2021-03-31,1715.6,210.77,1.76,JP,Tankan Large Manufacturers Index,166.66666666666669,350.0,Positive
+2021-03-30,1686.0,225.87,-1.53,US,President Biden Speech on Recovery Package ,1.097918675666989,1.4835862307477667,Negative
+2021-03-29,1712.2,135.46,-1.16,,,1.097918675666989,1.4835862307477667,Neutral
+2021-03-26,1732.3,172.94,0.42,US,Personal Income MoM ,0.4672897196261686,2.1201413427561855,Positive
+2021-03-25,1725.1,226.21,-0.47,,,1.097918675666989,1.4835862307477667,Neutral
+2021-03-24,1733.2,186.52,0.47,US,Durable Goods Orders MoM ,3.8114343029087263,4.3999999999999995,Positive
+2021-03-23,1725.1,226.2,-0.75,GB,Claimant Count Change ,1.097918675666989,293.4844192634561,Negative
+2021-03-22,1738.1,196.31,-0.21,,,1.097918675666989,1.4835862307477667,Neutral
+2021-03-19,1741.7,213.28,0.53,,,1.097918675666989,1.4835862307477667,Neutral
+2021-03-18,1732.5,251.76,0.31,GB,Gfk Consumer Confidence ,22.857142857142858,22.857142857142858,Positive
+2021-03-17,1727.1,220.55,-0.22,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Negative
+2021-03-16,1730.9,173.89,0.1,US,Retail Sales MoM ,5.181347150259067,4.979253112033195,Positive
+2021-03-15,1729.2,163.05,0.55,,,1.097918675666989,1.4835862307477667,Neutral
+2021-03-12,1719.8,232.21,-0.16,GB,Balance of Trade ,1.097918675666989,118.5185185185185,Negative
+2021-03-11,1722.6,215.34,0.05,,,1.097918675666989,1.4835862307477667,Neutral
+2021-03-10,1721.8,226.89,0.29,US,Core Inflation Rate YoY ,0.1947419668938658,0.1947419668938658,Positive
+2021-03-09,1716.9,248.95,2.32,CN,Inflation Rate YoY ,0.4024144869215292,0.20100502512562815,Positive
+2021-03-08,1678.0,273.91,-1.21,,,1.097918675666989,1.4835862307477667,Neutral
+2021-03-05,1698.5,269.33,-0.13,US,Balance of Trade ,1.039346696362291,1.039346696362291,Negative
+2021-03-04,1700.7,277.45,-0.88,JP,Consumer Confidence ,1.097918675666989,9.146341463414624,Negative
+2021-03-03,1715.8,255.65,-1.03,,,1.097918675666989,1.4835862307477667,Neutral
+2021-03-02,1733.6,235.96,0.62,,,1.097918675666989,1.4835862307477667,Neutral
+2021-03-01,1723.0,241.92,-0.34,,,1.097918675666989,1.4835862307477667,Neutral
+2021-02-26,1728.8,362.55,-2.62,US,Personal Income MoM ,0.836820083682009,2.5316455696202533,Negative
+2021-02-25,1775.4,316.25,-1.25,US,Durable Goods Orders MoM ,4.401913875598087,4.2065009560229445,Negative
+2021-02-24,1797.9,224.06,-0.44,,,1.097918675666989,1.4835862307477667,Neutral
+2021-02-23,1805.9,191.15,-0.14,GB,Claimant Count Change ,1.097918675666989,1500.0,Negative
+2021-02-22,1808.4,221.2,1.74,,,1.097918675666989,1.4835862307477667,Neutral
+2021-02-19,1777.4,251.78,0.14,CN,Loan Prime Rate 1Y,1.097918675666989,0.0,Positive
+2021-02-18,1775.0,224.77,0.12,GB,Gfk Consumer Confidence ,16.3265306122449,12.5,Positive
+2021-02-17,1772.8,257.34,-1.46,US,Retail Sales MoM ,7.894736842105261,8.286252354048964,Negative
+2021-02-16,1799.0,355.92,0.0,JP,Balance of Trade ,59.8331346841478,28.184353831850185,Neutral
+2021-02-15,1799.0,355.92,-1.33,,,1.097918675666989,1.4835862307477667,Neutral
+2021-02-12,1823.2,171.9,-0.2,GB,Balance of Trade ,1.097918675666989,42.5531914893617,Negative
+2021-02-11,1826.8,147.02,-0.86,,,1.097918675666989,1.4835862307477667,Neutral
+2021-02-10,1842.7,176.44,0.28,US,Core Inflation Rate YoY ,0.194363459669582,0.3883495145631068,Positive
+2021-02-09,1837.5,154.39,0.18,CN,Inflation Rate YoY ,0.6018054162487463,0.20100502512562815,Positive
+2021-02-08,1834.2,177.56,1.17,,,1.097918675666989,1.4835862307477667,Neutral
+2021-02-05,1813.0,205.76,1.22,US,Balance of Trade ,1.3709063214013577,5.014749262536881,Positive
+2021-02-04,1791.2,279.62,-2.39,,,1.097918675666989,1.4835862307477667,Neutral
+2021-02-03,1835.1,137.23,0.09,,,1.097918675666989,1.4835862307477667,Neutral
+2021-02-02,1833.4,236.0,-1.64,,,1.097918675666989,1.4835862307477667,Neutral
+2021-02-01,1863.9,242.05,0.74,,,1.097918675666989,1.4835862307477667,Neutral
+2021-01-29,1850.3,276.17,0.49,US,Personal Income MoM ,0.99304865938431,0.99304865938431,Positive
+2021-01-28,1841.2,277.59,-0.2,,,1.097918675666989,1.4835862307477667,Neutral
+2021-01-27,1844.9,195.54,-0.32,US,Durable Goods Orders MoM ,1.3847675568743818,1.188118811881188,Negative
+2021-01-26,1850.9,170.26,-0.23,GB,Claimant Count Change ,130.2325581395349,137.5,Negative
+2021-01-25,1855.2,211.98,-0.05,,,1.097918675666989,1.4835862307477667,Neutral
+2021-01-22,1856.2,249.72,-0.52,,,1.097918675666989,1.4835862307477667,Neutral
+2021-01-21,1865.9,196.94,-0.03,GB,Gfk Consumer Confidence ,3.571428571428571,0.0,Negative
+2021-01-20,1866.5,274.4,1.33,GB,Inflation Rate YoY ,0.1978239366963403,0.0,Positive
+2021-01-19,1842.0,0.4,0.1,US,Treasury Secretary Yellen Senate Confirmation Hearing,1.097918675666989,1.4835862307477667,Positive
+2021-01-18,1840.2,331.59,0.56,,,1.097918675666989,1.4835862307477667,Neutral
+2021-01-15,1829.9,231.11,-1.16,US,Retail Sales MoM ,1.4098690835850958,1.0090817356205852,Negative
+2021-01-14,1851.4,257.66,-0.19,,,1.097918675666989,1.4835862307477667,Neutral
+2021-01-13,1854.9,225.99,0.58,US,Core Inflation Rate YoY ,0.0,0.0,Positive
+2021-01-12,1844.2,240.66,-0.36,,,1.097918675666989,1.4835862307477667,Neutral
+2021-01-11,1850.8,268.36,0.84,,,1.097918675666989,1.4835862307477667,Neutral
+2021-01-08,1835.4,443.51,-4.09,US,Non Farm Payrolls ,620.5882352941177,1866.6666666666667,Negative
+2021-01-07,1913.6,199.98,0.26,US,Balance of Trade ,4.383975812547228,0.7423904974016333,Positive
+2021-01-06,1908.6,366.61,-2.34,JP,Consumer Confidence ,1.097918675666989,9.439528023598818,Negative
+2021-01-05,1954.4,201.95,0.4,,,1.097918675666989,1.4835862307477667,Neutral
+2021-01-04,1946.6,273.37,2.72,,,1.097918675666989,1.4835862307477667,Neutral
+2020-12-31,1895.1,130.63,0.09,,,1.097918675666989,1.4835862307477667,Neutral
+2020-12-30,1893.4,133.66,0.56,CN,NBS Manufacturing PMI ,0.19065776930410186,0.7662835249042118,Positive
+2020-12-29,1882.9,149.27,0.13,,,1.097918675666989,1.4835862307477667,Neutral
+2020-12-28,1880.4,196.76,-0.15,,,1.097918675666989,1.4835862307477667,Neutral
+2020-12-24,1883.2,89.41,0.27,,,1.097918675666989,1.4835862307477667,Neutral
+2020-12-23,1878.1,162.54,0.42,US,Durable Goods Orders MoM ,0.5911330049261082,0.5911330049261082,Positive
+2020-12-22,1870.3,176.02,-0.66,,,1.097918675666989,1.4835862307477667,Neutral
+2020-12-21,1882.8,232.05,-0.32,,,1.097918675666989,1.4835862307477667,Neutral
+2020-12-18,1888.9,153.23,-0.08,,,1.097918675666989,1.4835862307477667,Neutral
+2020-12-17,1890.4,219.87,1.68,GB,GfK Consumer Confidence ,17.857142857142858,14.545454545454545,Positive
+2020-12-16,1859.1,199.68,0.2,US,Retail Sales MoM ,1.6227180527383367,1.6227180527383367,Positive
+2020-12-15,1855.3,173.61,1.27,GB,Claimant Count Change ,1.097918675666989,71.9832109129066,Positive
+2020-12-14,1832.1,168.49,-0.62,,,1.097918675666989,1.4835862307477667,Neutral
+2020-12-11,1843.6,153.8,0.34,,,1.097918675666989,1.4835862307477667,Neutral
+2020-12-10,1837.4,164.8,-0.06,US,Core Inflation Rate YoY ,0.0,0.0,Negative
+2020-12-09,1838.5,219.59,-1.94,,,1.097918675666989,1.4835862307477667,Neutral
+2020-12-08,1874.9,151.79,0.48,CN,Inflation Rate YoY ,1.0050251256281406,1.2048192771084338,Positive
+2020-12-07,1866.0,209.04,1.41,CA,Ivey PMI s.a ,3.6900369003690034,2.4141132776230214,Positive
+2020-12-04,1840.0,171.26,-0.06,US,Balance of Trade ,2.679275019700545,2.9897718332022007,Negative
+2020-12-03,1841.1,180.36,0.6,,,1.097918675666989,1.4835862307477667,Neutral
+2020-12-02,1830.2,185.32,0.62,JP,Consumer Confidence ,1.097918675666989,2.0679468242245282,Positive
+2020-12-01,1818.9,203.65,2.13,,,1.097918675666989,1.4835862307477667,Neutral
+2020-11-30,1780.9,242.73,-0.4,EA,Eurogroup Video Conference,1.097918675666989,1.4835862307477667,Negative
+2020-11-27,1788.1,282.35,0.0,,,1.097918675666989,1.4835862307477667,Neutral
+2020-11-26,1788.1,282.35,-0.96,,,1.097918675666989,1.4835862307477667,Neutral
+2020-11-25,1805.5,205.75,0.05,US,Durable Goods Orders MoM ,0.7827788649706457,0.979431929480901,Positive
+2020-11-24,1804.6,367.88,-1.81,,,1.097918675666989,1.4835862307477667,Neutral
+2020-11-23,1837.8,319.66,-1.85,,,1.097918675666989,1.4835862307477667,Neutral
+2020-11-20,1872.4,186.17,0.59,,,1.097918675666989,1.4835862307477667,Neutral
+2020-11-19,1861.5,222.35,-0.66,GB,GfK Consumer Confidence ,3.0303030303030303,0.0,Negative
+2020-11-18,1873.9,209.0,-0.59,GB,Inflation Rate YoY ,0.1974333662388944,0.0,Negative
+2020-11-17,1885.1,160.88,-0.14,US,Retail Sales MoM ,0.3968253968253968,0.198609731876862,Negative
+2020-11-16,1887.8,222.94,0.08,,,1.097918675666989,1.4835862307477667,Neutral
+2020-11-13,1886.2,162.54,0.69,,,1.097918675666989,1.4835862307477667,Neutral
+2020-11-12,1873.3,209.93,0.63,US,Core Inflation Rate YoY ,0.3868471953578333,0.3868471953578333,Positive
+2020-11-11,1861.6,215.17,-0.79,,,1.097918675666989,1.4835862307477667,Neutral
+2020-11-10,1876.4,264.87,1.19,GB,Claimant Count Change ,752.8301886792452,1827.7777777777778,Positive
+2020-11-09,1854.4,496.09,-4.99,CN,Inflation Rate YoY ,0.5923000987166832,0.9852216748768474,Negative
+2020-11-06,1951.7,246.78,0.25,US,Non Farm Payrolls ,6.133979015334948,22.28024369016536,Positive
+2020-11-05,1946.8,297.51,2.67,,,1.097918675666989,1.4835862307477667,Neutral
+2020-11-04,1896.2,293.95,-0.74,US,Balance of Trade ,0.15785319652723193,1.2698412698412653,Negative
+2020-11-03,1910.4,171.37,0.95,EA,Eurogroup Video Conference,1.097918675666989,1.4835862307477667,Positive
+2020-11-02,1892.5,164.94,0.67,US,Presidential Election,1.097918675666989,1.4835862307477667,Positive
+2020-10-30,1879.9,213.17,0.64,US,Personal Income MoM ,0.9871668311944718,0.9871668311944718,Positive
+2020-10-29,1868.0,225.16,-0.6,JP,Consumer Confidence ,1.097918675666989,3.458213256484137,Negative
+2020-10-28,1879.2,297.09,-1.71,,,1.097918675666989,1.4835862307477667,Neutral
+2020-10-27,1911.9,153.3,0.33,US,Durable Goods Orders MoM ,2.7343749999999996,2.932551319648094,Positive
+2020-10-26,1905.7,166.31,0.03,,,1.097918675666989,1.4835862307477667,Neutral
+2020-10-23,1905.2,172.96,0.03,,,1.097918675666989,1.4835862307477667,Neutral
+2020-10-22,1904.6,215.58,-1.29,GB,Gfk Consumer Confidence ,10.344827586206897,17.857142857142858,Negative
+2020-10-21,1929.5,201.27,0.74,GB,Inflation Rate YoY ,0.0,0.1982160555004956,Positive
+2020-10-20,1915.4,163.91,0.19,,,1.097918675666989,1.4835862307477667,Neutral
+2020-10-19,1911.7,159.85,0.28,CN,Loan Prime Rate 1Y,0.0,0.0,Positive
+2020-10-16,1906.4,146.91,-0.13,US,Retail Sales MoM ,2.3391812865497075,2.7343749999999996,Negative
+2020-10-15,1908.9,213.57,0.08,,,1.097918675666989,1.4835862307477667,Neutral
+2020-10-14,1907.3,188.3,0.67,CN,Inflation Rate YoY ,0.19323671497584494,0.5785920925747347,Positive
+2020-10-13,1894.6,267.54,-1.78,US,Core Inflation Rate YoY ,0.19323671497584494,0.0,Negative
+2020-10-12,1928.9,157.21,0.14,,,1.097918675666989,1.4835862307477667,Neutral
+2020-10-09,1926.2,229.85,1.64,GB,Balance of Trade ,1.097918675666989,53.333333333333336,Positive
+2020-10-08,1895.1,185.45,0.23,,,1.097918675666989,1.4835862307477667,Neutral
+2020-10-07,1890.8,188.59,-0.94,CA,Ivey PMI s.a ,1.097918675666989,22.222222222222225,Negative
+2020-10-06,1908.8,219.44,-0.59,US,Balance of Trade ,1.5128593040847202,0.9049773755656023,Negative
+2020-10-05,1920.1,177.59,0.66,EA,Eurogroup Video Conference,1.097918675666989,1.4835862307477667,Positive
+2020-10-02,1907.6,212.73,-0.45,US,Non Farm Payrolls ,25.0,32.21306277742549,Negative
+2020-10-01,1916.3,262.09,1.1,US,Personal Income MoM ,0.632244467860906,1.4690451206715633,Positive
+2020-09-30,1895.5,259.87,-0.4,JP,Tankan Large Manufacturers Index,16.3265306122449,3.8461538461538463,Negative
+2020-09-29,1903.2,217.8,1.11,CN,NBS Manufacturing PMI ,0.5785920925747293,0.19249278152069568,Positive
+2020-09-28,1882.3,235.92,0.86,,,1.097918675666989,1.4835862307477667,Neutral
+2020-09-25,1866.3,230.86,-0.56,US,Durable Goods Orders MoM ,2.1589793915603535,3.125,Negative
+2020-09-24,1876.9,345.04,0.45,GB,Winter Economy Plan,1.097918675666989,1.4835862307477667,Positive
+2020-09-23,1868.4,411.56,-2.05,,,1.097918675666989,1.4835862307477667,Neutral
+2020-09-22,1907.6,282.71,-0.16,,,1.097918675666989,1.4835862307477667,Neutral
+2020-09-21,1910.6,386.67,-2.62,,,1.097918675666989,1.4835862307477667,Neutral
+2020-09-18,1962.1,176.07,0.63,,,1.097918675666989,1.4835862307477667,Neutral
+2020-09-17,1949.9,273.14,-1.05,JP,Inflation Rate YoY ,1.097918675666989,0.19940179461615157,Negative
+2020-09-16,1970.5,298.39,0.22,US,Retail Sales MoM ,0.7874015748031495,0.7874015748031495,Positive
+2020-09-15,1966.2,239.54,0.13,GB,Claimant Count Change ,30.108757870635372,36.11774065234686,Positive
+2020-09-14,1963.7,200.09,0.81,,,1.097918675666989,1.4835862307477667,Neutral
+2020-09-11,1947.9,205.23,-0.83,US,Core Inflation Rate YoY ,0.1936108422071638,0.38759689922480656,Negative
+2020-09-10,1964.3,271.48,0.48,,,1.097918675666989,1.4835862307477667,Neutral
+2020-09-09,1954.9,227.18,0.79,,,1.097918675666989,1.4835862307477667,Neutral
+2020-09-08,1939.5,0.04,-0.19,CN,Inflation Rate YoY ,0.0,0.19065776930409933,Negative
+2020-09-07,1943.2,416.01,0.46,,,1.097918675666989,1.4835862307477667,Neutral
+2020-09-04,1934.3,304.74,-0.18,US,Non Farm Payrolls ,2.092352092352092,8.315863032844165,Negative
+2020-09-03,1937.8,303.03,-0.35,US,Balance of Trade ,9.286898839137647,7.565789473684213,Negative
+2020-09-02,1944.7,332.59,-1.73,,,1.097918675666989,1.4835862307477667,Neutral
+2020-09-01,1978.9,304.89,0.02,,,1.097918675666989,1.4835862307477667,Neutral
+2020-08-31,1978.6,245.11,0.19,JP,Consumer Confidence ,1.097918675666989,1.0118043844856686,Positive
+2020-08-28,1974.9,334.1,2.19,US,Personal Income MoM ,1.1976047904191618,1.6,Positive
+2020-08-27,1932.6,467.17,-1.02,,,1.097918675666989,1.4835862307477667,Neutral
+2020-08-26,1952.5,342.21,1.53,US,Durable Goods Orders MoM ,11.94805194805195,12.68462206776716,Positive
+2020-08-25,1923.1,274.11,-0.83,,,1.097918675666989,1.4835862307477667,Neutral
+2020-08-24,1939.2,286.26,-0.4,,,1.097918675666989,1.4835862307477667,Neutral
+2020-08-21,1947.0,355.07,0.03,,,1.097918675666989,1.4835862307477667,Neutral
+2020-08-20,1946.5,383.34,-1.21,GB,Gfk Consumer Confidence ,7.8431372549019605,12.0,Negative
+2020-08-19,1970.3,443.26,-2.13,GB,Inflation Rate YoY ,0.7874015748031495,0.5899705014749264,Negative
+2020-08-18,2013.1,361.48,0.72,JP,Balance of Trade ,274.46153846153845,245.0651769087523,Positive
+2020-08-17,1998.7,289.44,2.51,,,1.097918675666989,1.4835862307477667,Neutral
+2020-08-14,1949.8,241.8,-1.05,US,Retail Sales MoM ,1.3579049466537343,1.550387596899225,Negative
+2020-08-13,1970.4,349.89,1.1,,,1.097918675666989,1.4835862307477667,Neutral
+2020-08-12,1949.0,459.84,0.14,US,Core Inflation Rate YoY ,0.9737098344693284,1.1695906432748537,Positive
+2020-08-11,1946.3,565.0,-4.58,GB,Claimant Count Change ,160.1518026565465,178.08764940239044,Negative
+2020-08-10,2039.7,251.31,0.58,,,1.097918675666989,1.4835862307477667,Neutral
+2020-08-07,2028.0,398.13,-2.0,US,Non Farm Payrolls ,9.690844233055886,8.451536643026005,Negative
+2020-08-06,2069.4,312.76,0.98,,,1.097918675666989,1.4835862307477667,Neutral
+2020-08-05,2049.3,366.38,1.4,US,Balance of Trade ,1.2024048096192412,0.0,Positive
+2020-08-04,2021.0,274.42,1.75,,,1.097918675666989,1.4835862307477667,Neutral
+2020-08-03,1986.3,178.75,0.02,,,1.097918675666989,1.4835862307477667,Neutral
+2020-07-31,1985.9,279.32,0.97,US,Personal Income MoM ,1.2195121951219512,1.6227180527383367,Positive
+2020-07-30,1966.8,271.38,0.69,CN,NBS Manufacturing PMI ,0.7782101167315146,0.19398642095053625,Positive
+2020-07-29,1953.4,209.84,0.45,,,1.097918675666989,1.4835862307477667,Neutral
+2020-07-28,1944.6,434.45,0.7,,,1.097918675666989,1.4835862307477667,Neutral
+2020-07-27,1931.0,428.23,1.77,US,Durable Goods Orders MoM ,0.5249343832020977,4.096170970614424,Positive
+2020-07-24,1897.5,300.17,0.4,,,1.097918675666989,1.4835862307477667,Neutral
+2020-07-23,1890.0,418.75,1.34,GB,Gfk Consumer Confidence ,3.8461538461538463,3.8461538461538463,Positive
+2020-07-22,1865.1,382.23,1.15,CA,Inflation Rate YoY ,0.7920792079207921,0.7920792079207921,Positive
+2020-07-21,1843.9,271.09,1.46,,,1.097918675666989,1.4835862307477667,Neutral
+2020-07-20,1817.4,177.74,0.41,JP,Inflation Rate YoY ,1.097918675666989,0.0,Positive
+2020-07-17,1810.0,167.01,0.54,,,1.097918675666989,1.4835862307477667,Neutral
+2020-07-16,1800.3,196.57,-0.74,US,Retail Sales MoM ,4.444444444444443,5.357142857142856,Negative
+2020-07-15,1813.8,183.06,0.02,GB,Inflation Rate YoY ,0.39603960396039606,0.0,Positive
+2020-07-14,1813.4,253.21,-0.04,US,Core Inflation Rate YoY ,0.19550342130987308,0.0,Negative
+2020-07-13,1814.1,230.4,0.68,,,1.097918675666989,1.4835862307477667,Neutral
+2020-07-10,1801.9,223.83,-0.11,,,1.097918675666989,1.4835862307477667,Neutral
+2020-07-09,1803.8,283.37,-0.92,EA,Eurogroup Meeting,1.097918675666989,1.4835862307477667,Negative
+2020-07-08,1820.6,247.5,0.59,GB,Supplementary Budget,1.097918675666989,1.4835862307477667,Positive
+2020-07-07,1809.9,221.73,0.61,CA,Ivey PMI s.a ,1.097918675666989,29.745596868884544,Positive
+2020-07-06,1799.0,0.11,0.31,,,1.097918675666989,1.4835862307477667,Neutral
+2020-07-03,1793.5,184.65,0.2,,,1.097918675666989,1.4835862307477667,Neutral
+2020-07-02,1790.0,186.31,0.57,US,Balance of Trade,3.001876172607883,3.001876172607883,Positive
+2020-07-01,1779.9,263.25,-1.14,JP,Consumer Confidence ,1.097918675666989,5.387205387205392,Negative
+2020-06-30,1800.5,199.42,1.08,JP,Tankan Large Manufacturers Index,9.375,0.0,Positive
+2020-06-29,1781.2,130.51,0.05,CN,NBS Manufacturing PMI ,0.9775171065493646,1.3712047012732531,Positive
+2020-06-26,1780.3,201.23,0.55,US,Personal Income MoM,4.0089086859688186,3.1042128603104207,Positive
+2020-06-25,1770.6,152.2,-0.25,US,Durable Goods Orders MoM,7.734806629834255,11.74577634754626,Negative
+2020-06-24,1775.1,239.53,-0.39,,,1.097918675666989,1.4835862307477667,Neutral
+2020-06-23,1782.0,194.68,0.88,,,1.097918675666989,1.4835862307477667,Neutral
+2020-06-22,1766.4,228.68,0.76,,,1.097918675666989,1.4835862307477667,Neutral
+2020-06-19,1753.0,181.15,1.27,,,1.097918675666989,1.4835862307477667,Neutral
+2020-06-18,1731.1,155.91,-0.26,JP,Inflation Rate YoY,0.0,0.0,Negative
+2020-06-17,1735.6,140.07,-0.05,GB,Inflation Rate YoY,0.0,0.0,Negative
+2020-06-16,1736.5,182.42,0.54,US,Retail Sales MoM,15.433571996817816,16.293929712460063,Positive
+2020-06-15,1727.2,200.23,-0.58,,,1.097918675666989,1.4835862307477667,Neutral
+2020-06-12,1737.3,151.4,-0.14,GB,Balance of Trade ,1.097918675666989,266.25766871165644,Negative
+2020-06-11,1739.8,205.35,1.11,,,1.097918675666989,1.4835862307477667,Neutral
+2020-06-10,1720.7,198.76,-0.07,US,Core Inflation Rate YoY,0.19512195121951204,0.0,Negative
+2020-06-09,1721.9,182.91,0.99,CN,Inflation Rate YoY,0.5708848715509038,0.5708848715509038,Positive
+2020-06-08,1705.1,154.77,1.31,,,1.097918675666989,1.4835862307477667,Neutral
+2020-06-05,1683.0,273.68,-2.57,US,Non Farm Payrolls,382.8415300546448,357.8301886792453,Negative
+2020-06-04,1727.4,198.72,1.33,US,Balance of Trade ,0.8213552361396275,9.542356377799415,Positive
+2020-06-03,1704.8,256.52,-1.68,,,1.097918675666989,1.4835862307477667,Neutral
+2020-06-02,1734.0,175.35,-0.93,,,1.097918675666989,1.4835862307477667,Neutral
+2020-06-01,1750.3,146.13,-0.08,,,1.097918675666989,1.4835862307477667,Neutral
+2020-05-29,1751.7,150.11,1.35,,,1.097918675666989,1.4835862307477667,Neutral
+2020-05-28,1728.3,164.82,1.03,US,Durable Goods Orders MoM ,5.642633228840131,5.642633228840131,Positive
+2020-05-27,1710.7,137.42,-0.38,,,1.097918675666989,1.4835862307477667,Neutral
+2020-05-26,1717.3,3.44,0.69,,,1.097918675666989,1.4835862307477667,Neutral
+2020-05-25,1705.6,313.17,-1.72,,,1.097918675666989,1.4835862307477667,Neutral
+2020-05-22,1735.5,196.82,0.79,,,1.097918675666989,1.4835862307477667,Neutral
+2020-05-21,1721.9,238.74,-1.72,GB,Gfk Consumer Confidence,1.097918675666989,21.333333333333336,Negative
+2020-05-20,1752.1,184.46,0.37,GB,Inflation Rate YoY ,0.19665683382497526,0.0,Positive
+2020-05-19,1745.6,185.26,0.65,GB,Claimant Count Change ,23.46805736636245,27.396351575456052,Positive
+2020-05-18,1734.4,271.47,-1.25,,,1.097918675666989,1.4835862307477667,Neutral
+2020-05-15,1756.3,200.18,0.88,,,1.097918675666989,1.4835862307477667,Neutral
+2020-05-14,1740.9,212.91,1.43,,,1.097918675666989,1.4835862307477667,Neutral
+2020-05-13,1716.4,211.61,0.56,US,Retail Sales MoM ,12.290502793296094,12.813370473537608,Positive
+2020-05-12,1706.8,198.07,0.52,US,Core Inflation Rate YoY ,0.5819592628516006,0.3883495145631068,Positive
+2020-05-11,1698.0,202.17,-0.93,,,1.097918675666989,1.4835862307477667,Neutral
+2020-05-08,1713.9,232.81,-0.69,,,1.097918675666989,1.4835862307477667,Neutral
+2020-05-07,1725.8,250.7,2.21,US,Non Farm Payrolls ,7.058989623285254,6.055015492324794,Positive
+2020-05-06,1688.5,203.37,-1.29,,,1.097918675666989,1.4835862307477667,Neutral
+2020-05-05,1710.6,184.73,-0.16,US,Balance of Trade ,0.9153318077803171,0.4566210045662003,Negative
+2020-05-04,1713.3,148.73,0.73,,,1.097918675666989,1.4835862307477667,Neutral
+2020-05-01,1700.9,168.02,0.4,,,1.097918675666989,1.4835862307477667,Neutral
+2020-04-30,1694.2,234.53,-1.12,US,Personal Income MoM ,1.0362694300518136,2.0618556701030926,Negative
+2020-04-29,1713.4,159.6,-0.51,EA,Business Confidence ,1.097918675666989,55.60975609756099,Negative
+2020-04-28,1722.2,171.34,-0.09,,,1.097918675666989,1.4835862307477667,Neutral
+2020-04-27,1723.8,146.64,-0.68,,,1.097918675666989,1.4835862307477667,Neutral
+2020-04-24,1735.6,180.24,-0.56,US,Durable Goods Orders MoM ,6.784260515603798,6.521739130434781,Negative
+2020-04-23,1745.4,201.88,0.41,GB,Gfk Consumer Confidence ,16.43835616438356,30.37974683544304,Positive
+2020-04-22,1738.3,193.73,2.99,GB,Inflation Rate YoY ,0.0,0.38910505836575876,Positive
+2020-04-21,1687.8,248.63,-1.37,GB,Claimant Count Change ,173.00743889479278,182.1879382889201,Negative
+2020-04-20,1711.2,186.91,0.73,,,1.097918675666989,1.4835862307477667,Neutral
+2020-04-17,1698.8,227.07,-1.9,,,1.097918675666989,1.4835862307477667,Neutral
+2020-04-16,1731.7,204.23,-0.49,,,1.097918675666989,1.4835862307477667,Neutral
+2020-04-15,1740.2,186.7,-1.62,US,Retail Sales MoM ,1.6806722689075613,5.188679245283017,Negative
+2020-04-14,1768.9,241.19,0.43,,,1.097918675666989,1.4835862307477667,Neutral
+2020-04-13,1761.4,166.89,0.49,,,1.097918675666989,1.4835862307477667,Neutral
+2020-04-09,1752.8,218.8,4.07,EA,Eurogroup Meeting,1.097918675666989,1.4835862307477667,Positive
+2020-04-08,1684.3,125.33,0.04,,,1.097918675666989,1.4835862307477667,Neutral
+2020-04-07,1683.7,204.5,-0.6,EA,Eurogroup Meeting,1.097918675666989,1.4835862307477667,Negative
+2020-04-06,1693.9,192.75,2.93,JP,Consumer Confidence ,1.097918675666989,17.17612809315866,Positive
+2020-04-03,1645.7,139.61,0.49,US,Non Farm Payrolls ,150.25,129.6470588235294,Positive
+2020-04-02,1637.7,167.71,2.91,US,Balance of Trade ,0.25348542458808976,2.3106546854942196,Positive
+2020-04-01,1591.4,164.48,-0.33,,,1.097918675666989,1.4835862307477667,Neutral
+2020-03-31,1596.6,176.55,-2.84,JP,Tankan Large Manufacturers Index,23.52941176470588,42.10526315789473,Negative
+2020-03-30,1643.2,157.37,-0.66,EA,Business Confidence ,68.65671641791047,533.3333333333333,Negative
+2020-03-27,1654.1,159.26,0.18,US,Personal Income MoM ,0.39603960396039606,0.5946481665014867,Positive
+2020-03-26,1651.2,215.97,1.09,,,1.097918675666989,1.4835862307477667,Neutral
+2020-03-25,1633.4,254.19,-1.65,US,Durable Goods Orders MoM ,3.9840637450199203,3.7810945273631846,Negative
+2020-03-24,1660.8,418.78,5.95,CA,Parliamentary Debate & Vote on Coronavirus Aid Package,1.097918675666989,1.4835862307477667,Positive
+2020-03-23,1567.6,362.07,5.59,,,1.097918675666989,1.4835862307477667,Neutral
+2020-03-20,1484.6,269.97,0.36,,,1.097918675666989,1.4835862307477667,Neutral
+2020-03-19,1479.3,325.29,0.09,CN,Loan Prime Rate 1Y,1.097918675666989,0.18518518518518534,Positive
+2020-03-18,1477.9,435.19,-3.14,JP,Inflation Rate YoY ,0.7905138339920948,0.1982160555004956,Negative
+2020-03-17,1525.8,434.51,2.64,US,Retail Sales MoM ,1.4042126379137412,1.2048192771084338,Positive
+2020-03-16,1486.5,565.98,-1.99,,,1.097918675666989,1.4835862307477667,Neutral
+2020-03-13,1516.7,551.05,-4.63,US,President Trump Statement on Coronavirus,1.097918675666989,1.4835862307477667,Negative
+2020-03-12,1590.3,605.72,-3.17,,,1.097918675666989,1.4835862307477667,Neutral
+2020-03-11,1642.3,404.35,-1.08,US,Core Inflation Rate YoY ,0.1910219675262657,0.1910219675262657,Negative
+2020-03-10,1660.3,385.48,-0.92,,,1.097918675666989,1.4835862307477667,Neutral
+2020-03-09,1675.7,504.16,0.2,CN,Inflation Rate YoY ,0.0,0.18132366273798747,Positive
+2020-03-06,1672.4,659.63,0.26,US,Balance of Trade ,1.7699115044247882,1.109877913429523,Positive
+2020-03-05,1668.0,363.0,1.52,,,1.097918675666989,1.4835862307477667,Neutral
+2020-03-04,1643.0,313.34,-0.09,,,1.097918675666989,1.4835862307477667,Neutral
+2020-03-03,1644.4,466.53,3.11,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Positive
+2020-03-02,1594.8,443.53,1.79,,,1.097918675666989,1.4835862307477667,Neutral
+2020-02-28,1566.7,745.84,-4.61,US,Personal Income MoM ,0.5946481665014867,0.5946481665014867,Negative
+2020-02-27,1642.5,573.29,-0.04,US,Durable Goods Orders MoM ,2.644964394710071,3.6809815950920246,Negative
+2020-02-26,1643.1,531.9,-0.42,US,President Trump Speech ,1.097918675666989,1.4835862307477667,Negative
+2020-02-25,1650.0,672.76,-1.59,,,1.097918675666989,1.4835862307477667,Neutral
+2020-02-24,1676.6,680.82,1.69,,,1.097918675666989,1.4835862307477667,Neutral
+2020-02-21,1648.8,489.19,1.75,,,1.097918675666989,1.4835862307477667,Neutral
+2020-02-20,1620.5,403.04,0.54,JP,Inflation Rate YoY ,0.0,0.0,Positive
+2020-02-19,1611.8,307.89,0.51,GB,Inflation Rate YoY ,0.3868471953578333,0.775193798449612,Positive
+2020-02-18,1603.6,414.24,0.0,GB,Claimant Count Change ,117.5257731958763,88.37209302325581,Neutral
+2020-02-17,1603.6,414.24,1.08,,,1.097918675666989,1.4835862307477667,Neutral
+2020-02-14,1586.4,227.11,0.48,US,Retail Sales MoM ,0.0,0.0,Positive
+2020-02-13,1578.8,276.25,0.46,US,Core Inflation Rate YoY ,0.1913875598086126,0.0,Positive
+2020-02-12,1571.6,189.55,0.1,,,1.097918675666989,1.4835862307477667,Neutral
+2020-02-11,1570.1,231.83,-0.6,GB,Balance of Trade ,1.097918675666989,337.3671300081766,Negative
+2020-02-10,1579.5,191.75,0.39,,,1.097918675666989,1.4835862307477667,Neutral
+2020-02-07,1573.4,286.42,0.22,US,Non Farm Payrolls ,33.67875647668394,41.17647058823529,Positive
+2020-02-06,1570.0,229.0,0.46,,,1.097918675666989,1.4835862307477667,Neutral
+2020-02-05,1562.8,306.05,0.47,US,Balance of Trade ,1.4568158168574314,0.20639834881321242,Positive
+2020-02-04,1555.5,349.0,-1.7,,,1.097918675666989,1.4835862307477667,Neutral
+2020-02-03,1582.4,320.6,-0.35,RU,Full Year GDP Growth 2019,1.097918675666989,1.4835862307477667,Negative
+2020-01-31,1587.9,343.37,-0.08,US,Personal Income MoM ,0.19900497512437815,0.3976143141153082,Negative
+2020-01-30,1589.2,382.6,1.2,EA,Business Confidence ,13.793103448275865,16.94915254237289,Positive
+2020-01-29,1570.4,251.27,0.04,US,USMCA Trade Deal Signature,1.097918675666989,1.4835862307477667,Positive
+2020-01-28,1569.8,378.01,-0.48,US,Durable Goods Orders MoM ,3.8910505836575875,3.4951456310679614,Negative
+2020-01-27,1577.4,398.06,0.35,,,1.097918675666989,1.4835862307477667,Neutral
+2020-01-24,1571.9,427.14,0.42,,,1.097918675666989,1.4835862307477667,Neutral
+2020-01-23,1565.4,361.03,0.56,JP,Inflation Rate YoY ,0.7905138339920948,0.5923000987166832,Positive
+2020-01-22,1556.7,286.08,-0.26,JP,Balance of Trade ,1.658374792703151,20.689655172413794,Negative
+2020-01-21,1560.8,2.22,0.19,GB,Claimant Count Change ,40.00000000000001,52.98329355608592,Positive
+2020-01-20,1557.9,462.62,-0.15,,,1.097918675666989,1.4835862307477667,Neutral
+2020-01-17,1560.3,264.93,0.63,,,1.097918675666989,1.4835862307477667,Neutral
+2020-01-16,1550.5,260.05,-0.23,US,Retail Sales MoM ,0.0,0.0,Negative
+2020-01-15,1554.0,310.07,0.61,US,US-China Phase 1 Trade Deal Signature,1.097918675666989,1.4835862307477667,Positive
+2020-01-14,1544.6,340.91,-0.39,US,Core Inflation Rate YoY ,0.0,0.1913875598086126,Negative
+2020-01-13,1550.6,311.73,-0.61,GB,Balance of Trade ,1.097918675666989,790.1639344262295,Negative
+2020-01-10,1560.1,344.34,0.37,US,Non Farm Payrolls ,12.258064516129032,12.861736334405144,Positive
+2020-01-09,1554.3,372.88,-0.38,,,1.097918675666989,1.4835862307477667,Neutral
+2020-01-08,1560.2,813.41,-0.9,EA,Business Confidence ,30.508474576271187,46.15384615384615,Negative
+2020-01-07,1574.3,435.87,0.35,US,Balance of Trade ,1.629802095459827,0.23501762632197754,Positive
+2020-01-06,1568.8,558.97,1.06,,,1.097918675666989,1.4835862307477667,Neutral
+2020-01-03,1552.4,436.74,1.59,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Positive
+2020-01-02,1528.1,270.55,0.33,,,1.097918675666989,1.4835862307477667,Neutral
+2019-12-31,1523.1,220.85,0.3,,,1.097918675666989,1.4835862307477667,Neutral
+2019-12-30,1518.6,178.72,0.03,CN,NBS Manufacturing PMI ,0.19743336623889712,0.19704433497535825,Positive
+2019-12-27,1518.1,204.99,0.24,,,1.097918675666989,1.4835862307477667,Neutral
+2019-12-26,1514.4,216.61,0.64,,,1.097918675666989,1.4835862307477667,Neutral
+2019-12-24,1504.8,183.68,1.08,,,1.097918675666989,1.4835862307477667,Neutral
+2019-12-23,1488.7,162.45,0.53,US,Durable Goods Orders MoM ,7.035175879396986,6.256306760847628,Positive
+2019-12-20,1480.9,140.77,-0.24,US,Personal Income MoM ,0.3968253968253968,0.595829195630586,Negative
+2019-12-19,1484.4,201.19,0.39,GB,GfK Consumer Confidence ,25.0,9.090909090909092,Positive
+2019-12-18,1478.7,197.97,-0.13,GB,Inflation Rate YoY ,0.194363459669582,0.194363459669582,Negative
+2019-12-17,1480.6,173.25,0.01,GB,Claimant Count Change ,15.837937384898716,0.6802721088435351,Positive
+2019-12-16,1480.5,165.85,-0.05,,,1.097918675666989,1.4835862307477667,Neutral
+2019-12-13,1481.2,356.68,0.6,US,Retail Sales MoM ,0.595829195630586,0.19900497512437815,Positive
+2019-12-12,1472.3,409.86,-0.18,JP,Tankan Large Manufacturers Index,133.33333333333331,133.33333333333331,Negative
+2019-12-11,1475.0,251.73,0.47,US,Core Inflation Rate YoY ,0.0,0.0,Positive
+2019-12-10,1468.1,228.83,0.22,GB,Balance of Trade ,1.097918675666989,60.91794158553546,Positive
+2019-12-09,1464.9,177.22,-0.01,CN,Inflation Rate YoY ,0.5519779208831639,0.3676470588235297,Negative
+2019-12-06,1465.1,317.32,-1.21,US,Non Farm Payrolls ,38.47874720357942,41.17647058823529,Negative
+2019-12-05,1483.1,240.01,0.2,US,Balance of Trade ,3.1612223393045307,1.908801696712616,Positive
+2019-12-04,1480.2,319.73,-0.28,,,1.097918675666989,1.4835862307477667,Neutral
+2019-12-03,1484.4,400.9,1.03,,,1.097918675666989,1.4835862307477667,Neutral
+2019-12-02,1469.2,316.58,-0.24,,,1.097918675666989,1.4835862307477667,Neutral
+2019-11-29,1472.7,272.34,0.0,JP,Consumer Confidence ,8.78828229027964,7.133421400264208,Neutral
+2019-11-28,1472.7,272.34,1.33,EA,Business Confidence ,28.57142857142857,22.95081967213115,Positive
+2019-11-27,1453.4,88.36,-0.47,US,Durable Goods Orders MoM ,2.80561122244489,2.4,Negative
+2019-11-26,1460.3,346.36,0.23,,,1.097918675666989,1.4835862307477667,Neutral
+2019-11-25,1456.9,298.71,-0.46,,,1.097918675666989,1.4835862307477667,Neutral
+2019-11-22,1463.6,320.5,0.0,,,1.097918675666989,1.4835862307477667,Neutral
+2019-11-21,1463.6,388.34,-0.72,JP,Inflation Rate YoY ,0.19900497512437815,0.3976143141153082,Negative
+2019-11-20,1474.2,369.97,-0.01,CA,Inflation Rate YoY ,0.0,0.19249278152069316,Negative
+2019-11-19,1474.3,307.86,0.16,JP,Balance of Trade ,177.7012214218603,169.99578592498946,Positive
+2019-11-18,1471.9,331.24,0.23,,,1.097918675666989,1.4835862307477667,Neutral
+2019-11-15,1468.5,251.21,-0.33,US,Retail Sales MoM ,0.19900497512437815,0.0,Negative
+2019-11-14,1473.4,317.4,0.69,,,1.097918675666989,1.4835862307477667,Neutral
+2019-11-13,1463.3,352.33,0.66,US,Core Inflation Rate YoY ,0.1910219675262657,0.1910219675262657,Positive
+2019-11-12,1453.7,429.61,-0.23,GB,Claimant Count Change ,42.31464737793852,19.672131147540984,Negative
+2019-11-11,1457.1,310.16,-0.4,GB,Balance of Trade ,1.097918675666989,50.87719298245612,Negative
+2019-11-08,1462.9,447.07,-0.24,CN,Inflation Rate YoY ,0.9337068160597569,1.4981273408239701,Negative
+2019-11-07,1466.4,674.98,-1.79,,,1.097918675666989,1.4835862307477667,Neutral
+2019-11-06,1493.1,313.72,0.63,CA,Ivey PMI s.a ,189.60000000000002,9.393346379647744,Positive
+2019-11-05,1483.7,593.62,-1.81,US,Balance of Trade ,0.0,0.966183574879227,Negative
+2019-11-04,1511.1,260.2,-0.02,,,1.097918675666989,1.4835862307477667,Neutral
+2019-11-01,1511.4,380.99,-0.22,US,Non Farm Payrolls ,35.77981651376147,24.45414847161572,Negative
+2019-10-31,1514.8,390.01,1.21,US,Personal Income MoM ,0.0,0.0,Positive
+2019-10-30,1496.7,353.64,0.4,EA,Business Confidence ,17.5438596491228,69.47368421052632,Positive
+2019-10-29,1490.7,291.98,-0.34,,,1.097918675666989,1.4835862307477667,Neutral
+2019-10-28,1495.8,318.13,-0.63,,,1.097918675666989,1.4835862307477667,Neutral
+2019-10-25,1505.3,368.74,0.04,,,1.097918675666989,1.4835862307477667,Neutral
+2019-10-24,1504.7,305.01,0.6,US,Durable Goods Orders MoM ,0.6116207951070335,1.0172939979654119,Positive
+2019-10-23,1495.7,244.62,0.55,,,1.097918675666989,1.4835862307477667,Neutral
+2019-10-22,1487.5,208.97,-0.04,,,1.097918675666989,1.4835862307477667,Neutral
+2019-10-21,1488.1,284.29,-0.4,,,1.097918675666989,1.4835862307477667,Neutral
+2019-10-18,1494.1,232.55,-0.28,,,1.097918675666989,1.4835862307477667,Neutral
+2019-10-17,1498.3,305.67,0.29,JP,Inflation Rate YoY ,0.3976143141153082,0.3976143141153082,Positive
+2019-10-16,1494.0,367.9,0.71,US,Retail Sales MoM ,1.2,1.2,Positive
+2019-10-15,1483.5,317.99,-0.94,GB,Claimant Count Change ,22.222222222222214,12.58134490238611,Negative
+2019-10-14,1497.6,228.32,0.6,CN,Inflation Rate YoY ,0.1888574126534462,0.1888574126534462,Positive
+2019-10-11,1488.7,485.96,-0.81,,,1.097918675666989,1.4835862307477667,Neutral
+2019-10-10,1500.9,417.88,-0.79,US,Core Inflation Rate YoY ,0.0,0.0,Negative
+2019-10-09,1512.8,285.28,0.59,,,1.097918675666989,1.4835862307477667,Neutral
+2019-10-08,1503.9,371.44,-0.03,,,1.097918675666989,1.4835862307477667,Neutral
+2019-10-07,1504.4,257.78,-0.56,,,1.097918675666989,1.4835862307477667,Neutral
+2019-10-04,1512.9,344.79,-0.06,US,Balance of Trade ,0.7380073800737981,1.109057301293903,Negative
+2019-10-03,1513.8,408.74,0.39,,,1.097918675666989,1.4835862307477667,Neutral
+2019-10-02,1507.9,393.1,1.27,JP,Consumer Confidence ,1.097918675666989,4.60081190798375,Positive
+2019-10-01,1489.0,450.17,1.09,,,1.097918675666989,1.4835862307477667,Neutral
+2019-09-30,1472.9,439.71,-2.22,JP,Tankan Large Manufacturers Index,75.0,114.28571428571428,Negative
+2019-09-27,1506.4,451.93,-0.58,US,Durable Goods Orders MoM ,2.4193548387096775,2.8282828282828283,Negative
+2019-09-26,1515.2,378.29,0.19,GB,Gfk Consumer Confidence ,16.0,16.0,Positive
+2019-09-25,1512.3,481.46,-1.81,,,1.097918675666989,1.4835862307477667,Neutral
+2019-09-24,1540.2,424.86,0.57,,,1.097918675666989,1.4835862307477667,Neutral
+2019-09-23,1531.5,359.88,1.08,,,1.097918675666989,1.4835862307477667,Neutral
+2019-09-20,1515.1,284.39,0.59,,,1.097918675666989,1.4835862307477667,Neutral
+2019-09-19,1506.2,291.3,-0.63,JP,Inflation Rate YoY ,0.5946481665014867,0.9891196834817014,Negative
+2019-09-18,1515.8,364.96,0.16,GB,Inflation Rate YoY ,0.3861003861003858,0.3861003861003858,Positive
+2019-09-17,1513.4,336.63,0.13,JP,Balance of Trade ,89.41368078175894,103.90942862197063,Positive
+2019-09-16,1511.5,349.61,0.8,,,1.097918675666989,1.4835862307477667,Neutral
+2019-09-13,1499.5,364.42,-0.52,US,Retail Sales MoM ,0.3976143141153082,0.0,Negative
+2019-09-12,1507.4,491.47,0.28,US,Core Inflation Rate YoY ,0.1910219675262657,0.382409177820268,Positive
+2019-09-11,1503.2,308.79,0.27,,,1.097918675666989,1.4835862307477667,Neutral
+2019-09-10,1499.2,397.92,-0.79,GB,Claimant Count Change ,6.081081081081083,53.98230088495575,Negative
+2019-09-09,1511.1,317.52,-0.29,GB,Balance of Trade ,1.097918675666989,273.9960500329164,Negative
+2019-09-06,1515.5,544.87,-0.66,US,Non Farm Payrolls ,19.377162629757784,14.893617021276595,Negative
+2019-09-05,1525.5,606.4,-2.24,,,1.097918675666989,1.4835862307477667,Neutral
+2019-09-04,1560.4,412.35,0.49,US,Balance of Trade ,0.9389671361502347,1.127819548872183,Positive
+2019-09-03,1552.8,0.0,-0.2,,,1.097918675666989,1.4835862307477667,Neutral
+2019-09-02,1555.9,554.83,1.73,,,1.097918675666989,1.4835862307477667,Neutral
+2019-08-30,1529.4,330.85,-0.49,US,Personal Income MoM ,0.398406374501992,0.398406374501992,Negative
+2019-08-29,1536.9,455.6,-0.79,EA,Business Confidence ,5.042016806722689,68.13186813186813,Negative
+2019-08-28,1549.1,353.91,-0.17,,,1.097918675666989,1.4835862307477667,Neutral
+2019-08-27,1551.8,347.05,0.95,,,1.097918675666989,1.4835862307477667,Neutral
+2019-08-26,1537.2,411.67,-0.03,US,Durable Goods Orders MoM ,1.7424975798644728,2.526724975704568,Negative
+2019-08-23,1537.6,473.0,1.93,,,1.097918675666989,1.4835862307477667,Neutral
+2019-08-22,1508.5,279.41,-0.48,JP,Inflation Rate YoY ,0.0,0.5923000987166832,Negative
+2019-08-21,1515.7,245.9,0.0,CA,Inflation Rate YoY ,0.5785920925747347,0.3853564547206169,Neutral
+2019-08-20,1515.7,247.54,0.27,,,1.097918675666989,1.4835862307477667,Neutral
+2019-08-19,1511.6,295.83,-0.79,,,1.097918675666989,1.4835862307477667,Neutral
+2019-08-16,1523.6,322.46,-0.5,,,1.097918675666989,1.4835862307477667,Neutral
+2019-08-15,1531.2,436.12,0.22,US,Retail Sales MoM ,0.7920792079207921,0.7920792079207921,Positive
+2019-08-14,1527.8,484.19,0.9,GB,Inflation Rate YoY ,0.3846153846153849,0.19212295869356408,Positive
+2019-08-13,1514.1,616.74,-0.2,US,Core Inflation Rate YoY ,0.19175455417066106,0.19175455417066106,Negative
+2019-08-12,1517.2,355.1,0.58,,,1.097918675666989,1.4835862307477667,Neutral
+2019-08-09,1508.5,332.61,-0.07,GB,Balance of Trade ,1.097918675666989,7733.884297520662,Negative
+2019-08-08,1509.5,402.96,-0.66,CN,Inflation Rate YoY ,0.18957345971564,0.18957345971564,Negative
+2019-08-07,1519.6,651.55,2.39,CA,Ivey PMI s.a ,2.2181146025878054,4.485981308411226,Positive
+2019-08-06,1484.2,381.92,0.52,,,1.097918675666989,1.4835862307477667,Neutral
+2019-08-05,1476.5,534.19,1.3,,,1.097918675666989,1.4835862307477667,Neutral
+2019-08-02,1457.5,493.05,1.75,US,Balance of Trade ,1.1029411764705908,0.9182736455463728,Positive
+2019-08-01,1432.4,587.56,-0.38,,,1.097918675666989,1.4835862307477667,Neutral
+2019-07-31,1437.8,419.58,-0.28,JP,Consumer Confidence ,1.8111254851229053,8.020050125313292,Negative
+2019-07-30,1441.8,259.62,1.51,US,Personal Income MoM ,0.0,0.198609731876862,Positive
+2019-07-29,1420.4,224.27,0.08,CN,US-China Trade Talks,1.097918675666989,1.4835862307477667,Positive
+2019-07-26,1419.3,306.02,0.33,,,1.097918675666989,1.4835862307477667,Neutral
+2019-07-25,1414.7,489.39,-0.63,US,Durable Goods Orders MoM ,2.5316455696202533,2.5316455696202533,Negative
+2019-07-24,1423.6,318.16,0.13,,,1.097918675666989,1.4835862307477667,Neutral
+2019-07-23,1421.7,386.68,-0.36,,,1.097918675666989,1.4835862307477667,Neutral
+2019-07-22,1426.9,255.35,0.01,,,1.097918675666989,1.4835862307477667,Neutral
+2019-07-19,1426.7,530.02,-0.1,,,1.097918675666989,1.4835862307477667,Neutral
+2019-07-18,1428.1,481.33,0.34,JP,Inflation Rate YoY ,0.0,0.1970443349753695,Positive
+2019-07-17,1423.3,358.17,0.86,GB,Inflation Rate YoY ,0.0,0.19212295869356408,Positive
+2019-07-16,1411.2,334.82,-0.16,US,Retail Sales MoM ,0.5970149253731344,0.0,Negative
+2019-07-15,1413.5,243.38,0.09,,,1.097918675666989,1.4835862307477667,Neutral
+2019-07-12,1412.2,284.97,0.39,,,1.097918675666989,1.4835862307477667,Neutral
+2019-07-11,1406.7,400.09,-0.41,US,Core Inflation Rate YoY ,0.19212295869356408,0.19212295869356408,Negative
+2019-07-10,1412.5,443.5,0.86,GB,Balance of Trade,1.097918675666989,14.067278287461788,Positive
+2019-07-09,1400.5,287.18,0.04,CN,Inflation Rate YoY ,0.0,0.18993352326685678,Positive
+2019-07-08,1400.0,318.69,-0.24,,,1.097918675666989,1.4835862307477667,Neutral
+2019-07-05,1403.4,0.34,0.24,US,Non Farm Payrolls ,33.246753246753244,26.767676767676768,Positive
+2019-07-04,1400.1,577.38,-1.46,,,1.097918675666989,1.4835862307477667,Neutral
+2019-07-03,1420.9,419.61,0.92,US,Balance of Trade,2.7649769585253456,2.205882352941182,Positive
+2019-07-02,1408.0,383.25,1.35,,,1.097918675666989,1.4835862307477667,Neutral
+2019-07-01,1389.3,389.76,-1.73,JP,Consumer Confidence ,1.2674271229404308,5.217391304347812,Negative
+2019-06-28,1413.7,306.62,0.12,US,Personal Income MoM,0.3968253968253968,0.3968253968253968,Positive
+2019-06-27,1412.0,336.36,-0.24,EA,Business Confidence ,8.571428571428571,11.267605633802816,Negative
+2019-06-26,1415.4,421.95,-0.23,US,Durable Goods Orders MoM,2.434077079107505,3.0333670374115265,Negative
+2019-06-25,1418.7,643.59,0.04,,,1.097918675666989,1.4835862307477667,Neutral
+2019-06-24,1418.2,375.15,1.29,,,1.097918675666989,1.4835862307477667,Neutral
+2019-06-21,1400.1,518.89,0.23,,,1.097918675666989,1.4835862307477667,Neutral
+2019-06-20,1396.9,542.9,3.57,JP,Inflation Rate YoY,0.0,0.5899705014749264,Positive
+2019-06-19,1348.8,332.61,-0.14,GB,Inflation Rate YoY,0.0,0.19212295869356408,Negative
+2019-06-18,1350.7,376.27,0.58,JP,Balance of Trade,1.244024057985917,12.778603268945025,Positive
+2019-06-17,1342.9,238.71,-0.12,,,1.097918675666989,1.4835862307477667,Neutral
+2019-06-14,1344.5,358.45,0.06,US,Retail Sales MoM,0.1978239366963403,0.1978239366963403,Positive
+2019-06-13,1343.7,204.83,0.52,,,1.097918675666989,1.4835862307477667,Neutral
+2019-06-12,1336.8,234.46,0.42,US,Core Inflation Rate YoY,0.19212295869356408,0.19212295869356408,Positive
+2019-06-11,1331.2,215.15,0.14,GB,Claimant Count Change,1.2738853503184746,9.73451327433628,Positive
+2019-06-10,1329.3,228.03,-1.25,GB,Balance of Trade ,1.097918675666989,18.623481781376515,Negative
+2019-06-07,1346.1,331.29,0.25,US,Non Farm Payrolls,84.2911877394636,86.46616541353383,Positive
+2019-06-06,1342.7,263.09,0.68,US,Balance of Trade ,0.19900497512436677,0.7920792079208033,Positive
+2019-06-05,1333.6,413.47,0.37,,,1.097918675666989,1.4835862307477667,Neutral
+2019-06-04,1328.7,319.96,0.06,,,1.097918675666989,1.4835862307477667,Neutral
+2019-06-03,1327.9,363.4,1.28,,,1.097918675666989,1.4835862307477667,Neutral
+2019-05-31,1311.1,341.18,1.45,,,1.097918675666989,1.4835862307477667,Neutral
+2019-05-30,1292.4,284.02,0.89,US,Personal Income MoM ,0.3968253968253968,0.595829195630586,Positive
+2019-05-29,1281.0,189.69,0.07,,,1.097918675666989,1.4835862307477667,Neutral
+2019-05-28,1280.1,0.78,0.23,EA,Business Confidence,11.764705882352946,7.228915662650602,Positive
+2019-05-27,1277.1,362.16,-0.51,,,1.097918675666989,1.4835862307477667,Neutral
+2019-05-24,1283.6,218.71,-0.14,,,1.097918675666989,1.4835862307477667,Neutral
+2019-05-23,1285.4,330.16,0.88,US,Durable Goods Orders MoM ,0.20855057351407735,0.8316008316008316,Positive
+2019-05-22,1274.2,191.37,0.08,GB,Inflation Rate YoY ,0.19175455417066106,0.5774783445620795,Positive
+2019-05-21,1273.2,213.17,-0.32,JP,Balance of Trade ,107.93650793650794,126.93461307738454,Negative
+2019-05-20,1277.3,212.18,0.13,,,1.097918675666989,1.4835862307477667,Neutral
+2019-05-17,1275.7,264.57,-0.82,,,1.097918675666989,1.4835862307477667,Neutral
+2019-05-16,1286.2,282.07,-0.89,,,1.097918675666989,1.4835862307477667,Neutral
+2019-05-15,1297.8,247.52,0.12,US,Retail Sales MoM ,0.8,0.9990009990009991,Positive
+2019-05-14,1296.3,222.05,-0.42,GB,Claimant Count Change ,2.004008016032064,1.1834319526627246,Negative
+2019-05-13,1301.8,379.44,1.12,,,1.097918675666989,1.4835862307477667,Neutral
+2019-05-10,1287.4,238.64,0.17,,,1.097918675666989,1.4835862307477667,Neutral
+2019-05-09,1285.2,306.55,0.3,US,Balance of Trade ,0.4032258064516186,0.20181634712411992,Positive
+2019-05-08,1281.4,302.69,-0.33,CN,Inflation Rate YoY ,0.0,0.7648183556405354,Negative
+2019-05-07,1285.6,251.09,0.14,CA,Ivey PMI s.a ,5.27752502274795,4.347826086956519,Positive
+2019-05-06,1283.8,244.34,0.2,,,1.097918675666989,1.4835862307477667,Neutral
+2019-05-03,1281.3,280.32,0.73,,,1.097918675666989,1.4835862307477667,Neutral
+2019-05-02,1272.0,282.5,-0.95,,,1.097918675666989,1.4835862307477667,Neutral
+2019-05-01,1284.2,275.43,-0.12,,,1.097918675666989,1.4835862307477667,Neutral
+2019-04-30,1285.7,239.44,0.33,,,1.097918675666989,1.4835862307477667,Neutral
+2019-04-29,1281.5,208.96,-0.57,US,Personal Income MoM ,0.5970149253731344,0.398406374501992,Negative
+2019-04-26,1288.8,278.89,0.71,,,1.097918675666989,1.4835862307477667,Neutral
+2019-04-25,1279.7,237.15,0.02,US,Durable Goods Orders MoM ,3.6714975845410627,4.263565891472868,Positive
+2019-04-24,1279.4,246.05,0.49,,,1.097918675666989,1.4835862307477667,Neutral
+2019-04-23,1273.2,280.34,-0.34,,,1.097918675666989,1.4835862307477667,Neutral
+2019-04-22,1277.6,136.44,0.13,,,1.097918675666989,1.4835862307477667,Neutral
+2019-04-18,1276.0,229.63,-0.06,US,Retail Sales MoM ,1.3658536585365857,1.9569471624266144,Negative
+2019-04-17,1276.8,223.36,-0.03,US,Balance of Trade ,8.047105004906774,6.719367588932804,Negative
+2019-04-16,1277.2,326.51,-1.09,GB,Claimant Count Change ,33.67139959432049,135.86005830903792,Negative
+2019-04-15,1291.3,232.99,-0.3,,,1.097918675666989,1.4835862307477667,Neutral
+2019-04-12,1295.2,192.49,0.15,,,1.097918675666989,1.4835862307477667,Neutral
+2019-04-11,1293.3,324.74,-1.57,,,1.097918675666989,1.4835862307477667,Neutral
+2019-04-10,1313.9,218.88,0.43,US,Core Inflation Rate YoY ,0.19212295869356408,0.3838771593090208,Positive
+2019-04-09,1308.3,200.34,0.49,,,1.097918675666989,1.4835862307477667,Neutral
+2019-04-08,1301.9,207.57,0.49,JP,Consumer Confidence ,4.295942720763716,3.592814371257485,Positive
+2019-04-05,1295.6,231.45,0.1,US,Non Farm Payrolls ,8.488063660477453,9.6,Positive
+2019-04-04,1294.3,262.54,-0.08,CA,Ivey PMI s.a ,6.015037593984954,7.379375591296119,Negative
+2019-04-03,1295.3,190.37,-0.01,,,1.097918675666989,1.4835862307477667,Neutral
+2019-04-02,1295.4,196.4,0.09,US,Durable Goods Orders MoM ,0.41407867494823986,1.8423746161719552,Positive
+2019-04-01,1294.2,236.66,-0.33,US,Retail Sales MoM ,0.9990009990009991,0.8,Negative
+2019-03-29,1298.5,270.18,0.25,US,Personal Income MoM ,0.19900497512437815,0.0,Positive
+2019-03-28,1295.3,426.82,-1.15,EA,Business Confidence ,11.872146118721462,6.5727699530516395,Negative
+2019-03-27,1310.4,206.26,-0.35,US,Balance of Trade ,11.017740429505134,14.48212648945921,Negative
+2019-03-26,1315.0,267.17,-0.57,,,1.097918675666989,1.4835862307477667,Neutral
+2019-03-25,1322.6,251.98,0.78,,,1.097918675666989,1.4835862307477667,Neutral
+2019-03-22,1312.3,271.38,0.38,CA,Inflation Rate YoY ,0.194363459669582,0.0,Positive
+2019-03-21,1307.3,332.61,0.43,JP,Inflation Rate YoY ,0.19900497512437815,0.19940179461615157,Positive
+2019-03-20,1301.7,370.4,-0.37,GB,Inflation Rate YoY ,0.1928640308582451,0.1928640308582451,Negative
+2019-03-19,1306.5,206.9,0.38,GB,Claimant Count Change ,158.30618892508144,96.49595687331535,Positive
+2019-03-18,1301.5,176.49,-0.11,,,1.097918675666989,1.4835862307477667,Neutral
+2019-03-15,1302.9,234.65,0.6,,,1.097918675666989,1.4835862307477667,Neutral
+2019-03-14,1295.1,248.21,-1.08,,,1.097918675666989,1.4835862307477667,Neutral
+2019-03-13,1309.3,214.24,0.86,US,Durable Goods Orders MoM ,1.801801801801802,2.613065326633166,Positive
+2019-03-12,1298.1,203.89,0.54,US,Core Inflation Rate YoY ,0.19175455417066106,0.19175455417066106,Positive
+2019-03-11,1291.1,196.86,-0.63,US,Retail Sales MoM ,0.39920159680638717,0.19900497512437815,Negative
+2019-03-08,1299.3,283.84,1.03,US,Non Farm Payrolls ,159.2039800995025,161.13744075829385,Positive
+2019-03-07,1286.1,257.92,-0.12,,,1.097918675666989,1.4835862307477667,Neutral
+2019-03-06,1287.6,192.93,0.23,US,Balance of Trade ,3.256212510711223,6.620209059233445,Positive
+2019-03-05,1284.7,216.93,-0.22,,,1.097918675666989,1.4835862307477667,Neutral
+2019-03-04,1287.5,268.39,-0.9,CN,National People’s Congress,1.097918675666989,1.4835862307477667,Negative
+2019-03-01,1299.2,343.47,-1.28,US,Personal Income MoM ,1.183431952662722,1.183431952662722,Negative
+2019-02-28,1316.1,252.24,-0.39,CN,Caixin Manufacturing PMI ,2.8169014084507014,1.801801801801799,Negative
+2019-02-27,1321.2,198.04,-0.55,EA,Business Confidence ,7.860262008733622,6.956521739130432,Negative
+2019-02-26,1328.5,185.56,-0.08,,,1.097918675666989,1.4835862307477667,Neutral
+2019-02-25,1329.5,181.78,-0.25,,,1.097918675666989,1.4835862307477667,Neutral
+2019-02-22,1332.8,241.8,0.38,,,1.097918675666989,1.4835862307477667,Neutral
+2019-02-21,1327.8,285.81,-1.49,US,Durable Goods Orders MoM ,0.5842259006815967,2.507232401157185,Negative
+2019-02-20,1347.9,246.72,0.23,,,1.097918675666989,1.4835862307477667,Neutral
+2019-02-19,1344.8,348.64,0.0,GB,Claimant Count Change ,128.49162011173186,89.65517241379311,Neutral
+2019-02-18,1344.8,348.64,1.72,,,1.097918675666989,1.4835862307477667,Neutral
+2019-02-15,1322.1,200.28,0.62,,,1.097918675666989,1.4835862307477667,Neutral
+2019-02-14,1313.9,228.46,-0.09,US,Retail Sales MoM ,2.8282828282828283,3.027245206861756,Negative
+2019-02-13,1315.1,213.96,0.08,US,Core Inflation Rate YoY ,0.19175455417066106,0.3838771593090208,Positive
+2019-02-12,1314.0,146.45,0.16,,,1.097918675666989,1.4835862307477667,Neutral
+2019-02-11,1311.9,150.61,-0.5,GB,Balance of Trade ,1.097918675666989,64.37394042140956,Negative
+2019-02-08,1318.5,150.61,0.33,,,1.097918675666989,1.4835862307477667,Neutral
+2019-02-07,1314.2,166.76,-0.02,,,1.097918675666989,1.4835862307477667,Neutral
+2019-02-06,1314.4,137.25,-0.36,US,Balance of Trade ,9.188660801564033,7.305034550839097,Negative
+2019-02-05,1319.2,129.01,-0.01,,,1.097918675666989,1.4835862307477667,Neutral
+2019-02-04,1319.3,159.56,-0.21,,,1.097918675666989,1.4835862307477667,Neutral
+2019-02-01,1322.1,200.0,-0.23,US,Non Farm Payrolls ,59.148936170212764,56.42105263157895,Negative
+2019-01-31,1325.2,224.75,0.74,CN,Caixin Manufacturing PMI ,2.4291497975708563,3.4239677744209525,Positive
+2019-01-30,1315.5,272.11,0.5,EA,Business Confidence ,4.9180327868852505,4.9180327868852505,Positive
+2019-01-29,1308.9,213.61,0.45,,,1.097918675666989,1.4835862307477667,Neutral
+2019-01-28,1303.1,243.07,0.39,,,1.097918675666989,1.4835862307477667,Neutral
+2019-01-25,1298.1,303.84,1.43,,,1.097918675666989,1.4835862307477667,Neutral
+2019-01-24,1279.8,225.77,-0.33,,,1.097918675666989,1.4835862307477667,Neutral
+2019-01-23,1284.0,217.13,-0.14,,,1.097918675666989,1.4835862307477667,Neutral
+2019-01-22,1285.8,1.27,0.19,GB,Claimant Count Change ,3.827751196172252,67.9245283018868,Positive
+2019-01-21,1283.4,318.85,0.06,,,1.097918675666989,1.4835862307477667,Neutral
+2019-01-18,1282.6,225.57,-0.75,CA,Inflation Rate YoY ,0.5785920925747347,0.5785920925747347,Negative
+2019-01-17,1292.3,191.98,-0.12,JP,Inflation Rate YoY ,0.0,0.5946481665014867,Negative
+2019-01-16,1293.8,181.39,0.42,GB,Inflation Rate YoY ,0.0,0.19175455417066106,Positive
+2019-01-15,1288.4,242.07,-0.22,,,1.097918675666989,1.4835862307477667,Neutral
+2019-01-14,1291.3,221.89,0.14,,,1.097918675666989,1.4835862307477667,Neutral
+2019-01-11,1289.5,210.64,0.16,US,Core Inflation Rate YoY ,0.0,0.0,Positive
+2019-01-10,1287.4,239.92,-0.36,,,1.097918675666989,1.4835862307477667,Neutral
+2019-01-09,1292.0,245.97,0.47,CN,Inflation Rate YoY ,0.3846153846153849,0.5763688760806915,Positive
+2019-01-08,1285.9,221.92,-0.31,EA,Business Confidence ,12.099644128113882,19.17808219178083,Negative
+2019-01-07,1289.9,204.68,0.32,CA,Ivey PMI s.a ,4.936170212765967,5.110732538330494,Positive
+2019-01-04,1285.8,316.06,-0.7,US,Non Farm Payrolls ,55.10204081632652,61.50627615062761,Negative
+2019-01-03,1294.8,244.54,0.83,,,1.097918675666989,1.4835862307477667,Neutral
+2019-01-02,1284.1,235.33,0.22,,,1.097918675666989,1.4835862307477667,Neutral
diff --git a/The Effect of Economic News on Gold Prices Analysis/Images/Accuracies of Models.png b/The Effect of Economic News on Gold Prices Analysis/Images/Accuracies of Models.png
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diff --git a/The Effect of Economic News on Gold Prices Analysis/Model/README.md b/The Effect of Economic News on Gold Prices Analysis/Model/README.md
new file mode 100644
index 000000000..eed1486d9
--- /dev/null
+++ b/The Effect of Economic News on Gold Prices Analysis/Model/README.md	
@@ -0,0 +1,83 @@
+## **Advertisement Click Prediction**
+
+### 🎯 **Goal**
+To explore the intricate dance between gold prices and key economic events across major global players – Canada, Japan, USA, Russia, European Union, and China. 
+
+### 🧵 **Dataset**
+Link for the dataset used in the project: ['https://www.kaggle.com/datasets/fekihmea/the-effect-of-economic-news-on-gold-prices'](https://www.kaggle.com/datasets/fekihmea/the-effect-of-economic-news-on-gold-prices)
+
+### 🧾 **Description**
+Start with *Exploratory Data Analysis (EDA)* and *Data Visualization* to gain insights from the dataset. Then, we apply various machine learning algorithms to predict the change in the price of Gold based on the sentiment of the Event. Finally, we compare the accuracies of these algorithms to identify the best-performing model.
+
+### 🧮 **What I had done!**
+- Imported essential libraries for data manipulation and machine learning.
+- Conducted Exploratory Data Analysis (EDA) to comprehend the dataset.
+- Visualized data to extract meaningful patterns and insights.
+- Setup a function to assign Sentiment to a Event
+- Assessed feature correlations to understand interdependencies.
+- Converted categorical features into numerical formats via feature mapping.
+- Split the dataset into training and testing sets and applied scaling techniques.
+- Implemented and trained four machine learning models: **Random Forest**, **SVM**, **Logistic Regression**, and **Gradient Booster**.
+- Evaluated the models using classification report and compared their accuracies to determine the best-performing model.
+
+### 🚀 **Models Implemented**
+Model Building: We implemented the following algorithms for their distinct advantages in handling various aspects of the dataset:
+
+- Random Forest Classifier: Random forests or Random Decision Trees is a collaborative team of decision trees that work together to provide a single output.
+- SVM: Support vector machines are supervised max-margin models with associated learning algorithms that analyze data for classification and regression analysis.
+- Logistic Regression: Logistic regression is a supervised machine learning algorithm used for classification tasks where the goal is to predict the probability that an instance belongs to a given class or not.
+- Gradient Booster: Gradient Boosting is a powerful boosting algorithm that combines several weak learners into strong learners, in which each new model is trained to minimize the loss function such as mean squared error or cross-entropy of the previous model using gradient descent
+
+### 📚 **Libraries Needed**
+- Language Used
+  - Python
+- Libraries Used
+  - Pandas
+  - Seaborn
+  - Numpy
+  - Matplotlib
+  - Sklearn
+
+### 📊 **Exploratory Data Analysis Results**
+
+<table>
+    <tr>
+        <td><img src="https://github.com/fspzar123/ML-Crate/blob/48ce7189e52355c9ef268a87d9d4d160dbc55b28/The%20Effect%20of%20Economic%20News%20on%20Gold%20Prices%20Analysis/Images/Weekly-Gold.png" alt="Weekly Gold Prices"></td>
+        <td><img src="https://github.com/fspzar123/ML-Crate/blob/22465f62c53b71fd029d4c1b350ae3bd1eda3f1f/The%20Effect%20of%20Economic%20News%20on%20Gold%20Prices%20Analysis/Images/Avg%20Price%20by%20country.png" alt="Average Price by Country"></td>
+    </tr>
+    <tr>
+        <td><img src="https://github.com/fspzar123/ML-Crate/blob/22465f62c53b71fd029d4c1b350ae3bd1eda3f1f/The%20Effect%20of%20Economic%20News%20on%20Gold%20Prices%20Analysis/Images/Dist%20of%20price%20by%20country.png" alt="Distribution of Price by Country"></td>
+        <td><img src="https://github.com/fspzar123/ML-Crate/blob/22465f62c53b71fd029d4c1b350ae3bd1eda3f1f/The%20Effect%20of%20Economic%20News%20on%20Gold%20Prices%20Analysis/Images/Trend%20of%20Price%26Vol_K.png" alt="Trend of Price and Volume"></td>
+    </tr>
+    <tr>
+        <td colspan="2" style="text-align: center;"><img src="https://github.com/fspzar123/ML-Crate/blob/22465f62c53b71fd029d4c1b350ae3bd1eda3f1f/The%20Effect%20of%20Economic%20News%20on%20Gold%20Prices%20Analysis/Images/HeatMap%20Of%20Correlation.png" alt="Heatmap of Correlation" style="width: 70%;"></td>
+    </tr>
+    <tr>
+        <td colspan="2" style="text-align: center;"><img src="https://github.com/fspzar123/ML-Crate/blob/22465f62c53b71fd029d4c1b350ae3bd1eda3f1f/The%20Effect%20of%20Economic%20News%20on%20Gold%20Prices%20Analysis/Images/Dist%20of%20events%20per%20date.png" alt="Distribution of events per date" style="width: 70%;"></td>
+    </tr>
+</table>
+
+### 📈 **Performance of the Models based on the Accuracy Scores**
+
+<table>
+    <tr>
+        <td style="padding-right: 20px; vertical-align: top;">
+            <ul style="list-style-type: disc; margin: 0;">
+                <li>Random Forest Classifier - 99.5%</li>
+                <li>Support Vector Machines - 97.5%</li>
+                <li>Logistic Regression - 97%</li>
+                <li>Gradient Booster - 100%</li>
+            </ul>
+        </td>
+        <td style="vertical-align: top;">
+            <img src="https://github.com/fspzar123/ML-Crate/blob/22465f62c53b71fd029d4c1b350ae3bd1eda3f1f/The%20Effect%20of%20Economic%20News%20on%20Gold%20Prices%20Analysis/Images/Accuracies%20of%20Models.png" alt="Accuracies of Models" style="max-width: 200px; max-height: 200px;">
+        </td>
+    </tr>
+</table>
+
+
+### 📢 **Conclusion**
+Among all the models tested, the **Gradient Booster** achieved the highest accuracy,**100%**, making it the best-performing model for predicting gold prices. This demonstrates its effectiveness in handling the dataset and providing reliable predictions.
+
+### ✒️ **Your Signature**
+Created by [Filbert Shawn](https://github.com/fspzar123) as a part of SSOC'24 Season 3.
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diff --git a/The Effect of Economic News on Gold Prices Analysis/Model/project_folder.ipynb b/The Effect of Economic News on Gold Prices Analysis/Model/project_folder.ipynb
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index 000000000..5ae6164a4
--- /dev/null
+++ b/The Effect of Economic News on Gold Prices Analysis/Model/project_folder.ipynb	
@@ -0,0 +1,2762 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "from matplotlib import pyplot as plt\n",
+    "from matplotlib import colors"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Day</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Hour</th>\n",
+       "      <th>Country</th>\n",
+       "      <th>Event</th>\n",
+       "      <th>Actual</th>\n",
+       "      <th>Previous</th>\n",
+       "      <th>Consensus</th>\n",
+       "      <th>Forecast</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Tuesday</td>\n",
+       "      <td>01/01/19</td>\n",
+       "      <td>20:45</td>\n",
+       "      <td>CN</td>\n",
+       "      <td>Caixin Manufacturing PMI DEC</td>\n",
+       "      <td>49.7</td>\n",
+       "      <td>50.2</td>\n",
+       "      <td>50.1</td>\n",
+       "      <td>50.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Friday</td>\n",
+       "      <td>01/04/19</td>\n",
+       "      <td>8:30</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Non Farm Payrolls DEC</td>\n",
+       "      <td>312K</td>\n",
+       "      <td>176K</td>\n",
+       "      <td>177K</td>\n",
+       "      <td>165K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Sunday</td>\n",
+       "      <td>01/06/19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CN</td>\n",
+       "      <td>US-China Trade Talks</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Monday</td>\n",
+       "      <td>01/07/19</td>\n",
+       "      <td>10:00</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>Ivey PMI s.a DEC</td>\n",
+       "      <td>59.7</td>\n",
+       "      <td>57.2</td>\n",
+       "      <td>56.8</td>\n",
+       "      <td>56.7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Monday</td>\n",
+       "      <td>01/07/19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CN</td>\n",
+       "      <td>US-China Trade Talks</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1871</th>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>11/30/23</td>\n",
+       "      <td>8:30</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Personal Income MoM OCT</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.40%</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.003</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1872</th>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>11/30/23</td>\n",
+       "      <td>8:30</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Personal Spending MoM OCT</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.70%</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1873</th>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>11/30/23</td>\n",
+       "      <td>20:45</td>\n",
+       "      <td>CN</td>\n",
+       "      <td>Caixin Manufacturing PMI NOV</td>\n",
+       "      <td>50.7</td>\n",
+       "      <td>49.5</td>\n",
+       "      <td>49.8</td>\n",
+       "      <td>49.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1874</th>\n",
+       "      <td>Friday</td>\n",
+       "      <td>12/01/23</td>\n",
+       "      <td>8:30</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>Unemployment Rate NOV</td>\n",
+       "      <td>0.058</td>\n",
+       "      <td>5.70%</td>\n",
+       "      <td>0.058</td>\n",
+       "      <td>0.058</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1875</th>\n",
+       "      <td>Friday</td>\n",
+       "      <td>12/01/23</td>\n",
+       "      <td>10:00</td>\n",
+       "      <td>US</td>\n",
+       "      <td>ISM Manufacturing PMI NOV</td>\n",
+       "      <td>46.7</td>\n",
+       "      <td>46.7</td>\n",
+       "      <td>47.6</td>\n",
+       "      <td>47.2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1876 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           Day      Date   Hour Country                         Event Actual  \\\n",
+       "0      Tuesday  01/01/19  20:45      CN  Caixin Manufacturing PMI DEC   49.7   \n",
+       "1       Friday  01/04/19   8:30      US         Non Farm Payrolls DEC   312K   \n",
+       "2       Sunday  01/06/19    NaN      CN          US-China Trade Talks    NaN   \n",
+       "3       Monday  01/07/19  10:00      CA              Ivey PMI s.a DEC   59.7   \n",
+       "4       Monday  01/07/19    NaN      CN          US-China Trade Talks    NaN   \n",
+       "...        ...       ...    ...     ...                           ...    ...   \n",
+       "1871  Thursday  11/30/23   8:30      US       Personal Income MoM OCT  0.002   \n",
+       "1872  Thursday  11/30/23   8:30      US     Personal Spending MoM OCT  0.002   \n",
+       "1873  Thursday  11/30/23  20:45      CN  Caixin Manufacturing PMI NOV   50.7   \n",
+       "1874    Friday  12/01/23   8:30      CA         Unemployment Rate NOV  0.058   \n",
+       "1875    Friday  12/01/23  10:00      US     ISM Manufacturing PMI NOV   46.7   \n",
+       "\n",
+       "     Previous Consensus Forecast  \n",
+       "0        50.2      50.1     50.1  \n",
+       "1        176K      177K     165K  \n",
+       "2         NaN       NaN      NaN  \n",
+       "3        57.2      56.8     56.7  \n",
+       "4         NaN       NaN      NaN  \n",
+       "...       ...       ...      ...  \n",
+       "1871    0.40%     0.002    0.003  \n",
+       "1872    0.70%     0.002    0.004  \n",
+       "1873     49.5      49.8     49.8  \n",
+       "1874    5.70%     0.058    0.058  \n",
+       "1875     46.7      47.6     47.2  \n",
+       "\n",
+       "[1876 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "path = \"C:/Users/shawn/OneDrive/Documents/GitHub/ML-Crate/Dataset/\"\n",
+    "news = pd.read_csv(path + \"economic_calendar_19_24.csv\")\n",
+    "gold_price = pd.read_csv(path + \"gold_price_19_24.csv\")\n",
+    "news"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Price</th>\n",
+       "      <th>Open</th>\n",
+       "      <th>High</th>\n",
+       "      <th>Low</th>\n",
+       "      <th>Vol_K</th>\n",
+       "      <th>Change_percent</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>12/01/2023</td>\n",
+       "      <td>2089.7</td>\n",
+       "      <td>2056.5</td>\n",
+       "      <td>2095.7</td>\n",
+       "      <td>2052.6</td>\n",
+       "      <td>241.62</td>\n",
+       "      <td>1.58</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>11/30/2023</td>\n",
+       "      <td>2057.2</td>\n",
+       "      <td>2065.4</td>\n",
+       "      <td>2067.4</td>\n",
+       "      <td>2051.2</td>\n",
+       "      <td>151.92</td>\n",
+       "      <td>-0.48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>11/29/2023</td>\n",
+       "      <td>2067.1</td>\n",
+       "      <td>2062.0</td>\n",
+       "      <td>2072.7</td>\n",
+       "      <td>2055.9</td>\n",
+       "      <td>197.79</td>\n",
+       "      <td>0.81</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>11/28/2023</td>\n",
+       "      <td>2050.5</td>\n",
+       "      <td>2025.0</td>\n",
+       "      <td>2054.4</td>\n",
+       "      <td>2022.9</td>\n",
+       "      <td>1.86</td>\n",
+       "      <td>1.35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>11/27/2023</td>\n",
+       "      <td>2023.1</td>\n",
+       "      <td>2012.9</td>\n",
+       "      <td>2027.5</td>\n",
+       "      <td>2012.7</td>\n",
+       "      <td>1.06</td>\n",
+       "      <td>0.47</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1274</th>\n",
+       "      <td>01/08/2019</td>\n",
+       "      <td>1285.9</td>\n",
+       "      <td>1287.4</td>\n",
+       "      <td>1288.4</td>\n",
+       "      <td>1280.2</td>\n",
+       "      <td>221.92</td>\n",
+       "      <td>-0.31</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1275</th>\n",
+       "      <td>01/07/2019</td>\n",
+       "      <td>1289.9</td>\n",
+       "      <td>1290.2</td>\n",
+       "      <td>1297.0</td>\n",
+       "      <td>1287.3</td>\n",
+       "      <td>204.68</td>\n",
+       "      <td>0.32</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1276</th>\n",
+       "      <td>01/04/2019</td>\n",
+       "      <td>1285.8</td>\n",
+       "      <td>1298.9</td>\n",
+       "      <td>1300.0</td>\n",
+       "      <td>1278.1</td>\n",
+       "      <td>316.06</td>\n",
+       "      <td>-0.70</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1277</th>\n",
+       "      <td>01/03/2019</td>\n",
+       "      <td>1294.8</td>\n",
+       "      <td>1290.4</td>\n",
+       "      <td>1296.9</td>\n",
+       "      <td>1286.4</td>\n",
+       "      <td>244.54</td>\n",
+       "      <td>0.83</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1278</th>\n",
+       "      <td>01/02/2019</td>\n",
+       "      <td>1284.1</td>\n",
+       "      <td>1285.0</td>\n",
+       "      <td>1291.0</td>\n",
+       "      <td>1280.6</td>\n",
+       "      <td>235.33</td>\n",
+       "      <td>0.22</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1279 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Date   Price    Open    High     Low   Vol_K  Change_percent\n",
+       "0     12/01/2023  2089.7  2056.5  2095.7  2052.6  241.62            1.58\n",
+       "1     11/30/2023  2057.2  2065.4  2067.4  2051.2  151.92           -0.48\n",
+       "2     11/29/2023  2067.1  2062.0  2072.7  2055.9  197.79            0.81\n",
+       "3     11/28/2023  2050.5  2025.0  2054.4  2022.9    1.86            1.35\n",
+       "4     11/27/2023  2023.1  2012.9  2027.5  2012.7    1.06            0.47\n",
+       "...          ...     ...     ...     ...     ...     ...             ...\n",
+       "1274  01/08/2019  1285.9  1287.4  1288.4  1280.2  221.92           -0.31\n",
+       "1275  01/07/2019  1289.9  1290.2  1297.0  1287.3  204.68            0.32\n",
+       "1276  01/04/2019  1285.8  1298.9  1300.0  1278.1  316.06           -0.70\n",
+       "1277  01/03/2019  1294.8  1290.4  1296.9  1286.4  244.54            0.83\n",
+       "1278  01/02/2019  1284.1  1285.0  1291.0  1280.6  235.33            0.22\n",
+       "\n",
+       "[1279 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gold_price"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def outlier_thresholds(dataframe, variable):\n",
+    "    quartile1 = dataframe[variable].quantile(0.01)\n",
+    "    quartile3 = dataframe[variable].quantile(0.75)\n",
+    "    interquantile_range = quartile3 - quartile1\n",
+    "    up_limit = quartile3 + 1.5 * interquantile_range\n",
+    "    low_limit = quartile1 - 1.5 * interquantile_range\n",
+    "    return low_limit, up_limit"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def summary(df):\n",
+    "    missing_info = pd.DataFrame(df.isnull().sum(), columns=['Missing Values'])  \n",
+    "    data_types = pd.DataFrame(df.dtypes, columns=['Data Type'])\n",
+    "    summary_df = pd.concat([missing_info, data_types], axis=1)\n",
+    "    for column in df.columns:    \n",
+    "        if pd.api.types.is_object_dtype(df[column]):\n",
+    "            num_unique_choices = df[column].nunique()\n",
+    "            summary_df.loc[column, 'Unique Choices'] = num_unique_choices\n",
+    "        if pd.api.types.is_numeric_dtype(df[column]):\n",
+    "            low_limit, up_limit = outlier_thresholds(df, column)  \n",
+    "            summary_df.loc[column, 'min'] = df[column].min()\n",
+    "            summary_df.loc[column, 'max'] = df[column].max()            \n",
+    "            summary_df.loc[column, 'Mean'] = df[column].mean()\n",
+    "            summary_df.loc[column, 'Median'] = df[column].median()\n",
+    "            summary_df.loc[column, 'Variance'] = df[column].var()\n",
+    "            summary_df.loc[column, 'deviation'] = df[column].std()  \n",
+    "            num_outliers = len(df[(df[column] < low_limit) | (df[column] > up_limit)])\n",
+    "            summary_df.loc[column, 'Num Outliers'] = num_outliers \n",
+    "    return summary_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Missing Values</th>\n",
+       "      <th>Data Type</th>\n",
+       "      <th>Unique Choices</th>\n",
+       "      <th>min</th>\n",
+       "      <th>max</th>\n",
+       "      <th>Mean</th>\n",
+       "      <th>Median</th>\n",
+       "      <th>Variance</th>\n",
+       "      <th>deviation</th>\n",
+       "      <th>Num Outliers</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Date</th>\n",
+       "      <td>0</td>\n",
+       "      <td>object</td>\n",
+       "      <td>1279.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Price</th>\n",
+       "      <td>0</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1272.00</td>\n",
+       "      <td>2089.70</td>\n",
+       "      <td>1743.149062</td>\n",
+       "      <td>1797.700</td>\n",
+       "      <td>42242.879221</td>\n",
+       "      <td>205.530726</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Open</th>\n",
+       "      <td>0</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1272.30</td>\n",
+       "      <td>2076.40</td>\n",
+       "      <td>1743.342611</td>\n",
+       "      <td>1796.900</td>\n",
+       "      <td>42309.244310</td>\n",
+       "      <td>205.692110</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>High</th>\n",
+       "      <td>0</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1277.10</td>\n",
+       "      <td>2095.70</td>\n",
+       "      <td>1755.450665</td>\n",
+       "      <td>1810.200</td>\n",
+       "      <td>43006.633210</td>\n",
+       "      <td>207.380407</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Low</th>\n",
+       "      <td>0</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1267.30</td>\n",
+       "      <td>2055.90</td>\n",
+       "      <td>1730.448514</td>\n",
+       "      <td>1784.600</td>\n",
+       "      <td>41454.022138</td>\n",
+       "      <td>203.602608</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Vol_K</th>\n",
+       "      <td>15</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>813.41</td>\n",
+       "      <td>216.213473</td>\n",
+       "      <td>200.515</td>\n",
+       "      <td>12971.563973</td>\n",
+       "      <td>113.892774</td>\n",
+       "      <td>5.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Change_percent</th>\n",
+       "      <td>0</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-4.99</td>\n",
+       "      <td>5.95</td>\n",
+       "      <td>0.043206</td>\n",
+       "      <td>0.040</td>\n",
+       "      <td>0.966090</td>\n",
+       "      <td>0.982899</td>\n",
+       "      <td>2.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                Missing Values Data Type  Unique Choices      min      max  \\\n",
+       "Date                         0    object          1279.0      NaN      NaN   \n",
+       "Price                        0   float64             NaN  1272.00  2089.70   \n",
+       "Open                         0   float64             NaN  1272.30  2076.40   \n",
+       "High                         0   float64             NaN  1277.10  2095.70   \n",
+       "Low                          0   float64             NaN  1267.30  2055.90   \n",
+       "Vol_K                       15   float64             NaN     0.00   813.41   \n",
+       "Change_percent               0   float64             NaN    -4.99     5.95   \n",
+       "\n",
+       "                       Mean    Median      Variance   deviation  Num Outliers  \n",
+       "Date                    NaN       NaN           NaN         NaN           NaN  \n",
+       "Price           1743.149062  1797.700  42242.879221  205.530726           0.0  \n",
+       "Open            1743.342611  1796.900  42309.244310  205.692110           0.0  \n",
+       "High            1755.450665  1810.200  43006.633210  207.380407           0.0  \n",
+       "Low             1730.448514  1784.600  41454.022138  203.602608           0.0  \n",
+       "Vol_K            216.213473   200.515  12971.563973  113.892774           5.0  \n",
+       "Change_percent     0.043206     0.040      0.966090    0.982899           2.0  "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "summary(gold_price)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Note\n",
+    "* Vol_K: 05 outliers, and 15 missing Values.\n",
+    "* Change_percent: 02 outliers.\n",
+    "* Date: Type Object ."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gold_price.index = pd.to_datetime(gold_price['Date'])\n",
+    "gold_price.set_index(gold_price.index, inplace=True)\n",
+    "gold_price.drop(columns=['Date'], inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x1709c2c7410>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1600x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "weekly_gold_prices = gold_price.resample('W').last() \n",
+    "plt.figure(figsize=(16, 6))\n",
+    "plt.plot(weekly_gold_prices.index, weekly_gold_prices['Price'], label='Weekly Gold Prices', color='#ffd700', marker='+')\n",
+    "plt.title('Weekly Gold Prices (2019-2023)', fontsize=16, fontweight='bold')\n",
+    "plt.xlabel('Date', fontsize=12)\n",
+    "plt.ylabel('Gold Price', fontsize=12)\n",
+    "plt.grid(True, linestyle='--', alpha=0.7)\n",
+    "plt.legend(loc='upper left')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Day</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Hour</th>\n",
+       "      <th>Country</th>\n",
+       "      <th>Event</th>\n",
+       "      <th>Actual</th>\n",
+       "      <th>Previous</th>\n",
+       "      <th>Consensus</th>\n",
+       "      <th>Forecast</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Tuesday</td>\n",
+       "      <td>01/01/19</td>\n",
+       "      <td>20:45</td>\n",
+       "      <td>CN</td>\n",
+       "      <td>Caixin Manufacturing PMI DEC</td>\n",
+       "      <td>49.7</td>\n",
+       "      <td>50.2</td>\n",
+       "      <td>50.1</td>\n",
+       "      <td>50.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Friday</td>\n",
+       "      <td>01/04/19</td>\n",
+       "      <td>8:30</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Non Farm Payrolls DEC</td>\n",
+       "      <td>312K</td>\n",
+       "      <td>176K</td>\n",
+       "      <td>177K</td>\n",
+       "      <td>165K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Sunday</td>\n",
+       "      <td>01/06/19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CN</td>\n",
+       "      <td>US-China Trade Talks</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Monday</td>\n",
+       "      <td>01/07/19</td>\n",
+       "      <td>10:00</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>Ivey PMI s.a DEC</td>\n",
+       "      <td>59.7</td>\n",
+       "      <td>57.2</td>\n",
+       "      <td>56.8</td>\n",
+       "      <td>56.7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Monday</td>\n",
+       "      <td>01/07/19</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CN</td>\n",
+       "      <td>US-China Trade Talks</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Day      Date   Hour Country                         Event Actual  \\\n",
+       "0  Tuesday  01/01/19  20:45      CN  Caixin Manufacturing PMI DEC   49.7   \n",
+       "1   Friday  01/04/19   8:30      US         Non Farm Payrolls DEC   312K   \n",
+       "2   Sunday  01/06/19    NaN      CN          US-China Trade Talks    NaN   \n",
+       "3   Monday  01/07/19  10:00      CA              Ivey PMI s.a DEC   59.7   \n",
+       "4   Monday  01/07/19    NaN      CN          US-China Trade Talks    NaN   \n",
+       "\n",
+       "  Previous Consensus Forecast  \n",
+       "0     50.2      50.1     50.1  \n",
+       "1     176K      177K     165K  \n",
+       "2      NaN       NaN      NaN  \n",
+       "3     57.2      56.8     56.7  \n",
+       "4      NaN       NaN      NaN  "
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "news.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(1876, 9)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Missing Values</th>\n",
+       "      <th>Data Type</th>\n",
+       "      <th>Unique Choices</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Day</th>\n",
+       "      <td>0</td>\n",
+       "      <td>object</td>\n",
+       "      <td>7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</th>\n",
+       "      <td>0</td>\n",
+       "      <td>object</td>\n",
+       "      <td>888.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Hour</th>\n",
+       "      <td>41</td>\n",
+       "      <td>object</td>\n",
+       "      <td>55.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Country</th>\n",
+       "      <td>0</td>\n",
+       "      <td>object</td>\n",
+       "      <td>7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Event</th>\n",
+       "      <td>0</td>\n",
+       "      <td>object</td>\n",
+       "      <td>479.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Actual</th>\n",
+       "      <td>153</td>\n",
+       "      <td>object</td>\n",
+       "      <td>768.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Previous</th>\n",
+       "      <td>154</td>\n",
+       "      <td>object</td>\n",
+       "      <td>787.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Consensus</th>\n",
+       "      <td>356</td>\n",
+       "      <td>object</td>\n",
+       "      <td>592.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Forecast</th>\n",
+       "      <td>157</td>\n",
+       "      <td>object</td>\n",
+       "      <td>671.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           Missing Values Data Type  Unique Choices\n",
+       "Day                     0    object             7.0\n",
+       "Date                    0    object           888.0\n",
+       "Hour                   41    object            55.0\n",
+       "Country                 0    object             7.0\n",
+       "Event                   0    object           479.0\n",
+       "Actual                153    object           768.0\n",
+       "Previous              154    object           787.0\n",
+       "Consensus             356    object           592.0\n",
+       "Forecast              157    object           671.0"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(news.shape)\n",
+    "summary(news)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Notes -\n",
+    "* All data types is object\n",
+    "* 888 unique dates from 1876 Dates i.e (each date can have many rows (Events))\n",
+    "* Missing values in ( Actual, Previous, Consensus, Forecast ) columns\n",
+    "* There is 479 in Event (Deduplication. example (Consumer Confidence DEC and Consumer Confidence JAN)\n",
+    "* The columns( Actual, Previous, Consensus, Forecast ) (Contain chars (%, M, B, K). example (Consumer Confidence DEC and Consumer Confidence JAN)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['\\xa0DEC', 'alks', '\\xa0NOV', '\\xa0JAN', '\\xa0FEB', 'ress',\n",
+       "       '\\xa0MAR', 'x\\xa0Q1', '\\xa0APR', 'e\\xa005', 'I\\xa005', 'a\\xa005',\n",
+       "       's\\xa005', 'Y\\xa005', 'M\\xa005', '\\xa0JUN', 'x\\xa0Q2', '\\xa0JUL',\n",
+       "       '\\xa0AUG', 'e 1Y', '\\xa0SEP', 'x\\xa0Q3', '\\xa0OCT', 'x\\xa0Q4',\n",
+       "       'utes', 'ture', 'line', '2019', 'ting', 'ech\\xa0', 'ence', '2020',\n",
+       "       'irus', 'kage', 'l\\xa005', 'dget', 'Plan', 'tion', 'ring',\n",
+       "       'age\\xa0', 'ions', 'mony', 'sing', 'port', '-FEB', 'asts',\n",
+       "       'h\\xa005', 'kets', 'king', 'arty', 'ment', 'sion', 'Rate',\n",
+       "       'Y\\xa0Q4', 'v\\xa0Q4', 'h\\xa0Q4', 'l\\xa0Q4', 'Q\\xa0Q4', 'tem\\xa0',\n",
+       "       'Y\\xa0Q1', 'v\\xa0Q1', 'h\\xa0Q1', 'l\\xa0Q1', 'Q\\xa0Q1', 'Y\\xa0Q2',\n",
+       "       'v\\xa0Q2', 'h\\xa0Q2', 'l\\xa0Q2', 't\\xa0Q2', 'Q\\xa0Q2', 'Y\\xa0Q3',\n",
+       "       'v\\xa0Q3', 'h\\xa0Q3', 'l\\xa0Q3', 't\\xa0Q3', 'Q\\xa0Q3'],\n",
+       "      dtype=object)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "news['Event'].apply(lambda x: x[-4:]).unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Down to 144 Unique values for Event columns\n"
+     ]
+    }
+   ],
+   "source": [
+    "def remove_suffix(event):\n",
+    "    if event.endswith(('\\xa0JAN','\\xa0FEB','\\xa0MAR','\\xa0APR','\\xa005',\n",
+    "        '\\xa0JUN','\\xa0JUL','\\xa0AUG','\\xa0SEP','\\xa0OCT','\\xa0NOV',\n",
+    "                       '\\xa0DEC','\\xa0Q1','\\xa0Q2','\\xa0Q3','\\xa0Q4')):\n",
+    "        return event[:-3]\n",
+    "    else:\n",
+    "        return event\n",
+    "news['Event'] = news['Event'].apply(remove_suffix)\n",
+    "print(f\"Down to {len(news['Event'].unique())} Unique values for Event columns\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\shawn\\AppData\\Local\\Temp\\ipykernel_3588\\1052689142.py:2: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
+      "  percentage_mask.fillna(False, inplace=True)\n"
+     ]
+    }
+   ],
+   "source": [
+    "percentage_mask = news['Previous'].str.endswith('%')\n",
+    "percentage_mask.fillna(False, inplace=True)\n",
+    "news['Previous'] = news['Previous'].str.rstrip('%')\n",
+    "news.loc[percentage_mask, 'Previous'] = pd.to_numeric(news.loc[percentage_mask, 'Previous'], errors='coerce') / 100.0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create a new column 'Multiplier' based on 'Previous' values\n",
+    "news['Multiplier'] = news['Previous'].str.extract(r'([BKM])', expand=False)\n",
+    "\n",
+    "news['Previous'] = news['Previous'].str.replace(r'[BKM]', '', regex=True).astype(float)\n",
+    "news['Actual'] = news['Actual'].str.replace(r'[BKM]', '', regex=True).astype(float)\n",
+    "news['Consensus'] = news['Consensus'].str.replace(r'[BKM]', '', regex=True).astype(float)\n",
+    "news['Forecast'] = news['Forecast'].str.replace(r'[BKM]', '', regex=True).astype(float)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\shawn\\AppData\\Local\\Temp\\ipykernel_3588\\3036244955.py:9: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
+      "  news['Date'] = pd.to_datetime(news['Date'])\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Function to calculate percentage difference\n",
+    "def calculate_percentage_difference(row, value_column, actual_column):\n",
+    "    return abs((row[value_column] - row[actual_column]) / ((row[value_column] + row[actual_column] + 1) / 2)) * 100\n",
+    "\n",
+    "# Apply the function to each row and create new columns 'D_Consensus' and 'D_Forecast'\n",
+    "news['D_Consensus'] = news.apply(lambda row: calculate_percentage_difference(row, 'Consensus', 'Actual'), axis=1)\n",
+    "news['D_Forecast'] = news.apply(lambda row: calculate_percentage_difference(row, 'Forecast', 'Actual'), axis=1)\n",
+    "\n",
+    "news['Date'] = pd.to_datetime(news['Date'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Missing Values</th>\n",
+       "      <th>Data Type</th>\n",
+       "      <th>Unique Choices</th>\n",
+       "      <th>min</th>\n",
+       "      <th>max</th>\n",
+       "      <th>Mean</th>\n",
+       "      <th>Median</th>\n",
+       "      <th>Variance</th>\n",
+       "      <th>deviation</th>\n",
+       "      <th>Num Outliers</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Day</th>\n",
+       "      <td>0</td>\n",
+       "      <td>object</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</th>\n",
+       "      <td>0</td>\n",
+       "      <td>datetime64[ns]</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Hour</th>\n",
+       "      <td>41</td>\n",
+       "      <td>object</td>\n",
+       "      <td>55.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Country</th>\n",
+       "      <td>0</td>\n",
+       "      <td>object</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Event</th>\n",
+       "      <td>0</td>\n",
+       "      <td>object</td>\n",
+       "      <td>144.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Actual</th>\n",
+       "      <td>153</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-20500.0</td>\n",
+       "      <td>4800.000000</td>\n",
+       "      <td>-4.705783</td>\n",
+       "      <td>0.035000</td>\n",
+       "      <td>310961.105749</td>\n",
+       "      <td>557.638867</td>\n",
+       "      <td>7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Previous</th>\n",
+       "      <td>1055</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-20687.0</td>\n",
+       "      <td>4800.000000</td>\n",
+       "      <td>-9.164140</td>\n",
+       "      <td>34.100000</td>\n",
+       "      <td>666068.985029</td>\n",
+       "      <td>816.130495</td>\n",
+       "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Consensus</th>\n",
+       "      <td>356</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-22000.0</td>\n",
+       "      <td>3000.000000</td>\n",
+       "      <td>-15.208312</td>\n",
+       "      <td>0.031000</td>\n",
+       "      <td>418879.382158</td>\n",
+       "      <td>647.208917</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Forecast</th>\n",
+       "      <td>157</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-21780.0</td>\n",
+       "      <td>2900.000000</td>\n",
+       "      <td>-11.254396</td>\n",
+       "      <td>0.032000</td>\n",
+       "      <td>365741.781013</td>\n",
+       "      <td>604.765889</td>\n",
+       "      <td>6.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Multiplier</th>\n",
+       "      <td>1486</td>\n",
+       "      <td>object</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>D_Consensus</th>\n",
+       "      <td>356</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>17600.000000</td>\n",
+       "      <td>32.507795</td>\n",
+       "      <td>0.830565</td>\n",
+       "      <td>248035.454155</td>\n",
+       "      <td>498.031579</td>\n",
+       "      <td>238.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>D_Forecast</th>\n",
+       "      <td>157</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>7733.884298</td>\n",
+       "      <td>34.772847</td>\n",
+       "      <td>1.181102</td>\n",
+       "      <td>66839.635570</td>\n",
+       "      <td>258.533626</td>\n",
+       "      <td>282.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             Missing Values       Data Type  Unique Choices      min  \\\n",
+       "Day                       0          object             7.0      NaN   \n",
+       "Date                      0  datetime64[ns]             NaN      NaN   \n",
+       "Hour                     41          object            55.0      NaN   \n",
+       "Country                   0          object             7.0      NaN   \n",
+       "Event                     0          object           144.0      NaN   \n",
+       "Actual                  153         float64             NaN -20500.0   \n",
+       "Previous               1055         float64             NaN -20687.0   \n",
+       "Consensus               356         float64             NaN -22000.0   \n",
+       "Forecast                157         float64             NaN -21780.0   \n",
+       "Multiplier             1486          object             3.0      NaN   \n",
+       "D_Consensus             356         float64             NaN      0.0   \n",
+       "D_Forecast              157         float64             NaN      0.0   \n",
+       "\n",
+       "                      max       Mean     Median       Variance   deviation  \\\n",
+       "Day                   NaN        NaN        NaN            NaN         NaN   \n",
+       "Date                  NaN        NaN        NaN            NaN         NaN   \n",
+       "Hour                  NaN        NaN        NaN            NaN         NaN   \n",
+       "Country               NaN        NaN        NaN            NaN         NaN   \n",
+       "Event                 NaN        NaN        NaN            NaN         NaN   \n",
+       "Actual        4800.000000  -4.705783   0.035000  310961.105749  557.638867   \n",
+       "Previous      4800.000000  -9.164140  34.100000  666068.985029  816.130495   \n",
+       "Consensus     3000.000000 -15.208312   0.031000  418879.382158  647.208917   \n",
+       "Forecast      2900.000000 -11.254396   0.032000  365741.781013  604.765889   \n",
+       "Multiplier            NaN        NaN        NaN            NaN         NaN   \n",
+       "D_Consensus  17600.000000  32.507795   0.830565  248035.454155  498.031579   \n",
+       "D_Forecast    7733.884298  34.772847   1.181102   66839.635570  258.533626   \n",
+       "\n",
+       "             Num Outliers  \n",
+       "Day                   NaN  \n",
+       "Date                  NaN  \n",
+       "Hour                  NaN  \n",
+       "Country               NaN  \n",
+       "Event                 NaN  \n",
+       "Actual                7.0  \n",
+       "Previous              3.0  \n",
+       "Consensus             4.0  \n",
+       "Forecast              6.0  \n",
+       "Multiplier            NaN  \n",
+       "D_Consensus         238.0  \n",
+       "D_Forecast          282.0  "
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "summary(news)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1500x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "There are 394 dates with one event.\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "# Define a custom color palette with copper tones\n",
+    "custom_palette = [\"#FFD700\", \"#B87333\", \"#CD7F32\", \"#D2691E\", \"#BC8F8F\", \"#A52A2A\", \"#8B4513\"]\n",
+    "\n",
+    "date_event_counts = news.groupby('Date')['Event'].nunique()\n",
+    "# Count the occurrences of each event count\n",
+    "event_count_distribution = date_event_counts.value_counts().sort_index()\n",
+    "\n",
+    "# Plot the bar chart with the copper tone color palette\n",
+    "plt.figure(figsize=(15, 3))\n",
+    "event_count_distribution.plot(kind='bar', color=custom_palette, edgecolor='black')\n",
+    "plt.title('Distribution of Events per Date')\n",
+    "plt.xlabel('Number of Events')\n",
+    "plt.ylabel('Count of Dates')\n",
+    "plt.show()\n",
+    "\n",
+    "print(f\"There are {event_count_distribution[1]} dates with one event.\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Associate one Date with One Event"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\shawn\\AppData\\Local\\Temp\\ipykernel_3588\\2166861275.py:8: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  news.drop(columns=['Country_Priority'], inplace=True)\n"
+     ]
+    }
+   ],
+   "source": [
+    "country_priority = {'US': 1, 'EA': 2, 'GB': 3, 'JP': 4, 'CA': 5, 'CN': 6, 'RU': 7}\n",
+    "news['Country_Priority'] = news['Country'].map(country_priority)\n",
+    "# Sort by 'Country_Priority' and 'Date'\n",
+    "news.sort_values(by=['Country_Priority', 'Date'], inplace=True)\n",
+    "# Drop duplicates based on 'Date', keeping the first occurrence\n",
+    "news = news.drop_duplicates(subset='Date', keep='first')\n",
+    "# Drop the 'Country_Priority' column if you don't need it in the final result\n",
+    "news.drop(columns=['Country_Priority'], inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(1279, 18)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Price</th>\n",
+       "      <th>Vol_K</th>\n",
+       "      <th>Change_percent</th>\n",
+       "      <th>Country</th>\n",
+       "      <th>Event</th>\n",
+       "      <th>D_Consensus</th>\n",
+       "      <th>D_Forecast</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2023-12-01</td>\n",
+       "      <td>2089.7</td>\n",
+       "      <td>241.62</td>\n",
+       "      <td>1.58</td>\n",
+       "      <td>US</td>\n",
+       "      <td>ISM Manufacturing PMI</td>\n",
+       "      <td>1.888772</td>\n",
+       "      <td>1.053741</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2023-11-30</td>\n",
+       "      <td>2057.2</td>\n",
+       "      <td>151.92</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Core PCE Price Index MoM</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.199005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2023-11-29</td>\n",
+       "      <td>2067.1</td>\n",
+       "      <td>197.79</td>\n",
+       "      <td>0.81</td>\n",
+       "      <td>US</td>\n",
+       "      <td>GDP Growth Rate QoQ 2nd Est</td>\n",
+       "      <td>0.362976</td>\n",
+       "      <td>0.544959</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2023-11-28</td>\n",
+       "      <td>2050.5</td>\n",
+       "      <td>1.86</td>\n",
+       "      <td>1.35</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2023-11-27</td>\n",
+       "      <td>2023.1</td>\n",
+       "      <td>1.06</td>\n",
+       "      <td>0.47</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Date   Price   Vol_K  Change_percent Country  \\\n",
+       "0 2023-12-01  2089.7  241.62            1.58      US   \n",
+       "1 2023-11-30  2057.2  151.92           -0.48      US   \n",
+       "2 2023-11-29  2067.1  197.79            0.81      US   \n",
+       "3 2023-11-28  2050.5    1.86            1.35     NaN   \n",
+       "4 2023-11-27  2023.1    1.06            0.47     NaN   \n",
+       "\n",
+       "                         Event  D_Consensus  D_Forecast  \n",
+       "0       ISM Manufacturing PMI      1.888772    1.053741  \n",
+       "1    Core PCE Price Index MoM      0.000000    0.199005  \n",
+       "2  GDP Growth Rate QoQ 2nd Est     0.362976    0.544959  \n",
+       "3                          NaN          NaN         NaN  \n",
+       "4                          NaN          NaN         NaN  "
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Merge based on the 'Date' column\n",
+    "data = pd.merge(gold_price, news, on='Date', how='left')\n",
+    "print(data.shape)\n",
+    "data = data[[\"Date\", \"Price\", \"Vol_K\", \"Change_percent\", \"Country\", \"Event\", \"D_Consensus\", \"D_Forecast\"]]\n",
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Date</th>\n",
+       "      <th>Price</th>\n",
+       "      <th>Vol_K</th>\n",
+       "      <th>Change_percent</th>\n",
+       "      <th>Country</th>\n",
+       "      <th>Event</th>\n",
+       "      <th>D_Consensus</th>\n",
+       "      <th>D_Forecast</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2023-12-01</td>\n",
+       "      <td>2089.70</td>\n",
+       "      <td>241.62</td>\n",
+       "      <td>1.58</td>\n",
+       "      <td>US</td>\n",
+       "      <td>ISM Manufacturing PMI</td>\n",
+       "      <td>1.888772</td>\n",
+       "      <td>1.053741</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2023-11-30</td>\n",
+       "      <td>2057.20</td>\n",
+       "      <td>151.92</td>\n",
+       "      <td>-0.48</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Core PCE Price Index MoM</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.199005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2023-11-29</td>\n",
+       "      <td>2067.10</td>\n",
+       "      <td>197.79</td>\n",
+       "      <td>0.81</td>\n",
+       "      <td>US</td>\n",
+       "      <td>GDP Growth Rate QoQ 2nd Est</td>\n",
+       "      <td>0.362976</td>\n",
+       "      <td>0.544959</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2023-11-28</td>\n",
+       "      <td>2050.50</td>\n",
+       "      <td>1.86</td>\n",
+       "      <td>1.35</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2023-11-27</td>\n",
+       "      <td>2023.10</td>\n",
+       "      <td>1.06</td>\n",
+       "      <td>0.47</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2023-11-24</td>\n",
+       "      <td>2013.70</td>\n",
+       "      <td>0.52</td>\n",
+       "      <td>0.95</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2023-11-23</td>\n",
+       "      <td>1994.75</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-0.43</td>\n",
+       "      <td>JP</td>\n",
+       "      <td>Inflation Rate YoY</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.187793</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2023-11-22</td>\n",
+       "      <td>2003.40</td>\n",
+       "      <td>0.67</td>\n",
+       "      <td>-0.43</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Durable Goods Orders MoM</td>\n",
+       "      <td>5.027322</td>\n",
+       "      <td>5.664488</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2023-11-21</td>\n",
+       "      <td>2012.00</td>\n",
+       "      <td>0.67</td>\n",
+       "      <td>1.07</td>\n",
+       "      <td>US</td>\n",
+       "      <td>FOMC Minutes</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2023-11-20</td>\n",
+       "      <td>1990.70</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.30</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2023-11-17</td>\n",
+       "      <td>1984.70</td>\n",
+       "      <td>133.12</td>\n",
+       "      <td>-0.13</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Building Permits Prel</td>\n",
+       "      <td>1.879604</td>\n",
+       "      <td>1.879604</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2023-11-16</td>\n",
+       "      <td>1987.30</td>\n",
+       "      <td>186.81</td>\n",
+       "      <td>1.17</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2023-11-15</td>\n",
+       "      <td>1964.30</td>\n",
+       "      <td>142.92</td>\n",
+       "      <td>-0.11</td>\n",
+       "      <td>US</td>\n",
+       "      <td>PPI MoM</td>\n",
+       "      <td>1.204819</td>\n",
+       "      <td>1.204819</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2023-11-14</td>\n",
+       "      <td>1966.50</td>\n",
+       "      <td>180.74</td>\n",
+       "      <td>0.84</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Core Inflation Rate MoM</td>\n",
+       "      <td>0.199005</td>\n",
+       "      <td>0.199005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2023-11-13</td>\n",
+       "      <td>1950.20</td>\n",
+       "      <td>183.70</td>\n",
+       "      <td>0.65</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2023-11-10</td>\n",
+       "      <td>1937.70</td>\n",
+       "      <td>229.64</td>\n",
+       "      <td>-1.63</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Michigan Consumer Sentiment Prel</td>\n",
+       "      <td>5.275779</td>\n",
+       "      <td>6.050955</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2023-11-09</td>\n",
+       "      <td>1969.80</td>\n",
+       "      <td>214.08</td>\n",
+       "      <td>0.61</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Fed Chair Powell Speech</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2023-11-08</td>\n",
+       "      <td>1957.80</td>\n",
+       "      <td>189.36</td>\n",
+       "      <td>-0.80</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Fed Chair Powell Speech</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2023-11-07</td>\n",
+       "      <td>1973.50</td>\n",
+       "      <td>218.95</td>\n",
+       "      <td>-0.76</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2023-11-06</td>\n",
+       "      <td>1988.60</td>\n",
+       "      <td>146.28</td>\n",
+       "      <td>-0.53</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>Ivey PMI s.a</td>\n",
+       "      <td>1.107011</td>\n",
+       "      <td>2.441315</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2023-11-03</td>\n",
+       "      <td>1999.20</td>\n",
+       "      <td>222.19</td>\n",
+       "      <td>0.29</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Non Farm Payrolls</td>\n",
+       "      <td>18.126888</td>\n",
+       "      <td>23.460411</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>2023-11-02</td>\n",
+       "      <td>1993.50</td>\n",
+       "      <td>158.65</td>\n",
+       "      <td>0.30</td>\n",
+       "      <td>GB</td>\n",
+       "      <td>BoE Interest Rate Decision</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>2023-11-01</td>\n",
+       "      <td>1987.50</td>\n",
+       "      <td>197.63</td>\n",
+       "      <td>-0.34</td>\n",
+       "      <td>US</td>\n",
+       "      <td>ISM Manufacturing PMI</td>\n",
+       "      <td>4.756980</td>\n",
+       "      <td>5.761317</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>2023-10-31</td>\n",
+       "      <td>1994.30</td>\n",
+       "      <td>214.78</td>\n",
+       "      <td>-0.56</td>\n",
+       "      <td>EA</td>\n",
+       "      <td>GDP Growth Rate QoQ Flash</td>\n",
+       "      <td>0.200200</td>\n",
+       "      <td>0.200200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>2023-10-30</td>\n",
+       "      <td>2005.60</td>\n",
+       "      <td>181.34</td>\n",
+       "      <td>0.83</td>\n",
+       "      <td>JP</td>\n",
+       "      <td>BoJ Interest Rate Decision</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>2023-10-27</td>\n",
+       "      <td>1989.00</td>\n",
+       "      <td>0.37</td>\n",
+       "      <td>0.06</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Core PCE Price Index MoM</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.199005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>2023-10-26</td>\n",
+       "      <td>1987.90</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>0.12</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Durable Goods Orders MoM</td>\n",
+       "      <td>5.639098</td>\n",
+       "      <td>6.805293</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>2023-10-25</td>\n",
+       "      <td>1985.50</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.44</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Fed Chair Powell Speech</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>2023-10-24</td>\n",
+       "      <td>1976.80</td>\n",
+       "      <td>1.23</td>\n",
+       "      <td>-0.07</td>\n",
+       "      <td>GB</td>\n",
+       "      <td>Unemployment Rate - Adjusted</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>2023-10-23</td>\n",
+       "      <td>1978.20</td>\n",
+       "      <td>0.45</td>\n",
+       "      <td>-0.81</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Date    Price   Vol_K  Change_percent Country  \\\n",
+       "0  2023-12-01  2089.70  241.62            1.58      US   \n",
+       "1  2023-11-30  2057.20  151.92           -0.48      US   \n",
+       "2  2023-11-29  2067.10  197.79            0.81      US   \n",
+       "3  2023-11-28  2050.50    1.86            1.35     NaN   \n",
+       "4  2023-11-27  2023.10    1.06            0.47     NaN   \n",
+       "5  2023-11-24  2013.70    0.52            0.95     NaN   \n",
+       "6  2023-11-23  1994.75     NaN           -0.43      JP   \n",
+       "7  2023-11-22  2003.40    0.67           -0.43      US   \n",
+       "8  2023-11-21  2012.00    0.67            1.07      US   \n",
+       "9  2023-11-20  1990.70    0.31            0.30     NaN   \n",
+       "10 2023-11-17  1984.70  133.12           -0.13      US   \n",
+       "11 2023-11-16  1987.30  186.81            1.17     NaN   \n",
+       "12 2023-11-15  1964.30  142.92           -0.11      US   \n",
+       "13 2023-11-14  1966.50  180.74            0.84      US   \n",
+       "14 2023-11-13  1950.20  183.70            0.65     NaN   \n",
+       "15 2023-11-10  1937.70  229.64           -1.63      US   \n",
+       "16 2023-11-09  1969.80  214.08            0.61      US   \n",
+       "17 2023-11-08  1957.80  189.36           -0.80      US   \n",
+       "18 2023-11-07  1973.50  218.95           -0.76     NaN   \n",
+       "19 2023-11-06  1988.60  146.28           -0.53      CA   \n",
+       "20 2023-11-03  1999.20  222.19            0.29      US   \n",
+       "21 2023-11-02  1993.50  158.65            0.30      GB   \n",
+       "22 2023-11-01  1987.50  197.63           -0.34      US   \n",
+       "23 2023-10-31  1994.30  214.78           -0.56      EA   \n",
+       "24 2023-10-30  2005.60  181.34            0.83      JP   \n",
+       "25 2023-10-27  1989.00    0.37            0.06      US   \n",
+       "26 2023-10-26  1987.90    0.20            0.12      US   \n",
+       "27 2023-10-25  1985.50    0.16            0.44      US   \n",
+       "28 2023-10-24  1976.80    1.23           -0.07      GB   \n",
+       "29 2023-10-23  1978.20    0.45           -0.81     NaN   \n",
+       "\n",
+       "                                Event  D_Consensus  D_Forecast  \n",
+       "0              ISM Manufacturing PMI      1.888772    1.053741  \n",
+       "1           Core PCE Price Index MoM      0.000000    0.199005  \n",
+       "2         GDP Growth Rate QoQ 2nd Est     0.362976    0.544959  \n",
+       "3                                 NaN          NaN         NaN  \n",
+       "4                                 NaN          NaN         NaN  \n",
+       "5                                 NaN          NaN         NaN  \n",
+       "6                 Inflation Rate YoY           NaN    0.187793  \n",
+       "7           Durable Goods Orders MoM      5.027322    5.664488  \n",
+       "8                        FOMC Minutes          NaN         NaN  \n",
+       "9                                 NaN          NaN         NaN  \n",
+       "10             Building Permits Prel      1.879604    1.879604  \n",
+       "11                                NaN          NaN         NaN  \n",
+       "12                           PPI MoM      1.204819    1.204819  \n",
+       "13           Core Inflation Rate MoM      0.199005    0.199005  \n",
+       "14                                NaN          NaN         NaN  \n",
+       "15  Michigan Consumer Sentiment Prel      5.275779    6.050955  \n",
+       "16           Fed Chair Powell Speech           NaN         NaN  \n",
+       "17           Fed Chair Powell Speech           NaN         NaN  \n",
+       "18                                NaN          NaN         NaN  \n",
+       "19                      Ivey PMI s.a      1.107011    2.441315  \n",
+       "20                 Non Farm Payrolls     18.126888   23.460411  \n",
+       "21         BoE Interest Rate Decision     0.000000    0.000000  \n",
+       "22             ISM Manufacturing PMI      4.756980    5.761317  \n",
+       "23          GDP Growth Rate QoQ Flash     0.200200    0.200200  \n",
+       "24         BoJ Interest Rate Decision     0.000000    0.000000  \n",
+       "25          Core PCE Price Index MoM      0.000000    0.199005  \n",
+       "26          Durable Goods Orders MoM      5.639098    6.805293  \n",
+       "27           Fed Chair Powell Speech           NaN         NaN  \n",
+       "28      Unemployment Rate - Adjusted           NaN         NaN  \n",
+       "29                                NaN          NaN         NaN  "
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.head(30)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Missing Values</th>\n",
+       "      <th>Data Type</th>\n",
+       "      <th>min</th>\n",
+       "      <th>max</th>\n",
+       "      <th>Mean</th>\n",
+       "      <th>Median</th>\n",
+       "      <th>Variance</th>\n",
+       "      <th>deviation</th>\n",
+       "      <th>Num Outliers</th>\n",
+       "      <th>Unique Choices</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Date</th>\n",
+       "      <td>0</td>\n",
+       "      <td>datetime64[ns]</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Price</th>\n",
+       "      <td>0</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>1272.00</td>\n",
+       "      <td>2089.700000</td>\n",
+       "      <td>1743.149062</td>\n",
+       "      <td>1797.700000</td>\n",
+       "      <td>42242.879221</td>\n",
+       "      <td>205.530726</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Vol_K</th>\n",
+       "      <td>15</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>813.410000</td>\n",
+       "      <td>216.213473</td>\n",
+       "      <td>200.515000</td>\n",
+       "      <td>12971.563973</td>\n",
+       "      <td>113.892774</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Change_percent</th>\n",
+       "      <td>0</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>-4.99</td>\n",
+       "      <td>5.950000</td>\n",
+       "      <td>0.043206</td>\n",
+       "      <td>0.040000</td>\n",
+       "      <td>0.966090</td>\n",
+       "      <td>0.982899</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Country</th>\n",
+       "      <td>472</td>\n",
+       "      <td>object</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Event</th>\n",
+       "      <td>472</td>\n",
+       "      <td>object</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>98.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>D_Consensus</th>\n",
+       "      <td>599</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>752.830189</td>\n",
+       "      <td>11.308194</td>\n",
+       "      <td>1.097919</td>\n",
+       "      <td>2253.849946</td>\n",
+       "      <td>47.474730</td>\n",
+       "      <td>94.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>D_Forecast</th>\n",
+       "      <td>537</td>\n",
+       "      <td>float64</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>7733.884298</td>\n",
+       "      <td>33.955382</td>\n",
+       "      <td>1.483586</td>\n",
+       "      <td>96522.160809</td>\n",
+       "      <td>310.680158</td>\n",
+       "      <td>105.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                Missing Values       Data Type      min          max  \\\n",
+       "Date                         0  datetime64[ns]      NaN          NaN   \n",
+       "Price                        0         float64  1272.00  2089.700000   \n",
+       "Vol_K                       15         float64     0.00   813.410000   \n",
+       "Change_percent               0         float64    -4.99     5.950000   \n",
+       "Country                    472          object      NaN          NaN   \n",
+       "Event                      472          object      NaN          NaN   \n",
+       "D_Consensus                599         float64     0.00   752.830189   \n",
+       "D_Forecast                 537         float64     0.00  7733.884298   \n",
+       "\n",
+       "                       Mean       Median      Variance   deviation  \\\n",
+       "Date                    NaN          NaN           NaN         NaN   \n",
+       "Price           1743.149062  1797.700000  42242.879221  205.530726   \n",
+       "Vol_K            216.213473   200.515000  12971.563973  113.892774   \n",
+       "Change_percent     0.043206     0.040000      0.966090    0.982899   \n",
+       "Country                 NaN          NaN           NaN         NaN   \n",
+       "Event                   NaN          NaN           NaN         NaN   \n",
+       "D_Consensus       11.308194     1.097919   2253.849946   47.474730   \n",
+       "D_Forecast        33.955382     1.483586  96522.160809  310.680158   \n",
+       "\n",
+       "                Num Outliers  Unique Choices  \n",
+       "Date                     NaN             NaN  \n",
+       "Price                    0.0             NaN  \n",
+       "Vol_K                    5.0             NaN  \n",
+       "Change_percent           2.0             NaN  \n",
+       "Country                  NaN             7.0  \n",
+       "Event                    NaN            98.0  \n",
+       "D_Consensus             94.0             NaN  \n",
+       "D_Forecast             105.0             NaN  "
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "summary(data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\shawn\\AppData\\Local\\Temp\\ipykernel_3588\\1062981010.py:2: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
+      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
+      "\n",
+      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
+      "\n",
+      "\n",
+      "  data['Vol_K'].fillna(data['Vol_K'].median(), inplace=True)\n",
+      "C:\\Users\\shawn\\AppData\\Local\\Temp\\ipykernel_3588\\1062981010.py:3: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
+      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
+      "\n",
+      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
+      "\n",
+      "\n",
+      "  data['D_Consensus'].fillna(data['D_Consensus'].median(), inplace=True)\n",
+      "C:\\Users\\shawn\\AppData\\Local\\Temp\\ipykernel_3588\\1062981010.py:4: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
+      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
+      "\n",
+      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
+      "\n",
+      "\n",
+      "  data['D_Forecast'].fillna(data['D_Forecast'].median(), inplace=True)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Handle missing values (example: filling with median)\n",
+    "data['Vol_K'].fillna(data['Vol_K'].median(), inplace=True)\n",
+    "data['D_Consensus'].fillna(data['D_Consensus'].median(), inplace=True)\n",
+    "data['D_Forecast'].fillna(data['D_Forecast'].median(), inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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kSHTv3n2917U6u+++ewwZMiT22GOPWqOramrI9091dXVstNFG2XBs+duoUaMi4pv31z333BPPPfdcnHXWWfHRRx/FySefHNtvv/0KYdu6+MEPfhAzZ86MZ599NhYuXBgPPPBAHHPMMSuEhMvbYostYsGCBSucRH1drennqiE+A3X17w9+8INYtGhR3H///ZEkSfz1r3+NAw88MDp06FDvdQOQboIgAFjOspO37rvvvqtsl5eXF9/97nfjyiuvjH//+98xevTomDhxYvYwmrp+PK6td999t9bjJElixowZta5atMEGG8T8+fNXWHb50Q1rUlvPnj3j448/XmGkxbRp07LzG0LPnj3j3XffXWFU1bo8z3777RetWrWqdShNfepY2+1dtg3Lmz59er2fv6FtttlmMX369FUeyrXZZpvF559/Hrvuums2IKt5GzRoUK32O++8c4wePTqmTp0at99+e7z11lvxt7/9bbW1zJgxY4Uw5J133omIqPU+Hjp0aHTp0iVuv/32uO+++6KioqJeJ4A+6KCDIiJqXfGvLsv6cWV9M3369Fr9XN/P1ZpY2++HrbbaKrbbbru4/fbb4+mnn44PPvig3ifHBoAIQRAA1DJx4sT49a9/Hb17917leV3mzZu3wrRtt902IiJ7mExJSUlExEp/QK6NW2+9tVY4cc8998Ts2bNjv/32y07bbLPN4vnnn4+vv/46O+3BBx9cYYTEmtS2//77R1VVVVx77bW1pl911VWRyWRqPf+62H///WPOnDlx5513ZqctXbo0rrnmmmjbtm3ssccea7zOTTfdNE4++eR45JFHVqh/meWDiXXZ3v333z+ef/75mDJlSnbap59+ukZBVEM74ogj4rPPPlvp9i/b9u9973tRVVUVv/71r1dos3Tp0uz75Isvvljh9Vr+fb8qH3/8cdx3333Zx+Xl5XHrrbfGtttuG926dctOz8/Pj2OOOSbuuuuuuOWWW2LrrbeObbbZZrXrP/LII2PrrbeO0aNHx3PPPbfC/IULF8ZFF10UERE77LBDbLTRRnHjjTfWqv2RRx6Jt99+Ow444IDstM022yymTZsWn376aXbaa6+9lr1K4NpYl++H448/Ph577LEYM2ZMdOrUqcE+gwCkg8vHA5BajzzySEybNi2WLl0an3zySUycODEmTJgQPXv2jAceeKDWCWSXN2rUqHjqqafigAMOiJ49e8bcuXPj+uuvj0022SR22223iPjmx2PHjh3jxhtvjHbt2kVJSUnstNNOKz33R31suOGGsdtuu8VJJ50Un3zySYwZMyb69u1b6xL3p556atxzzz0xdOjQ+N73vhfvvfde3HbbbSscXrQmtR100EExePDguOiii+L999+PQYMGxWOPPRb/+Mc/YtiwYXUeurSmTjvttPjjH/8YJ554Yrz00kvRq1evuOeee+KZZ56JMWPG1PskwMsbM2ZMzJo1K84+++z429/+FgcddFBstNFG8dlnn8UzzzwT//znP2udJ2ZdtnfEiBHxl7/8JYYOHRrnnntu9vLxPXv2jNdff32t6l9XP/jBD+LWW2+N4cOHx5QpU+K//uu/4ssvv4zHH388zjjjjDjkkENijz32iB/96EdxySWXxKuvvhr77LNPFBQUxLvvvht33313XH311XHkkUfGn//857j++uvjsMMOi8022ywWLlwYf/rTn6J9+/ax//77r7aWfv36xSmnnBIvvvhidO3aNcaNGxeffPJJ3HzzzSut+w9/+ENMmjQpLr300npta0FBQdx7770xZMiQ2H333eN73/te7LrrrlFQUBBvvfVW/PWvf40NNtggRo8eHQUFBXHppZfGSSedFHvssUccc8wx2cvH9+rVq9bl608++eS48sorY999941TTjkl5s6dGzfeeGMMHDgwe0LyNbXsnE/nnHNO7LvvvtGqVav4/ve/X69l//u//ztGjBgR9913X5x++ulRUFCwVjUAkFK5ulwZAOTKssvHL7u1bt066datW7L33nsnV199da3LlC+z/OXjn3jiieSQQw5JevTokbRu3Trp0aNHcswxxyTvvPNOreX+8Y9/JAMGDEjy8/NrXa59jz32SAYOHLjS+uq6fPwdd9yRjBw5Mtloo42SoqKi5IADDkj+85//rLD8FVdckWy88cZJYWFhsuuuuyZTp05d6eWv66pt+UtiJ0mSLFy4MDnvvPOSHj16JAUFBcnmm2+eXHbZZdnLjy8TEcmZZ565Qk11XdZ+eZ988kly0kknJZ07d05at26dbL311iu9xH19Lx+/zNKlS5Obb7452WuvvZINN9wwyc/PTzp37px897vfTW688cZalw9fk+1d2Xa9/vrryR577JG0adMm2XjjjZNf//rXydixY9fo8vGffvrpKtutyfsnSZKkoqIiueiii5LevXsnBQUFSbdu3ZIjjzwyee+992q1u+mmm5Ltt98+KSoqStq1a5dsvfXWyYgRI5KPP/44SZIkefnll5Njjjkm2XTTTZPCwsJko402Sg488MBk6tSpq6w3Sf6vzx599NFkm222SQoLC5Mtttgiufvuu+tcZuDAgUleXl7y4Ycfrnb9NX3xxRfJL37xi2TrrbdOiouLkzZt2iRbbbVVMnLkyGT27Nm12t55553JdtttlxQWFiYbbrhhcuyxx670+W677bakT58+SevWrZNtt902efTRR+u8fPxll122wvIRkfzyl7/MPl66dGly9tlnJ126dEkymUz2+2VV66hp//33TyIiefbZZ9fglQGAJMkkSQ7O3AgAAKux3XbbxYYbbhhPPPFErktpcg477LB44403YsaMGbkuBYBmxjmCAABocqZOnRqvvvpq/OAHP8h1KU3O7Nmz46GHHnKSaADWihFBAAA0GW+++Wa89NJLccUVV8Rnn30WM2fOXOX5utJk1qxZ8cwzz8T/+3//L1588cV47733ap1kGwDqw4ggAACajHvuuSdOOumkWLJkSdxxxx1CoBqefPLJOP7442PWrFnx5z//WQgEwFoxIggAAAAgJYwIAgAAAEgJQRAAAABASuTnuoD1qbq6Oj7++ONo165dZDKZXJcDAAAA0CCSJImFCxdGjx49Ii+v7nE/qQqCPv744ygtLc11GQAAAACNoqysLDbZZJM656cqCGrXrl1EfPOitG/fPsfVAAAAADSM8vLyKC0tzWYfdUlVELTscLD27dsLggAAAIAWZ3WnwnGyaAAAAICUEAQBAAAApIQgCAAAACAlBEEAAAAAKZGqk0UDAKRVkiRRUVGR6zJYD5IkicrKyoiIKCoqWu1JQ0mX4uJi7wlIOUEQAEAKVFRURGlpaa7LAHKsrKwsSkpKcl0GkEMODQMAAABICSOCAABSZsM2mXBgSMuVJEnMW/zN/Q0Lw2FARBIR875Kcl0G0EQIggAAUiYTwoGW75sf/ZlMRl8TkQiBgP/j0DAAAACAlBAEAQAAAKSEIAgAAAAgJQRBAAAAACkhCAIAAABICUEQAAAAQEoIggAAAABSQhAEAAAAkBKCIAAAAICUEAQBAAAApIQgCAAAACAlBEEAAAAAKZGf6wKApitJkqioqIiIiOLi4shkMjmuCAAAoOGk8TePEUFAnSoqKqK0tDRKS0uzX44AAAAtRRp/8wiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkhCAIAAAAICUEQQAAAAApIQgCAAAASAlBEAAAAEBKCIIAAAAAUkIQBAAAAJASgiAAAACAlBAEAQAAAKSEIAgAAAAgJQRBzdj48eOjX79+0a9fvxg/fnx22qBBg2L06NExaNCgWtN79uwZnTt3jpNPPjk7r2b7ZetatuzJJ58cXbp0idGjR8fo0aOjU6dO0alTp+jZs2d2vWtT4+jRo6Nz586x8cYb15q+smVrbkN9563NepZt8/KvGwAAALQkmSRJklwWsOeee8a2224bY8aMqTX9lltuiWHDhsX8+fOjoqIifv3rX8ddd90VH330UbRr1y4GDBgQw4cPj0MOOaTez1VeXh4dOnSIBQsWRPv27Rt4S9avioqK2GGHHWLOnDkREdGtW7d4+umnY/fdd4/Zs2dHXl5eVFdXR/fu3eOpp56K3XbbLT755JNa6+jWrVtERMyZMyfbPiIik8lEzbdFJpOJiKg1rWvXrvHSSy9FcXHxGtX42GOPxaBBg2qtq1u3bjF16tRa66qoqIgdd9wxZs+eHd27d48XX3wxO39V81ZWQ33Ws2z7a75uq1pvWnz55ZdRWloaERFlZWVRUlKS44oAWFs1v9M7tclk/77T8iRJEp9/9c2+lr4movZ7wj4d1NaSfvPUN/NoFiOCfvzjH8e9994b11xzTUybNi3Gjx8fRx55ZHz++ee5Li1nrrrqqmzAEvFNmHP88cdnpy0LdZZNXz4EWjZv+fYRtQOfZY+Xn/bJJ5+sEN7Vp8b99ttvhXXNmTNnhXXVXHb5+auat6oaVrWeZdtf83Vb3fYBAABAc9MsRgR17Ngxrr766jjhhBPW6blayoigmTNnxk477RRVVVU5raNVq1bxwgsvRJ8+fVaYt6Y15ufnx/PPPx99+vSJmTNnxs477xxLly7Nzi8oKIjnnnsuIqLOecvXsabrWV5d602TRYsWxaabbhoREdOnT0/9CCmA5qyioiL69+8fEREbFkbk5TWL/weyFowIYnnV1dUxb/E39+3TQW01/z5+8MEH0bZt2xxXtPbqm3nkr8ea1lq3bt3i4YcfjsMPPzzatWtX7+UWL14cixcvzj4uLy9vjPLWqyRJ4oILLsh5CBQRUVVVFRdccEHcc889tXYwkiSJESNG1BpltDpLly6NCy64IO6+++4YMWLECqOGqqurs9Prmnf33XfXOoytrvVccMEFKxz+tjIrW2/aVFZWZu8v+3IEAKD5sk8HdausrGzWQVB9NYt/Bd10003x7LPPRqdOnWLHHXeM8847L5555pnVLnfJJZdEhw4dsrdlx/01Z++8805MmjQp12VkTZo0Kd55551a0955552YOHHiaoOWla1rwoQJMXHixBWCrqqqqpg4cWJMmjSpznk161hWw8raTpo0aaXzlrey9QIAAEBz1ixGBO2+++4xc+bMeP755+PZZ5+NJ554Iq6++ur41a9+FT//+c/rXG7kyJExfPjw7OPy8vJmHwb169cvBg8e3GTCoMGDB0e/fv1qTevXr1/stddeMXHixDVa11577RV777137LXXXvHkk0/WCmpatWoVe+yxRyRJEk899dQK8/bcc89adSyroa71RMQK85a3svWmTVFRUfa+YcQAzVvNoe9Aetmng9pq/n2s+funJcv5OYIOPvjg6NSpU9x88821po8ZMyauuuqq+M9//rPS5X7zm9/EqFGjYtGiRdG6det6PZdzBDWsVq1axZQpU6J3794rzFubcwS98MIL0bt37zrP7fP8889HkiR1zlu+jjVdz/LqWm+atKQz6AOknauGpYdzBLE8Vw2DurWk3zzN5qph/fv3j5dffnmF6S+//PIqR2IMGDAgli5dGl999VVjltck9enTJ4YNG7bC9J133nmFP/SZTCZ23nnnRqnjvPPOqzMkqavGjTfeeKXthw0bll1Xnz594txzz81uSyaTiXPPPTd69+69ynkrq6G+61neqtYLAAAAzVXORwTNnDkzBg4cGD/84Q/j1FNPjcLCwnjooYfipz/9afzzn/+MoUOHxp577hnHHHNM7LDDDtGpU6f497//HcOHD4+NN944nnjiiXo/V0sZERTxzfC1HXbYIXv58+7du8dTTz0Vu+++e8yePTvy8vKiuro6evToEU8++WTstttuK1xCvlu3bhHxzaXSl7WPiBVOpFzzBMw1l506deoqh5UuX2O3bt3isccei0GDBq12XRUVFbHjjjvG7Nmzo0ePHjFlypTs/FXNW1kN9VnPsu2v+bqtar1p0ZLScYC0MyIoPYwIYnlGBEHdWtJvnmYzIqhPnz7x1FNPxbRp02LIkCGx0047xV133RV33313DB06NCIi9t133/jzn/8c++yzT2y55ZZx9tlnx7777ht33XVXjqvPneLi4rjyyiujc+fO0blz57jiiiuiU6dOccUVV0RpaWmcd955UVpaGpdffnl06tQprrrqqmjXrl3k5eXFoYceGqWlpXHllVfGlVdemW2/bF3Dhw+P0tLSOPTQQ6NVq1YxfPjwGD58eGQy3+xItGvXLq688srVhiTL13jllVfGJptsEsOHD4+8vLwoKirKTl9+XcXFxdltufzyy2vNX9W8ldVQn/Use71qvm5pD4EAAABoeXI+Imh9akkjgmB9aEnpOEDaGRGUHkYEsTwjgqBuLek3T7MZEQQAAADA+iEIAgAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkhCAIAAAAICUEQQAAAAApIQgCAAAASAlBEAAAAEBK5Oe6AKDpKi4ujrKysux9AACAliSNv3kEQUCdMplMlJSU5LoMAACARpHG3zwODQMAAABICUEQAAAAQEoIggAAAABSQhAEAAAAkBKCIAAAAICUEAQBAAAApIQgCAAAACAlBEEAAAAAKSEIAgAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJTIz3UBAACsX0lERJLkugwaSVKjbxP9TPzvZx7gfwmCAABSZt5XfhamxbzFEWIAAGpyaBgAAABAShgRBACQAsXFxVFWVpbrMlgPkiSJysrKiIgoKiqKTCaT44poSoqLi3NdApBjgiAAgBTIZDJRUlKS6zJYT9q2bZvrEgBoohwaBgAAAJASgiAAAACAlBAEAQAAAKSEIAgAAAAgJQRBAAAAACkhCAIAAABICUEQAAAAQEoIggAAAABSQhAEAAAAkBKCIAAAAICUEAQBAAAApIQgCAAAACAlBEEAAAAAKZGf6wIAaHxJkkRFRUWuywBoNEmSRGVlZUREFBUVRSaTyXFFLVNxcbHXFqCZEwQBpEBFRUWUlpbmugwAmrmysrIoKSnJdRkArAOHhgEAAACkhBFBACmzfc9OkWdYP9DCVFUn8fIHn0dExLc27RSt8nzPNZTqJImX/vN5rssAoIEIggBSJi+T8QMJaNFa5fmea1DVuS4AgIbk0DAAAACAlBAEAQAAAKSEIAgAAAAgJQRBAAAAACkhCAIAAABICUEQAAAAQEoIggAAAABSQhAEAAAAkBKCIAAAAICUEAQBAAAApIQgCAAAACAlBEEAAAAAKZGf6wKovyRJoqKiIiIiiouLI5PJ5LgiAAAAGpLffTQ2I4KakYqKiigtLY3S0tLsFwMAAAAth999NDZBEAAAAEBKCIIAAAAAUkIQBAAAAJASgiAAAACAlBAEAQAAAKSEIAgAAAAgJQRBAAAAACkhCAIAAABICUEQAAAAQEoIggAAAABSQhAEAAAAkBKCIAAAAICUEAQBAAAApIQgCAAAACAlmnQQdOKJJ8ahhx6avZ/JZCKTyUTr1q2jb9++MWrUqFi6dGluiwQAAABoJvJzXcCaGDp0aNx8882xePHiePjhh+PMM8+MgoKCGDlyZK5LAwAAAGjymlUQVFhYGN26dYuIiNNPPz3uu+++eOCBB1ITBCVJkr1fUVGRw0qA5qbmd8Y33yWZ3BUDQLNiHxTWrxX326BhNasgaHlFRUXx+eef1zl/8eLFsXjx4uzj8vLy9VFWo6msrMze79+/fw4rAZqzavsTAKyBmn837IPC+lVZWRlt27bNdRm0ME36HEF1SZIkHn/88Xj00Udjr732qrPdJZdcEh06dMjeSktL12OVAAAAAE1LsxoR9OCDD0bbtm1jyZIlUV1dHf/93/8dF198cZ3tR44cGcOHD88+Li8vb9ZhUFFRUfb+9OnTo7i4OIfVAM1JRUVF9r+4eY4KA2AN1Py7YR8UGl/N/baavwGhoTSrIGjw4MFxww03ROvWraNHjx6Rn7/q8gsLC6OwsHA9Vdf4Mpn/+ytcXFwcJSUlOawGaK5qfpcAwOrYB4Xcsd9GY2hWQVBJSUn07ds312UAAAAANEvN8hxBAAAAAKy5Jh0EVVdXr/bwLwAAAADqp0mnLHPnzs0eCnbLLbfkthgAAACAZq5Jjgj64osv4sEHH4zJkyfHkCFDcl0OAAAAQIvQJEcEnXzyyfHiiy/G+eefH4ccckiuywEAAABoEZpkEHTfffflugQAAACAFqdJHhoGAAAAQMMTBAEAAACkhCAIAAAAICUEQQAAAAApIQgCAAAASAlBEAAAAEBKCIIAAAAAUkIQBAAAAJAS+bkugPorLi6OsrKy7H0AAABaFr/7aGyCoGYkk8lESUlJrssAAACgkfjdR2NzaBgAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkhCAIAAAAICUEQQAAAAApIQgCAAAASAlBEAAAAEBKCIIAAAAAUkIQBAAAAJASgiAAAACAlBAEAQAAAKREfq4LAGD9qk6SiOpcVwHQsKqqk5XeZ91VJ15PgJZEEASQMi/95/NclwDQqF7+wPccANTFoWEAAAAAKWFEEEAKFBcXR1lZWa7LAGg0SZJEZWVlREQUFRVFJpPJcUUtU3Fxca5LAGAdCYIAUiCTyURJSUmuywBoVG3bts11CQDQ5Dk0DAAAACAlBEEAAAAAKSEIAgAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkhCAIAAAAICUEQQAAAAApIQgCAAAASAlBEAAAAEBKCIIAAAAAUiI/1wUA0HIkSRIVFRW5LgOARpAkSVRWVkZERFFRUWQymRxXRFNTXFzsfQHNgCAIgAZTUVERpaWluS4DAMiBsrKyKCkpyXUZwGo4NAwAAAAgJYwIAqBRHPntvpHfyv8bAFqKpVXVcc+UGRHhO57/U/N9ATQPgiAAGkV+q7wo8CMBoEXyHQ/QfPn2BgAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkhCAIAAAAICUEQQAAAAApIQgCAAAASAlBEAAAAEBKCIIAAAAAUkIQBAAAAJAS+bkugMaRJElUVFRERERxcXFkMpkcVwQAAEBd/IZjfTEiqIWqqKiI0tLSKC0tzX6ZAAAA0DT5Dcf6IggCAAAASAlBEAAAAEBKCIIAAAAAUkIQBAAAAJASgiAAAACAlBAEAQAAAKSEIAgAAAAgJQRBAAAAACkhCAIAAABICUEQAAAAQEoIggAAAABSQhAEAAAAkBKCIAAAAICUEAQBAAAApESTCILmzJkTZ599dvTp0ycKCwujtLQ0DjrooHjiiSdqtbvkkkuiVatWcdlll+WoUgAAAIDmK+dB0Pvvvx/bb799TJw4MS677LJ44403Yvz48TF48OA488wza7UdN25cjBgxIsaNG5ejagEAAACar/xcF3DGGWdEJpOJKVOmRElJSXb6wIED4+STT84+fvLJJ6OysjJGjRoVt956azz77LPxne98JxclNwtJkmTvV1RU5LASIE1qft/U/B4CAFomvzsajv0o1pecBkHz5s2L8ePHx+jRo2uFQMt07Ngxe3/s2LFxzDHHREFBQRxzzDExduzY1QZBixcvjsWLF2cfl5eXN1jtTV1lZWX2fv/+/XNYCZBWVdV2YACgpav5997vjoZTWVkZbdu2zXUZtFA5PTRsxowZkSRJbLHFFqtsV15eHvfcc08cd9xxERFx3HHHxV133RWLFi1a5XKXXHJJdOjQIXsrLS1tsNoBAAAAmpucjgiq73C3O+64IzbbbLMYNGhQRERsu+220bNnz7jzzjvjlFNOqXO5kSNHxvDhw7OPy8vLUxMGFRUVZe9Pnz49iouLc1gNkBYVFRXZ/wa2ysvkuBoAoLHV/Hvvd8e6qbkfVfP3HDS0nAZBm2++eWQymZg2bdoq240dOzbeeuutyM//v3Krq6tj3LhxqwyCCgsLo7CwsMHqbU4ymf/7Qi4uLl7poXcAjanm9xAA0DL53dE47EfRmHIaBG244Yax7777xnXXXRfnnHPOCl8a8+fPj7Kyspg6dWpMnjw5Ntxww+y8efPmxZ577hnTpk1b7aFlAAAAADSBq4Zdd911seuuu8a3v/3tGDVqVGyzzTaxdOnSmDBhQtxwww2x7777xre//e3YfffdV1h2xx13jLFjx8Zll12Wg8oBAAAAmpecniw6IqJPnz7x8ssvx+DBg+P888+PrbbaKvbee+944okn4uqrr47bbrstjjjiiJUue8QRR8Stt94aS5YsWc9VAwAAADQ/OR8RFBHRvXv3uPbaa+Paa69dYd5nn31W53IjRoyIESNGNGZpAAAAAC1GzkcEAQAAALB+CIIAAAAAUkIQBAAAAJASgiAAAACAlBAEAQAAAKSEIAgAAAAgJQRBAAAAACkhCAIAAABICUEQAAAAQEoIggAAAABSQhAEAAAAkBL5uS6AxlFcXBxlZWXZ+wAAADRdfsOxvgiCWqhMJhMlJSW5LgMAAIB68BuO9cWhYQAAAAApIQgCAAAASAlBEAAAAEBKCIIAAAAAUkIQBAAAAJASgiAAAACAlBAEAQAAAKSEIAgAAAAgJQRBAAAAACkhCAIAAABICUEQAAAAQEoIggAAAABSQhAEAAAAkBL5uS4AgJZpaVV1rksAoAHV/F73Hc8y3gvQ/AiCAGgU90yZkesSAGgkvuMBmi+HhgEAAACkhBFBADSY4uLiKCsry3UZADSCJEmisrIyIiKKiooik8nkuCKamuLi4lyXANSDIAiABpPJZKKkpCTXZQDQSNq2bZvrEgBYRw4NAwAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkhCAIAAAAICUEQQAAAAApIQgCAAAASAlBEAAAAEBKCIIAAAAAUkIQBAAAAJASgiAAAACAlMjPdQEAALmUJElUVFTkugxSIEmSqKysjIiIoqKiyGQyOa6I1SkuLtZPQIsjCAIAUq2ioiJKS0tzXQbQBJWVlUVJSUmuywBoUA4NAwAAAEgJI4IAAP7XBQfvEK3zW+W6DFqor5dWxWUPTI0I77WmrGY/AbREgiAAgP/VOr+VH+esF95rAOSKQ8MAAAAAUkIQBAAAAJASgiAAAACAlBAEAQAAAKSEIAgAAAAgJQRBAAAAACkhCAIAAABIibUKgk444YR46qmnGroWAAAAABrRWgVBCxYsiCFDhsTmm28ev/3tb+Ojjz5q6LoAAAAAaGBrFQTdf//98dFHH8Xpp58ed955Z/Tq1Sv222+/uOeee2LJkiUNXSMAAAAADWCtzxHUpUuXGD58eLz22mvxwgsvRN++feP444+PHj16xHnnnRfvvvtuQ9YJAAAAwDpa55NFz549OyZMmBATJkyIVq1axf777x9vvPFGDBgwIK666qqGqBEAAACABrBWQdCSJUvi73//exx44IHRs2fPuPvuu2PYsGHx8ccfx5///Od4/PHH46677opRo0Y1dL3Q4JIkiS+//DK+/PLLSJIk1+UAAAAp5vcJjS1/bRbq3r17VFdXxzHHHBNTpkyJbbfddoU2gwcPjo4dO65jedD4KioqorS0NCIiysrKoqSkJMcVAQAAaeX3CY1trYKgq666Ko466qho06ZNnW06duwYs2bNWuvCAAAAAGhYa3xo2JIlS+Kkk06KGTNmNEY9AAAAADSSNQ6CCgoKYtNNN42qqqrGqAcAAACARrJWJ4u+6KKL4sILL4x58+Y1dD0AAAAANJK1OkfQtddeGzNmzIgePXpEz549Vzh51csvv9wgxQEAAADQcNYqCDrkkEMik8k0dC0AAAAANKK1CoIuvvjiBi4DAAAAgMa2VucI6tOnT3z++ecrTJ8/f3706dNnnYsCAAAAoOGtVRD0/vvvr/SqYYsXL44PP/xwnYsCAAAAoOGt0aFhDzzwQPb+o48+Gh06dMg+rqqqiieeeCJ69+7dcNUBAAAA0GDWKAg69NBDIyIik8nECSecUGteQUFB9OrVK6644ooGKw4AAACAhrNGQVB1dXVERPTu3TtefPHF6Ny5c6MUBQAAAEDDW6urhs2aNauh6wAAAACgka3VyaIjIp544om48MIL49RTT42TTz651o3GNX78+Bg0aFCMHz9+pY/ru1x92tW1zJpOX5PnXxPL1jl69OgGXzcAAAC0NJkkSZI1XehXv/pVjBo1KnbYYYfo3r17ZDKZWvPvu+++eq9rzpw5cckll8RDDz0UH374YXTo0CH69u0bxx13XJxwwglRXFwcvXr1iv/85z8REZGXlxddu3aN/fbbLy6//PLYYIMN6v1c5eXl0aFDh1iwYEG0b9++3ss1JRUVFbHjjjvG7Nmzo3v37vHUU0/F7rvvnn384osvRnFx8WqXq0+7bt26RcQ3fVRzmbrWtarnqO/zr+1rkZeXF9XV1Wu17i+//DJKS0sjIqKsrCxKSkrWqS4AmpeafwcuOnynaJ3fKscV0VJ9vbQqRt/7QkR4rzVlNfvJviG54PcJa6u+mcdajQi68cYb45ZbbokXXngh7r///rjvvvtq3epr5syZsd1228Vjjz0Wv/3tb+OVV16J5557LkaMGBEPPvhgPP7449m2o0aNitmzZ8cHH3wQt99+ezz11FNxzjnnrE35zdpVV10Vc+bMiYhvAprjjz++1uMxY8bUa7n6tlvZMnWta1XPUd/nXxM117ns/FUNtW4AAABoidZqRFCnTp1iypQpsdlmm63Tkw8dOjTeeuutmDZt2kpTziRJIpPJRK9evWLYsGExbNiw7Lzf/OY3cccdd8Rbb71V7+dr7iOCZs6cGTvvvHMsXbq0zjYFBQXx3HPPRZ8+fVa5XH3bLb/uu+66K4466qgV1lXX9Oeeey4iol7PvyZWVeuarnvRokWx6aabRkTE9OnT13mkEgDNS0VFRfTv3z8iIi487NtRWLBWp1CE1TIiqHlYvGRp/Pa+KRFh35DcqPl36YMPPoi2bdvmuCKai/pmHmu1p3PqqafGX//61/j5z3++1gV+/vnn2ZFAdQ11W/6Qs2U++uij+Oc//xk77bTTKp9j8eLFsXjx4uzj8vLyta4315IkiREjRsTqcrvq6uoYMWJE3H333ZHJZOpcrr7taqqqqopTTjllhTZ1Ta+uro4LLrggu/5VPf+aWF2tVVVVa7TuysrK7P1lX7gApNOSquooLMh1FUAuLamqzt63b0iuVVZWCoJocGsVBH311Vdx0003xeOPPx7bbLNNFBTU3mO68sorV7uOGTNmRJIkK3y5du7cOb766quIiDjzzDPj0ksvjYiIn/70p/Gzn/0sqqqq4quvvoqddtpptc9zySWXxK9+9as12bQm65133omJEyeutl1VVVVMnDgx3nnnnejfv3+dy9W3XU3V1dUxb968ek+vqqqKSZMm1avONbG6Wqurq9d63QAAANCSrVUQ9Prrr8e2224bERFvvvlmrXlrOrpjeVOmTInq6uo49thja43mueCCC+LEE0+MJEmirKwsLrzwwjjggAPiqaeeilatVj6sduTIkTF8+PDs4/Ly8uxJt5qbfv36xV577RVPPvlkVFVV1dmuVatWseeee0a/fv1WuVx929WUl5cXHTt2jAULFtRqU9f0Vq1axR577BERsdrnb8jXIi8vLwYPHlzvdRcVFWXvG/4LkD41h+AXtFrrC6oCLUTN7wH7huRCzb9LNX+rQENZqyCorlEea6Jv376RyWRi+vTptaYvO6/L8m/4zp07R9++fSMiYvPNN48xY8bELrvsEpMmTYohQ4as9DkKCwujsLBwnWttCjKZTPz+97+PnXfeeZXt8vLy4ve//302kKtrufq2q6lVq1Yxbty4OPLII+s1PS8vLy677LJIkmS1z78mVldrq1at1mjdNdsVFxc7Kz9Aiq3rP7SA5s++IU2Jv0s0hpz926tTp06x9957x7XXXhtffvnlGi+/bBRQzfO7tHR9+vSJc889t1Z4s/POO9d6fO6550bv3r1Xu1x92tW0bJndd999peuqa3rv3r3r/fzr8losX+e6rBsAAABaqrUKggYPHhx77bVXnbf6uv7662Pp0qWxww47xJ133hlvv/12TJ8+PW677baYNm1arUO+Fi5cGHPmzInZs2fHlClT4oILLoguXbrEd77znbXZhGbrvPPOi27dukVERPfu3eMvf/lLrcc1r6y2quXq225ly9S1rlU9R32ff03UXGdeXl6DrhsAAABaorUKgrbddtsYNGhQ9jZgwID4+uuv4+WXX46tt9663uvZbLPN4pVXXokhQ4bEyJEjY9CgQbHDDjvENddcEz/5yU/i17/+dbbtL37xi+jevXv06NEjDjzwwCgpKYnHHnssOnXqtDab0GwVFxfHFVdcEaWlpXH55ZdHp06daj2u6xjm5ZerT7srrrgirrzyyhWWqWtdq3qO+j7/2r4W5513XoOuGwAAAFqiTLK665GvgYsvvjgWLVoUl19+eUOtskGVl5dHhw4dYsGCBdG+fftcl0MT8eWXX2ZPIl5WVuY4cICUqfl34KLDd4rW+Su/CAWsq6+XVsXoe1+ICO+1pqxmP9k3JBf8PmFt1TfzaNBzBB133HExbty4hlwlAAAAAA2kQYOg5557Ltq0adOQqwQAAACggazV5eMPP/zwWo+TJInZs2fH1KlT4+c//3mDFAYAAABAw1qrIKhDhw61Hufl5UX//v1j1KhRsc8++zRIYQAAAAA0rLUKgm6++eaGrgMAAACARrZWQdAyL730Urz99tsRETFw4MDYbrvtGqQoAAAAABreWgVBc+fOje9///sxefLk6NixY0REzJ8/PwYPHhx/+9vfokuXLg1ZIwAAAAANYK2uGnb22WfHwoUL46233op58+bFvHnz4s0334zy8vI455xzGrpGAAAAABrAWo0IGj9+fDz++OOx5ZZbZqcNGDAgrrvuOieLBgAAAGii1mpEUHV1dRQUFKwwvaCgIKqrq9e5KAAAAAAa3loFQXvttVece+658fHHH2enffTRR3HeeefFd7/73QYrDgAAAICGs1aHhl177bVx8MEHR69evaK0tDQiIsrKymKrrbaK2267rUELhMZWXFwcZWVl2fsAAAC54vcJjW2tgqDS0tJ4+eWX4/HHH49p06ZFRMSWW24ZQ4YMadDiYH3IZDJRUlKS6zIAAAD8PqHRrdGhYRMnTowBAwZEeXl5ZDKZ2HvvvePss8+Os88+O3bccccYOHBgPP30041VKwAAAADrYI2CoDFjxsQPf/jDaN++/QrzOnToED/60Y/iyiuvbLDiAAAAAGg4axQEvfbaazF06NA65++zzz7x0ksvrXNRAAAAADS8NQqCPvnkk5VeNn6Z/Pz8+PTTT9e5KAAAAAAa3hoFQRtvvHG8+eabdc5//fXXo3v37utcFAAAAAANb42CoP333z9+/vOfx1dffbXCvMrKyvjlL38ZBx54YIMVBwAAAEDDWaPLx//sZz+Le++9N/r16xdnnXVW9O/fPyIipk2bFtddd11UVVXFRRdd1CiFAgAAALBu1igI6tq1azz77LNx+umnx8iRIyNJkoiIyGQyse+++8Z1110XXbt2bZRCAQAAAFg3axQERUT07NkzHn744fjiiy9ixowZkSRJbL755rHBBhs0Rn0AAAAANJA1DoKW2WCDDWLHHXdsyFoAAAAAaERrdLJoAAAAAJovQRAAAABASgiCAAAAAFJirc8RBADQ0ny9tCrXJdCC1Xx/ea81XfoGaOkEQQAA/+uyB6bmugRSwnsNgFxxaBgAAABAShgRBACkWnFxcZSVleW6DFIgSZKorKyMiIiioqLIZDI5rojVKS4uznUJAA1OEAQApFomk4mSkpJcl0FKtG3bNtclAJByDg0DAAAASAlBEAAAAEBKCIIAAAAAUkIQBAAAAJASgiAAAACAlBAEAQAAAKSEIAgAAAAgJQRBAAAAACkhCAIAAABICUEQAAAAQEoIggAAAABSQhAEAAAAkBKCIAAAAICUyM91AQCwKkmSREVFRa7LAJqAJEmisrIyIiKKiooik8nkuCKaouLiYu8NgFUQBAHQpFVUVERpaWmuywCgmSgrK4uSkpJclwHQZDk0DAAAACAljAgCoNm44Yf7RGFBq1yXAeTI4iVL4/Q/TYiIiBt+uHcUFtiV5RuLl1TF6X96LNdlADQL/noC0GwUFrSKNn74ARFRWJDv+wAA1oJDwwAAAABSQhAEAAAAkBKCIAAAAICUEAQBAAAApIQgCAAAACAlBEEAAAAAKSEIAgAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkRH6uC6DhJEkSFRUVERFRXFwcmUwmxxUBAABQF7/hyAUjglqQioqKKC0tjdLS0uyXCQAAAE2T33DkgiAIAAAAICUEQQAAAAApIQgCAAAASAlBEAAAAEBKCIIAAAAAUkIQBAAAAJASgiAAAACAlBAEAQAAAKSEIAgAAAAgJQRBAAAAACkhCAIAAABICUEQAAAAQEoIggAAAABSQhAEAAAAkBJNIgg68cQTI5PJrHAbOnRorXaXXHJJtGrVKi677LIcVQoAAADQfDWJICgiYujQoTF79uxatzvuuKNWm3HjxsWIESNi3LhxOaoSAAAAoPnKz3UByxQWFka3bt3qnP/kk09GZWVljBo1Km699dZ49tln4zvf+c56rLDpS5Ike7+ioiKHlQA0nJrfZzW/5wBgGfvBNFf2c8iFJhMErc7YsWPjmGOOiYKCgjjmmGNi7Nixqw2CFi9eHIsXL84+Li8vb+wyc6qysjJ7v3///jmsBKBxfL20KopaF+S6DACamK+XVmXv2w+muaqsrIy2bdvmugxSoMkcGvbggw9G27Zta91++9vfRsQ3Ac4999wTxx13XEREHHfccXHXXXfFokWLVrnOSy65JDp06JC9lZaWNvp2AAAAADRVTWZE0ODBg+OGG26oNW3DDTeMiIg77rgjNttssxg0aFBERGy77bbRs2fPuPPOO+OUU06pc50jR46M4cOHZx+Xl5e36DCoqKgoe3/69OlRXFycw2oAGkZFRUX2v7ut81vluBoAmqKafx/sB9Oc1NzPqfl7DhpTkwmCSkpKom/fviudN3bs2HjrrbciP///yq2uro5x48atMggqLCyMwsLCBq+1qcpkMtn7xcXFUVJSksNqABpeze85AFjGfjAtgf0c1pcmEwTV5Y033oipU6fG5MmTsyOEIiLmzZsXe+65Z0ybNi222GKLHFYIAAAA0Dw0mSBo8eLFMWfOnFrT8vPzY+zYsfHtb387dt999xWW2XHHHWPs2LFx2WWXra8yAQAAAJqtJnOy6PHjx0f37t1r3b797W/HbbfdFkccccRKlzniiCPi1ltvjSVLlqznagEAAACanyYRBN1yyy2RJMkKt5kzZ8Znn30WF1xwwUqXGzFiRHzyySdRUOBSwgAAAACr0ySCIAAAAAAanyAIAAAAICUEQQAAAAApIQgCAAAASAlBEAAAAEBKCIIAAAAAUkIQBAAAAJASgiAAAACAlBAEAQAAAKSEIAgAAAAgJQRBAAAAACmRn+sCaDjFxcVRVlaWvQ8AAEDT5TccuSAIakEymUyUlJTkugwAAADqwW84csGhYQAAAAApIQgCAAAASAlBEAAAAEBKCIIAAAAAUkIQBAAAAJASgiAAAACAlBAEAQAAAKSEIAgAAAAgJQRBAAAAACkhCAIAAABICUEQAAAAQEoIggAAAABSQhAEAAAAkBL5uS4AAOpr8ZKqXJcA5NDiJUtXeh/8fQCoP0EQAM3G6X96LNclAE3E6X+akOsSAKBZcmgYAAAAQEoYEQRAk1ZcXBxlZWW5LgNoApIkicrKyoiIKCoqikwmk+OKaIqKi4tzXQJAkyYIAqBJy2QyUVJSkusygCaibdu2uS4BAJo1h4YBAAAApIQgCAAAACAlBEEAAAAAKSEIAgAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkhCAIAAAAICUEQQAAAAApIQgCAAAASAlBEAAAAEBK5Oe6AAAAGkaSJFFRUZHrMlhHSZJEZWVlREQUFRVFJpPJcUWsq+LiYv0INBmCIACAFqKioiJKS0tzXQawnLKysigpKcl1GQAR4dAwAAAAgNQwIggAoAUa//Ojo6i1Xb3mqPLrpTH013dGhH5szmr2I0BT4q8KAEALVNQ6P4paF+S6DNaRfgSgoTk0DAAAACAlBEEAAAAAKSEIAgAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkhCAIAAAAICUEQQAAAAApIQgCAAAASAlBEAAAAEBK5Oe6AIDmKkmSqKioiIiI4uLiyGQyOa4IAID1wX4gzZkRQQBrqaKiIkpLS6O0tDS7IwAAQMtnP5DmTBAEAAAAkBKCIAAAAICUEAQBAAAApIQgCAAAACAlBEEAAAAAKSEIAgAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkhCAIAAAAICUEQQAAAAApIQhqocaPHx+DBg2K8ePH13veqpZpLGvynLmoL60a+7XWlwAAALnRJIKgOXPmxNlnnx19+vSJwsLCKC0tjYMOOiieeOKJiIjo1atXZDKZeP7552stN2zYsNhzzz1zUHHTVlFREeeff36UlZXF+eefHxUVFaudt6plclHnurRl3TT2a60vAQAAcifnQdD7778f22+/fUycODEuu+yyeOONN2L8+PExePDgOPPMM7Pt2rRpEz/96U9zWGnzcdVVV8WcOXMi4puQbcyYMaudt6plclHnurRl3TT2a60vAQAAcieTJEmSywL233//eP3112P69OlRUlJSa978+fOjY8eO0atXrzjkkEPixhtvjPvuuy/233//iPhmRNCrr74akydPrtdzlZeXR4cOHWLBggXRvn37ht6UJmHmzJmx8847x9KlS7PTCgoK4rnnnouIWOm8u+66K4466qiVLtOnT5/1Xufyz7kmbVk3jf1at7S+XLRoUWy66aYRETF9+vQoLi7OcUVA2lVUVET//v0jImLyqP+O4sLWOa6ItVH59ZLY4+e3R0TEk78+NopaF+S4ItZGxeKvY89f/DUi7Ce0RDW/bz/44INo27ZtjiuC+mce+euxphXMmzcvxo8fH6NHj14hBIqI6NixY/Z+796948c//nGMHDkyhg4dGnl5qx/MtHjx4li8eHH2cXl5eYPU3VQlSRIjRoyI5bO96urquOCCCyKTyawwr6qqKk455ZSVLjNixIi4++67I5PJrLc6l3/ONWnLumns17ol9mVlZWX2/rIdAYCm4qslVVFcmOsqIL2+WlKVvW8/oWWrrKwUBNGs5PTQsBkzZkSSJLHFFlvUq/3PfvazmDVrVtx+++31an/JJZdEhw4dsrfS0tJ1KbfJe+edd2LixIlRVVVVa3pVVVVMmjRppfOqq6tj3rx5K11m4sSJ8c4776zXOpd/zjVpy7pp7NdaXwIAAOReTkcErelRaV26dImf/OQn8Ytf/CKOPvro1bYfOXJkDB8+PPu4vLy8RYdB/fr1i7322iuefPLJWj+2W7VqFXvssUdExArz8vLyomPHjrFgwYIVltlzzz2jX79+67XO5Z9zTdqybhr7tW6JfVlUVJS9b8g30BTUPFShTUGrHFcD6VbzM2g/oeWp+X1bc58QmoOcBkGbb755ZDKZmDZtWr2XGT58eFx//fVx/fXXr7ZtYWFhFBamZ0x0JpOJ3//+97HzzjvXmp6XlxeXXXZZJEmywrxWrVrFuHHj4sgjj1xhmd///veNcqjOqupc/jnXpC3rprFf65bYlzVrLi4uXukhrgC50hy/V6ElsZ+QHr5vaW5yemjYhhtuGPvuu29cd9118eWXX64wf/78+StMa9u2bfz85z+P0aNHx8KFC9dDlc1Lnz594txzz81+GWUymTj33HOjd+/edc7bfffd61wmF3WuS1vWTWO/1voSAAAgt3J++fjrrrsuqqqq4tvf/nb8/e9/j3fffTfefvvt+MMf/hC77LLLSpc57bTTokOHDvHXv/51PVfbPJx33nnRrVu3iIjo3r17DBs2bLXzVrVMLupcl7asm8Z+rfUlAABA7uQ8COrTp0+8/PLLMXjw4Dj//PNjq622ir333jueeOKJuOGGG1a6TEFBQfz617+Or776aj1X2zwUFxfHFVdcEaWlpXH55ZfXOh65rnmrWiYXda5LW9ZNY7/W+hIAACB3MsmanrG5GSsvL48OHTrEggULon379rkuB2jmvvzyy+wJ6MvKyhz7D+Rcze+lJ399bBS1LshxRayNyq+XxB4//+Yqufqx+arZj/YTWh77gTRF9c08cj4iCAAAAID1QxAEAAAAkBKCIAAAAICUEAQBAAAApIQgCAAAACAlBEEAAAAAKSEIAgAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJTIz3UBAM1VcXFxlJWVZe8DAJAO9gNpzgRBAGspk8lESUlJrssAAGA9sx9Ic+bQMAAAAICUEAQBAAAApIQgCAAAACAlBEEAAAAAKSEIAgAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkhCAIAAAAICUEQQAAAAApIQgCAAAASIn8XBcAAEDDq/x6aa5LYC3V7Dv92HzpO6CpEgQBALRAQ399Z65LoAHoRwAamkPDAAAAAFLCiCAAgBaiuLg4ysrKcl0G6yhJkqisrIyIiKKioshkMjmuiHVVXFyc6xIAsgRBAAAtRCaTiZKSklyXQQNo27ZtrksAoIVyaBgAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkhCAIAAAAICUEQQAAAAApIQgCAAAASAlBEAAAAEBKCIIAAAAAUkIQBAAAAJASgiAAAACAlBAEAQAAAKREfq4LAIA0SpIkKioqIiKiuLg4MplMjisCACANjAgCgByoqKiI0tLSKC0tzQZCAADQ2ARBAJADNcMfQRAAAOuLIAgAAAAgJQRBAAAAACkhCAIAAABICUEQAAAAQEoIggAAAABSQhAEAAAAkBKCIAAAAICUEAQBAAAApIQgCAAAACAlBEEAAAAAKSEIAgAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAMiB6urqld4HAIDGJAgCgBz44osvVnofAAAakyAIAAAAICUEQQAAAAApIQgCAAAASAlBEAAAAEBKCIIAAAAAUkIQBAAAAJASgiAAAACAlBAEAQAAAKSEIAgAAAAgJQRBAAAAACkhCAIAAABICUEQAAAAQEoIggAAAABSQhAEAAAAkBI5D4JOPPHEyGQykclkoqCgIHr37h0jRoyIr776KiIi3n///chkMvHqq6+usOyee+4Zw4YNW78FAwAAADRT+bkuICJi6NChcfPNN8eSJUvipZdeihNOOCEymUxceumluS4NAAAAoMXI+YigiIjCwsLo1q1blJaWxqGHHhpDhgyJCRMm5LosAAAAgBalSYwIqunNN9+MZ599Nnr27LnO61q8eHEsXrw4+7i8vHyd1wkAAADQXDWJIOjBBx+Mtm3bxtKlS2Px4sWRl5cX11577Tqv95JLLolf/epXDVAhAAAAQPPXJA4NGzx4cLz66qvxwgsvxAknnBAnnXRSHHHEEeu83pEjR8aCBQuyt7KysgaoFgAAAKB5ahIjgkpKSqJv374RETFu3LgYNGhQjB07Nk455ZRo3759REQsWLBgheXmz58fHTp0qHO9hYWFUVhY2DhFAwAAADQzTWJEUE15eXlx4YUXxs9+9rOorKyMDTfcMDp37hwvvfRSrXbl5eUxY8aM6NevX44qBQAAAGhemlwQFBFx1FFHRatWreK6666LiIjhw4fHb3/727j99tvjvffeiylTpsSxxx4bXbp0icMPPzzH1QIAAAA0D03i0LDl5efnx1lnnRW///3v4/TTT48RI0ZE27Zt49JLL4333nsvNtxww9h1111j0qRJUVRUlOtyAQAAAJqFTJIkSa6LWF/Ky8ujQ4cOsWDBguy5hwAgF6ZNmxbf+c53IiLi2WefjS222CLHFQEA0JzVN/NokoeGAQAAANDwBEEAAAAAKSEIAgAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkhCAIAAAAICUEQQAAAAApIQgCAAAASAlBEADkwAYbbLDS+wAA0JgEQQCQA3l5eSu9DwAAjcmeJwAAAEBKCIIAAAAAUkIQBAAAAJASgiAAAACAlBAEAQAAAKSEIAgAAAAgJQRBAAAAACkhCAIAAABICUEQAAAAQEoIggAAAABSQhAEAAAAkBKCIAAAAICUEAQBAAAApIQgCAAAACAlBEEAAAAAKSEIAoAcKC4uXul9AABoTPm5LgAA0qi4uDjKysqy9wEAYH0QBAFADmQymSgpKcl1GQAApIxDwwAAAABSQhAEAAAAkBKCIAAAAICUEAQBAAAApIQgCAAAACAlUnXVsCRJIiKivLw8x5UAAAAANJxlWcey7KMuqQqCFi5cGBERpaWlOa4EAAAAoOEtXLgwOnToUOf8TLK6qKgFqa6ujo8//jjatWsXmUwm1+U0S+Xl5VFaWhplZWXRvn37XJdDI9DHLZ8+bvn0ccunj1s2/dvy6eOWTx+3fE2xj5MkiYULF0aPHj0iL6/uMwGlakRQXl5ebLLJJrkuo0Vo3759k3mz0zj0ccunj1s+fdzy6eOWTf+2fPq45dPHLV9T6+NVjQRaxsmiAQAAAFJCEAQAAACQEoIg1khhYWH88pe/jMLCwlyXQiPRxy2fPm759HHLp49bNv3b8unjlk8ft3zNuY9TdbJoAAAAgDQzIggAAAAgJQRBAAAAACkhCAIAAABICUEQAAAAQEoIglLoqaeeioMOOih69OgRmUwm7r///lrzL7744thiiy2ipKQkNthggxgyZEi88MILtdrMmzcvjj322Gjfvn107NgxTjnllFi0aFGtNq+//nr813/9V7Rp0yZKS0vj97//fWNvGv9rdX1c049//OPIZDIxZsyYWtP1cdO2uj4+8cQTI5PJ1LoNHTq0Vht93LTV53P89ttvx8EHHxwdOnSIkpKS2HHHHeODDz7Izv/qq6/izDPPjE6dOkXbtm3jiCOOiE8++aTWOj744IM44IADori4ODbaaKO44IILYunSpY29ecTq+3j5z/Cy22WXXZZt43PcdK2ufxctWhRnnXVWbLLJJlFUVBQDBgyIG2+8sVYbn+GmbXV9/Mknn8SJJ54YPXr0iOLi4hg6dGi8++67tdro46brkksuiR133DHatWsXG220URx66KExffr0Wm0aqv8mT54c3/rWt6KwsDD69u0bt9xyS2NvHlG/Pr7ppptizz33jPbt20cmk4n58+evsJ7m+LdYEJRCX375ZQwaNCiuu+66lc7v169fXHvttfHGG2/Ev/71r+jVq1fss88+8emnn2bbHHvssfHWW2/FhAkT4sEHH4ynnnoqTjvttOz88vLy2GeffaJnz57x0ksvxWWXXRYXX3xx3HTTTY2+fay+j5e577774vnnn48ePXqsME8fN2316eOhQ4fG7Nmzs7c77rij1nx93LStro/fe++92G233WKLLbaIyZMnx+uvvx4///nPo02bNtk25513Xvzzn/+Mu+++O5588sn4+OOP4/DDD8/Or6qqigMOOCC+/vrrePbZZ+PPf/5z3HLLLfGLX/yi0beP1fdxzc/v7NmzY9y4cZHJZOKII47ItvE5brpW17/Dhw+P8ePHx2233RZvv/12DBs2LM4666x44IEHsm18hpu2VfVxkiRx6KGHxsyZM+Mf//hHvPLKK9GzZ88YMmRIfPnll9l2+rjpevLJJ+PMM8+M559/PiZMmBBLliyJffbZp8H7b9asWXHAAQfE4MGD49VXX41hw4bFqaeeGo8++uh63d40qk8fV1RUxNChQ+PCCy+scz3N8m9xQqpFRHLfffetss2CBQuSiEgef/zxJEmS5N///ncSEcmLL76YbfPII48kmUwm+eijj5IkSZLrr78+2WCDDZLFixdn2/z0pz9N+vfv3/AbwSrV1ccffvhhsvHGGydvvvlm0rNnz+Sqq67KztPHzcvK+viEE05IDjnkkDqX0cfNy8r6+Oijj06OO+64OpeZP39+UlBQkNx9993ZaW+//XYSEclzzz2XJEmSPPzww0leXl4yZ86cbJsbbrghad++fa1+p/HV5+/xIYcckuy1117Zxz7HzcfK+nfgwIHJqFGjak371re+lVx00UVJkvgMNzfL9/H06dOTiEjefPPN7LSqqqqkS5cuyZ/+9KckSfRxczN37twkIpInn3wySZKG678RI0YkAwcOrPVcRx99dLLvvvs29iaxnOX7uKZJkyYlEZF88cUXtaY317/FRgSxSl9//XXcdNNN0aFDhxg0aFBERDz33HPRsWPH2GGHHbLthgwZEnl5edlDyJ577rnYfffdo3Xr1tk2++67b0yfPj2++OKL9bsRrKC6ujqOP/74uOCCC2LgwIErzNfHLcPkyZNjo402iv79+8fpp58en3/+eXaePm7eqqur46GHHop+/frFvvvuGxtttFHstNNOtQ5LeOmll2LJkiUxZMiQ7LQtttgiNt1003juueci4ps+3nrrraNr167ZNvvuu2+Ul5fHW2+9td62h9X75JNP4qGHHopTTjklO83nuHn7zne+Ew888EB89NFHkSRJTJo0Kd55553YZ599IsJnuLlbvHhxREStUZp5eXlRWFgY//rXvyJCHzc3CxYsiIiIDTfcMCIarv+ee+65WutY1mbZOlh/lu/j+miuf4sFQazUgw8+GG3bto02bdrEVVddFRMmTIjOnTtHRMScOXNio402qtU+Pz8/Ntxww5gzZ062Tc0vvIjIPl7Whty59NJLIz8/P84555yVztfHzd/QoUPj1ltvjSeeeCIuvfTSePLJJ2O//faLqqqqiNDHzd3cuXNj0aJF8bvf/S6GDh0ajz32WBx22GFx+OGHx5NPPhkR3/RR69ato2PHjrWW7dq1qz5uhv785z9Hu3btah1y4HPcvF1zzTUxYMCA2GSTTaJ169YxdOjQuO6662L33XePCJ/h5m5ZIDBy5Mj44osv4uuvv45LL700Pvzww5g9e3ZE6OPmpLq6OoYNGxa77rprbLXVVhHRcP1XV5vy8vKorKxsjM1hJVbWx/XRXP8W5+fkWWnylh2j+tlnn8Wf/vSn+N73vhcvvPDCCm9ymp+XXnoprr766nj55Zcjk8nkuhwayfe///3s/a233jq22Wab2GyzzWLy5Mnx3e9+N4eV0RCqq6sjIuKQQw6J8847LyIitt1223j22WfjxhtvjD322COX5dEIxo0bF8cee2yt0QU0b9dcc008//zz8cADD0TPnj3jqaeeijPPPDN69OixwugAmp+CgoK4995745RTTokNN9wwWrVqFUOGDIn99tsvkiTJdXmsoTPPPDPefPPN7GguWp609bERQaxUSUlJ9O3bN3beeecYO3Zs5Ofnx9ixYyMiolu3bjF37txa7ZcuXRrz5s2Lbt26Zdssf8b8ZY+XtSE3nn766Zg7d25suummkZ+fH/n5+fGf//wnzj///OjVq1dE6OOWqE+fPtG5c+eYMWNGROjj5q5z586Rn58fAwYMqDV9yy23zF41rFu3bvH111+vcHWLTz75RB83M08//XRMnz49Tj311FrTfY6br8rKyrjwwgvjyiuvjIMOOii22WabOOuss+Loo4+Oyy+/PCJ8hluC7bffPl599dWYP39+zJ49O8aPHx+ff/559OnTJyL0cXNx1llnxYMPPhiTJk2KTTbZJDu9ofqvrjbt27ePoqKiht4cVqKuPq6P5vq3WBBEvVRXV2ePdd5ll11i/vz58dJLL2XnT5w4Maqrq2OnnXbKtnnqqadiyZIl2TYTJkyI/v37xwYbbLB+i6eW448/Pl5//fV49dVXs7cePXrEBRdckL06gT5ueT788MP4/PPPo3v37hGhj5u71q1bx4477rjCJU7feeed6NmzZ0R88wOkoKAgnnjiiez86dOnxwcffBC77LJLRHzTx2+88UatHZgJEyZE+/btVwiZyJ2xY8fG9ttvnz1X3zI+x83XkiVLYsmSJZGXV3tXvFWrVtkRfz7DLUeHDh2iS5cu8e6778bUqVPjkEMOiQh93NQlSRJnnXVW3HfffTFx4sTo3bt3rfkN1X+77LJLrXUsa7NsHTSe1fVxfTTbv8U5O001ObNw4cLklVdeSV555ZUkIpIrr7wyeeWVV5L//Oc/yaJFi5KRI0cmzz33XPL+++8nU6dOTU466aSksLCw1lUPhg4dmmy33XbJCy+8kPzrX/9KNt988+SYY47Jzp8/f37StWvX5Pjjj0/efPPN5G9/+1tSXFyc/PGPf8zFJqfOqvp4ZZa/aliS6OOmblV9vHDhwuQnP/lJ8txzzyWzZs1KHn/88eRb3/pWsvnmmydfffVVdh36uGlb3ef43nvvTQoKCpKbbropeffdd5NrrrkmadWqVfL0009n1/HjH/842XTTTZOJEycmU6dOTXbZZZdkl112yc5funRpstVWWyX77LNP8uqrrybjx49PunTpkowcOXK9b28a1ee7esGCBUlxcXFyww03rHQdPsdN1+r6d4899kgGDhyYTJo0KZk5c2Zy8803J23atEmuv/767Dp8hpu21fXxXXfdlUyaNCl57733kvvvvz/p2bNncvjhh9dahz5uuk4//fSkQ4cOyeTJk5PZs2dnbxUVFdk2DdF/M2fOTIqLi5MLLrggefvtt5PrrrsuadWqVTJ+/Pj1ur1pVJ8+nj17dvLKK68kf/rTn5KISJ566qnklVdeST7//PNsm+b4t1gQlELLLn23/O2EE05IKisrk8MOOyzp0aNH0rp166R79+7JwQcfnEyZMqXWOj7//PPkmGOOSdq2bZu0b98+Oemkk5KFCxfWavPaa68lu+22W1JYWJhsvPHGye9+97v1uZmptqo+XpmVBUH6uGlbVR9XVFQk++yzT9KlS5ekoKAg6dmzZ/LDH/6w1qVLk0QfN3X1+RyPHTs26du3b9KmTZtk0KBByf33319rHZWVlckZZ5yRbLDBBklxcXFy2GGHJbNnz67V5v3330/222+/pKioKOncuXNy/vnnJ0uWLFkfm5h69enjP/7xj0lRUVEyf/78la7D57jpWl3/zp49OznxxBOTHj16JG3atEn69++fXHHFFUl1dXV2HT7DTdvq+vjqq69ONtlkk6SgoCDZdNNNk5/97GcrXPJdHzddK+vbiEhuvvnmbJuG6r9JkyYl2267bdK6deukT58+tZ6DxlOfPv7lL3+52jbN8W9xJkmcrQwAAAAgDZwjCAAAACAlBEEAAAAAKSEIAgAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkhCAIAGAVLr744th2221X2ebEE0+MQw89NCfPDQCwJgRBAECLNGfOnDj33HOjb9++0aZNm+jatWvsuuuuccMNN0RFRcV6rWXy5MmRyWSyt65du8YRRxwRM2fOXOVyP/nJT+KJJ55YT1UCAGmQn+sCAAAa2syZM2PXXXeNjh07xm9/+9vYeuuto7CwMN5444246aabYuONN46DDz54vdc1ffr0aNeuXbz77rtx2mmnxUEHHRSvv/56tGrVqla7JEmiqqoq2rZtG23btl3vdQIALZcRQQBAi3PGGWdEfn5+TJ06Nb73ve/FlltuGX369IlDDjkkHnrooTjooIOybT/44IM45JBDom3bttG+ffv43ve+F5988kmd666qqorhw4dHx44do1OnTjFixIhIkqRedW200UbRvXv32H333eMXv/hF/Pvf/44ZM2ZkRww98sgjsf3220dhYWH861//WumhYePGjYuBAwdGYWFhdO/ePc4666zsvPnz58epp54aXbp0ifbt28dee+0Vr7322pq9eABAiyYIAgBalM8//zwee+yxOPPMM6OkpGSlbTKZTEREVFdXxyGHHBLz5s2LJ598MiZMmBAzZ86Mo48+us71X3HFFXHLLbfEuHHj4l//+lfMmzcv7rvvvjWus6ioKCIivv766+y0//mf/4nf/e538fbbb8c222yzwjI33HBDnHnmmXHaaafFG2+8EQ888ED07ds3O/+oo46KuXPnxiOPPBIvvfRSfOtb34rvfve7MW/evDWuDwBomRwaBgC0KDNmzIgkSaJ///61pnfu3Dm++uqriIg488wz49JLL40nnngi3njjjZg1a1aUlpZGRMStt94aAwcOjBdffDF23HHHFdY/ZsyYGDlyZBx++OEREXHjjTfGo48+ukY1zp49Oy6//PLYeOONo3///vHss89GRMSoUaNi7733rnO53/zmN3H++efHueeem522rMZ//etfMWXKlJg7d24UFhZGRMTll18e999/f9xzzz1x2mmnrVGNAEDLZEQQAJAKU6ZMiVdffTUGDhwYixcvjoiIt99+O0pLS7MhUETEgAEDomPHjvH222+vsI4FCxbE7NmzY6eddspOy8/Pjx122KFeNWyyySZRUlISPXr0iC+//DL+/ve/R+vWrbPzV7WeuXPnxscffxzf/e53Vzr/tddei0WLFkWnTp2y5xZq27ZtzJo1K95777161QcAtHxGBAEALUrfvn0jk8nE9OnTa03v06dPRPzfIVm58PTTT0f79u1jo402inbt2q0wv65D2SJWX/eiRYuie/fuMXny5BXmdezYcU1LBQBaKCOCAIAWpVOnTrH33nvHtddeG19++eUq22655ZZRVlYWZWVl2Wn//ve/Y/78+TFgwIAV2nfo0CG6d+8eL7zwQnba0qVL46WXXqpXbb17947NNttspSHQ6rRr1y569epV5+Xkv/Wtb8WcOXMiPz8/+vbtW+vWuXPnNX4+AKBlEgQBAC3O9ddfH0uXLo0ddtgh7rzzznj77bdj+vTpcdttt8W0adOyl2sfMmRIbL311nHsscfGyy+/HFOmTIkf/OAHsccee9R5mNa5554bv/vd7+L++++PadOmxRlnnBHz589fL9t18cUXxxVXXBF/+MMf4t13342XX345rrnmmuy27LLLLnHooYfGY489Fu+//348++yzcdFFF8XUqVPXS30AQNPn0DAAoMXZbLPN4pVXXonf/va3MXLkyPjwww+jsLAwBgwYED/5yU/ijDPOiIhvrh72j3/8I84+++zYfffdIy8vL4YOHZoNV1bm/PPPj9mzZ8cJJ5wQeXl5cfLJJ8dhhx0WCxYsaPTtOuGEE+Krr76Kq666Kn7yk59E586d48gjj8xuy8MPPxwXXXRRnHTSSfHpp59Gt27dYvfdd4+uXbs2em0AQPOQSZIkyXURAAAAADQ+h4YBAAAApIQgCAAAACAlBEEAAAAAKSEIAgAAAEgJQRAAAABASgiCAAAAAFJCEAQAAACQEoIgAAAAgJQQBAEAAACkhCAIAAAAICUEQQAAAAAp8f8BgKJDszTzsEsAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1400x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Aggregate data by country\n",
+    "country_avg_prices = data.groupby('Country')['Price'].mean().reset_index()\n",
+    "# Sort countries by average price\n",
+    "country_avg_prices = country_avg_prices.sort_values(by='Price', ascending=False)\n",
+    "# Bar Plot of Average Gold Prices by Country\n",
+    "plt.figure(figsize=(12, 8))\n",
+    "sns.barplot(x='Price', y='Country', data=country_avg_prices, palette='copper')\n",
+    "plt.title('Average Gold Prices by Country')\n",
+    "plt.xlabel('Average Gold Price')\n",
+    "plt.ylabel('Country')\n",
+    "plt.show()\n",
+    "# Box Plot of Gold Prices by Country\n",
+    "plt.figure(figsize=(14, 8))\n",
+    "sns.boxplot(x='Price', y='Country', data=data, palette='copper')\n",
+    "plt.title('Distribution of Gold Prices by Country')\n",
+    "plt.xlabel('Gold Price')\n",
+    "plt.ylabel('Country')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "# Exclude non-numeric columns (assuming 'Country' is non-numeric)\n",
+    "numeric_data = data.drop(columns=['Country', 'Event'])\n",
+    "\n",
+    "# Calculate correlation matrix\n",
+    "correlation_matrix = numeric_data.corr()\n",
+    "\n",
+    "# Define custom color palette with copper and gold tones\n",
+    "custom_palette = [\"#FFD700\", \"#B87333\", \"#CD7F32\", \"#D2691E\", \"#BC8F8F\", \"#A52A2A\", \"#8B4513\"]\n",
+    "\n",
+    "# Plot heatmap with custom color palette\n",
+    "plt.figure(figsize=(12, 8))\n",
+    "sns.heatmap(correlation_matrix, annot=True, cmap=sns.color_palette(custom_palette), fmt=\".2f\", linewidths=.5)\n",
+    "plt.title('Correlation Heatmap of Variables')\n",
+    "plt.show()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\shawn\\AppData\\Local\\Temp\\ipykernel_3588\\847878419.py:2: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead.\n",
+      "  quarterly_data = data.set_index('Date').resample('Q').agg({'Price': 'mean', 'Vol_K': 'mean'})\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "# Resample data by quarter and calculate the average price and volume for each quarter\n",
+    "quarterly_data = data.set_index('Date').resample('Q').agg({'Price': 'mean', 'Vol_K': 'mean'})\n",
+    "\n",
+    "fig, ax1 = plt.subplots(figsize=(12, 6))\n",
+    "\n",
+    "# Plot Price trend\n",
+    "ax1.plot(quarterly_data.index, quarterly_data['Price'], marker='o', linestyle='-', color='#FFD700', label='Price')  # Gold color\n",
+    "ax1.set_xlabel('Quarter')\n",
+    "ax1.set_ylabel('Price', color='Black')  # Gold color\n",
+    "ax1.tick_params('y', colors='Black')  # Gold color\n",
+    "\n",
+    "# Create a secondary y-axis for Volume\n",
+    "ax2 = ax1.twinx()\n",
+    "ax2.plot(quarterly_data.index, quarterly_data['Vol_K'], marker='s', linestyle='-', color='#DAA520', label='Volume')  # Dark gold color\n",
+    "ax2.set_ylabel('Volume (Vol K)', color='Black')  # Dark gold color\n",
+    "ax2.tick_params('y', colors='Black')  # Dark gold color\n",
+    "\n",
+    "# Add legend\n",
+    "lines, labels = ax1.get_legend_handles_labels()\n",
+    "lines2, labels2 = ax2.get_legend_handles_labels()\n",
+    "ax2.legend(lines + lines2, labels + labels2, loc='upper left')\n",
+    "\n",
+    "plt.title('Price and Volume Trend Over Quarters')\n",
+    "plt.grid(True)\n",
+    "\n",
+    "plt.tight_layout()  # Adjust layout to prevent clipping of labels\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "           Date   Price   Vol_K  Change_percent Country  \\\n",
+      "0    2023-12-01  2089.7  241.62            1.58      US   \n",
+      "1    2023-11-30  2057.2  151.92           -0.48      US   \n",
+      "2    2023-11-29  2067.1  197.79            0.81      US   \n",
+      "3    2023-11-28  2050.5    1.86            1.35     NaN   \n",
+      "4    2023-11-27  2023.1    1.06            0.47     NaN   \n",
+      "...         ...     ...     ...             ...     ...   \n",
+      "1274 2019-01-08  1285.9  221.92           -0.31      EA   \n",
+      "1275 2019-01-07  1289.9  204.68            0.32      CA   \n",
+      "1276 2019-01-04  1285.8  316.06           -0.70      US   \n",
+      "1277 2019-01-03  1294.8  244.54            0.83     NaN   \n",
+      "1278 2019-01-02  1284.1  235.33            0.22     NaN   \n",
+      "\n",
+      "                            Event  D_Consensus  D_Forecast Sentiment  \n",
+      "0          ISM Manufacturing PMI      1.888772    1.053741  Positive  \n",
+      "1       Core PCE Price Index MoM      0.000000    0.199005  Negative  \n",
+      "2     GDP Growth Rate QoQ 2nd Est     0.362976    0.544959  Positive  \n",
+      "3                             NaN     1.097919    1.483586   Neutral  \n",
+      "4                             NaN     1.097919    1.483586   Neutral  \n",
+      "...                           ...          ...         ...       ...  \n",
+      "1274         Business Confidence     12.099644   19.178082  Negative  \n",
+      "1275                Ivey PMI s.a      4.936170    5.110733  Positive  \n",
+      "1276           Non Farm Payrolls     55.102041   61.506276  Negative  \n",
+      "1277                          NaN     1.097919    1.483586   Neutral  \n",
+      "1278                          NaN     1.097919    1.483586   Neutral  \n",
+      "\n",
+      "[1279 rows x 9 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "def assign_sentiment(change_percent, event):\n",
+    "  \"\"\"Assigns sentiment based on the change percent value, considering empty events.\n",
+    "\n",
+    "  Args:\n",
+    "      change_percent (float): The percent change in price.\n",
+    "      event (str): The event associated with the price change (may be empty).\n",
+    "\n",
+    "  Returns:\n",
+    "      str: \"Positive\" if change_percent is positive, \"Negative\" if negative, \n",
+    "           \"Neutral\" otherwise, or \"Neutral\" if event is empty.\n",
+    "  \"\"\"\n",
+    "  # Check if event is None (missing value) or an empty string after stripping\n",
+    "  if pd.isna(event) or (isinstance(event, str) and event.strip() == ''):\n",
+    "    return \"Neutral\"\n",
+    "  elif change_percent > 0:\n",
+    "    return \"Positive\"\n",
+    "  elif change_percent < 0:\n",
+    "    return \"Negative\"\n",
+    "  else:\n",
+    "    return \"Neutral\"\n",
+    "\n",
+    "# Add a new 'Sentiment' column with sentiment values based on 'Change_percent'\n",
+    "data['Sentiment'] = data.apply(lambda row: assign_sentiment(row['Change_percent'], row['Event']), axis=1)\n",
+    "\n",
+    "# Save the data to a CSV file\n",
+    "# data.to_csv('sentiment_labeled_data.csv', index=False)\n",
+    "\n",
+    "print(data)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## SENTIMENT ANALYSIS FOR EVENTS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.preprocessing import LabelEncoder, StandardScaler\n",
+    "from sklearn.metrics import classification_report, accuracy_score\n",
+    "\n",
+    "# Load the dataset\n",
+    "data = pd.read_csv('C:/Users/shawn/OneDrive/Documents/GitHub/ML-Crate/Dataset/sentiment_labeled_data.csv')\n",
+    "\n",
+    "\n",
+    "# Encode categorical features\n",
+    "label_encoder = LabelEncoder()\n",
+    "data['Country'] = label_encoder.fit_transform(data['Country'].fillna('Unknown'))\n",
+    "data['Event'] = label_encoder.fit_transform(data['Event'])\n",
+    "\n",
+    "# Define features and target\n",
+    "features = ['Price', 'Vol_K', 'Change_percent', 'D_Consensus', 'D_Forecast', 'Country', 'Event']\n",
+    "X = data[features]\n",
+    "y = data['Sentiment']\n",
+    "\n",
+    "# Encode target labels\n",
+    "y = label_encoder.fit_transform(y)\n",
+    "\n",
+    "# Split the data into training and testing sets\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
+    "\n",
+    "# Standardize the features\n",
+    "scaler = StandardScaler()\n",
+    "X_train = scaler.fit_transform(X_train)\n",
+    "X_test = scaler.transform(X_test)\n",
+    "\n",
+    "model_name=[]\n",
+    "model_accu = []"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## RANDOM FOREST"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy: 0.99609375\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "    Negative       0.99      1.00      0.99        85\n",
+      "     Neutral       1.00      0.99      0.99        93\n",
+      "    Positive       1.00      1.00      1.00        78\n",
+      "\n",
+      "    accuracy                           1.00       256\n",
+      "   macro avg       1.00      1.00      1.00       256\n",
+      "weighted avg       1.00      1.00      1.00       256\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "\n",
+    "\n",
+    "# Train a Random Forest Classifier\n",
+    "model = RandomForestClassifier(n_estimators=100, random_state=42)\n",
+    "model.fit(X_train, y_train)\n",
+    "\n",
+    "# Make predictions\n",
+    "y_pred = model.predict(X_test)\n",
+    "\n",
+    "# Evaluate the model\n",
+    "print('Accuracy:', accuracy_score(y_test, y_pred))\n",
+    "print(classification_report(y_test, y_pred, target_names=label_encoder.classes_))\n",
+    "\n",
+    "model_name.append('Random Forest')\n",
+    "model_accu.append(accuracy_score(y_test, y_pred))\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## SVM"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy: 0.9765625\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "    Negative       0.99      0.96      0.98        85\n",
+      "     Neutral       1.00      0.97      0.98        93\n",
+      "    Positive       0.94      1.00      0.97        78\n",
+      "\n",
+      "    accuracy                           0.98       256\n",
+      "   macro avg       0.98      0.98      0.98       256\n",
+      "weighted avg       0.98      0.98      0.98       256\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.svm import SVC\n",
+    "\n",
+    "# Train a Support Vector Classifier\n",
+    "model = SVC(kernel='linear', random_state=42)\n",
+    "model.fit(X_train, y_train)\n",
+    "\n",
+    "# Make predictions\n",
+    "y_pred = model.predict(X_test)\n",
+    "\n",
+    "# Evaluate the model\n",
+    "print('Accuracy:', accuracy_score(y_test, y_pred))\n",
+    "print(classification_report(y_test, y_pred, target_names=label_encoder.classes_))\n",
+    "\n",
+    "model_name.append('SVM')\n",
+    "model_accu.append(accuracy_score(y_test, y_pred))\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## LOGISTIC REGRESSION"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy: 0.97265625\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "    Negative       0.97      0.98      0.97        85\n",
+      "     Neutral       0.98      0.96      0.97        93\n",
+      "    Positive       0.97      0.99      0.98        78\n",
+      "\n",
+      "    accuracy                           0.97       256\n",
+      "   macro avg       0.97      0.97      0.97       256\n",
+      "weighted avg       0.97      0.97      0.97       256\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.linear_model import LogisticRegression\n",
+    "\n",
+    "# Train a Logistic Regression model\n",
+    "model = LogisticRegression(random_state=42, max_iter=1000)\n",
+    "model.fit(X_train, y_train)\n",
+    "\n",
+    "# Make predictions\n",
+    "y_pred = model.predict(X_test)\n",
+    "\n",
+    "# Evaluate the model\n",
+    "print('Accuracy:', accuracy_score(y_test, y_pred))\n",
+    "print(classification_report(y_test, y_pred, target_names=label_encoder.classes_))\n",
+    "\n",
+    "model_name.append('Logistic Regression')\n",
+    "model_accu.append(accuracy_score(y_test, y_pred))\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## GRADIENT BOOSTER "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy: 1.0\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "    Negative       1.00      1.00      1.00        85\n",
+      "     Neutral       1.00      1.00      1.00        93\n",
+      "    Positive       1.00      1.00      1.00        78\n",
+      "\n",
+      "    accuracy                           1.00       256\n",
+      "   macro avg       1.00      1.00      1.00       256\n",
+      "weighted avg       1.00      1.00      1.00       256\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.ensemble import GradientBoostingClassifier\n",
+    "\n",
+    "# Train a Gradient Boosting Classifier\n",
+    "model = GradientBoostingClassifier(random_state=42)\n",
+    "model.fit(X_train, y_train)\n",
+    "\n",
+    "# Make predictions\n",
+    "y_pred = model.predict(X_test)\n",
+    "\n",
+    "# Evaluate the model\n",
+    "print('Accuracy:', accuracy_score(y_test, y_pred))\n",
+    "print(classification_report(y_test, y_pred, target_names=label_encoder.classes_))\n",
+    "\n",
+    "model_name.append('Gradient Boosting')\n",
+    "model_accu.append(accuracy_score(y_test, y_pred))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Models</th>\n",
+       "      <th>Accuracies</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Random Forest</td>\n",
+       "      <td>0.996094</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>SVM</td>\n",
+       "      <td>0.976562</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Logistic Regression</td>\n",
+       "      <td>0.972656</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Gradient Boosting</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                Models  Accuracies\n",
+       "0        Random Forest    0.996094\n",
+       "1                  SVM    0.976562\n",
+       "2  Logistic Regression    0.972656\n",
+       "3    Gradient Boosting    1.000000"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model_comp=pd.DataFrame({'Models':model_name, 'Accuracies':model_accu})\n",
+    "model_comp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='Models'>"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "model_comp.plot(x='Models',y='Accuracies')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/The Effect of Economic News on Gold Prices Analysis/requirements.txt b/The Effect of Economic News on Gold Prices Analysis/requirements.txt
new file mode 100644
index 000000000..dc601bdca
--- /dev/null
+++ b/The Effect of Economic News on Gold Prices Analysis/requirements.txt	
@@ -0,0 +1,5 @@
+Pandas
+Seaborn
+Numpy
+Matplotlib
+Sklearn
\ No newline at end of file