3-momentum_algorithmic.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Developing \"Momentum\" Trading Strategy\n",
    "* Many differnt takes on this strategy\n",
    "* Sometimes referred to as trend following\n",
    "* Whatever you do and call it, you first need to research potential trading signals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pandas_datareader as pdr\n",
    "import matplotlib.pyplot as plt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Download data: \n",
    "* Many services for this, some paid some free \n",
    "* Yahoo Finance API\n",
    "* Typically trading \"systems\" involve a number of securities\n",
    "* For this demonstration we are just going to look at GLD --> the gold ETF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-04-11</th>\n",
       "      <td>1</td>\n",
       "      <td>119.470001</td>\n",
       "      <td>120.300003</td>\n",
       "      <td>119.419998</td>\n",
       "      <td>120.029999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04-12</th>\n",
       "      <td>2</td>\n",
       "      <td>120.230003</td>\n",
       "      <td>120.349998</td>\n",
       "      <td>119.550003</td>\n",
       "      <td>120.050003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04-13</th>\n",
       "      <td>3</td>\n",
       "      <td>119.370003</td>\n",
       "      <td>119.430000</td>\n",
       "      <td>118.559998</td>\n",
       "      <td>118.769997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04-14</th>\n",
       "      <td>4</td>\n",
       "      <td>118.089996</td>\n",
       "      <td>118.190002</td>\n",
       "      <td>116.949997</td>\n",
       "      <td>117.110001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04-15</th>\n",
       "      <td>5</td>\n",
       "      <td>117.330002</td>\n",
       "      <td>118.120003</td>\n",
       "      <td>117.190002</td>\n",
       "      <td>117.919998</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            day        Open        High         Low       Close\n",
       "Date                                                           \n",
       "2016-04-11    1  119.470001  120.300003  119.419998  120.029999\n",
       "2016-04-12    2  120.230003  120.349998  119.550003  120.050003\n",
       "2016-04-13    3  119.370003  119.430000  118.559998  118.769997\n",
       "2016-04-14    4  118.089996  118.190002  116.949997  117.110001\n",
       "2016-04-15    5  117.330002  118.120003  117.190002  117.919998"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gld = pdr.get_data_yahoo('GLD')\n",
    "day = np.arange(1, len(gld) + 1)\n",
    "gld['day'] = day\n",
    "gld.drop(columns=['Adj Close', 'Volume'], inplace = True)\n",
    "gld = gld[['day', 'Open', 'High', 'Low', 'Close']]\n",
    "gld.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 1258 entries, 2016-04-11 to 2021-04-08\n",
      "Data columns (total 5 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   day     1258 non-null   int64  \n",
      " 1   Open    1258 non-null   float64\n",
      " 2   High    1258 non-null   float64\n",
      " 3   Low     1258 non-null   float64\n",
      " 4   Close   1258 non-null   float64\n",
      "dtypes: float64(4), int64(1)\n",
      "memory usage: 59.0 KB\n"
     ]
    }
   ],
   "source": [
    "gld.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Add data/transform data\n",
    "* calculate signal based on some price or statistical action\n",
    "* we are going to try a moving average crossover to generate signals\n",
    "* for this strategy we will always by \"in\" a trade, either long or short\n",
    "* we are modeling; this means real life variation should be expected"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Add moving averages to the data frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>9-day</th>\n",
       "      <th>21-day</th>\n",
       "      <th>signal</th>\n",
       "      <th>return</th>\n",
       "      <th>system_return</th>\n",
       "      <th>entry</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-06-07</th>\n",
       "      <td>41</td>\n",
       "      <td>118.500000</td>\n",
       "      <td>119.019997</td>\n",
       "      <td>118.410004</td>\n",
       "      <td>118.820000</td>\n",
       "      <td>117.052222</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1</td>\n",
       "      <td>-0.000841</td>\n",
       "      <td>0.000841</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-08</th>\n",
       "      <td>42</td>\n",
       "      <td>120.300003</td>\n",
       "      <td>120.779999</td>\n",
       "      <td>120.230003</td>\n",
       "      <td>120.580002</td>\n",
       "      <td>117.452222</td>\n",
       "      <td>119.066192</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.014704</td>\n",
       "      <td>-0.014704</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-09</th>\n",
       "      <td>43</td>\n",
       "      <td>120.610001</td>\n",
       "      <td>121.480003</td>\n",
       "      <td>120.550003</td>\n",
       "      <td>121.250000</td>\n",
       "      <td>117.971111</td>\n",
       "      <td>119.079049</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.005541</td>\n",
       "      <td>-0.005541</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-10</th>\n",
       "      <td>44</td>\n",
       "      <td>121.550003</td>\n",
       "      <td>122.099998</td>\n",
       "      <td>121.180000</td>\n",
       "      <td>121.739998</td>\n",
       "      <td>118.651110</td>\n",
       "      <td>119.060953</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.004033</td>\n",
       "      <td>-0.004033</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-13</th>\n",
       "      <td>45</td>\n",
       "      <td>122.800003</td>\n",
       "      <td>122.830002</td>\n",
       "      <td>122.029999</td>\n",
       "      <td>122.639999</td>\n",
       "      <td>119.382222</td>\n",
       "      <td>119.131429</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.007366</td>\n",
       "      <td>-0.007366</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-14</th>\n",
       "      <td>46</td>\n",
       "      <td>123.000000</td>\n",
       "      <td>123.059998</td>\n",
       "      <td>122.300003</td>\n",
       "      <td>122.769997</td>\n",
       "      <td>120.141110</td>\n",
       "      <td>119.181905</td>\n",
       "      <td>1</td>\n",
       "      <td>0.001059</td>\n",
       "      <td>0.001059</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            day        Open        High         Low       Close       9-day  \\\n",
       "Date                                                                          \n",
       "2016-06-07   41  118.500000  119.019997  118.410004  118.820000  117.052222   \n",
       "2016-06-08   42  120.300003  120.779999  120.230003  120.580002  117.452222   \n",
       "2016-06-09   43  120.610001  121.480003  120.550003  121.250000  117.971111   \n",
       "2016-06-10   44  121.550003  122.099998  121.180000  121.739998  118.651110   \n",
       "2016-06-13   45  122.800003  122.830002  122.029999  122.639999  119.382222   \n",
       "2016-06-14   46  123.000000  123.059998  122.300003  122.769997  120.141110   \n",
       "\n",
       "                21-day  signal    return  system_return  entry  \n",
       "Date                                                            \n",
       "2016-06-07         NaN      -1 -0.000841       0.000841    0.0  \n",
       "2016-06-08  119.066192      -1  0.014704      -0.014704    0.0  \n",
       "2016-06-09  119.079049      -1  0.005541      -0.005541    0.0  \n",
       "2016-06-10  119.060953      -1  0.004033      -0.004033    0.0  \n",
       "2016-06-13  119.131429      -1  0.007366      -0.007366    0.0  \n",
       "2016-06-14  119.181905       1  0.001059       0.001059    2.0  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gld['9-day'] = gld['Close'].rolling(9).mean()\n",
    "gld['21-day'] = gld['Close'].rolling(21).mean()\n",
    "gld[19:25]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Add \"signal\" column  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>9-day</th>\n",
       "      <th>21-day</th>\n",
       "      <th>signal</th>\n",
       "      <th>return</th>\n",
       "      <th>system_return</th>\n",
       "      <th>entry</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-06-08</th>\n",
       "      <td>42</td>\n",
       "      <td>120.300003</td>\n",
       "      <td>120.779999</td>\n",
       "      <td>120.230003</td>\n",
       "      <td>120.580002</td>\n",
       "      <td>117.452222</td>\n",
       "      <td>119.066192</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.014704</td>\n",
       "      <td>-0.014704</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-09</th>\n",
       "      <td>43</td>\n",
       "      <td>120.610001</td>\n",
       "      <td>121.480003</td>\n",
       "      <td>120.550003</td>\n",
       "      <td>121.250000</td>\n",
       "      <td>117.971111</td>\n",
       "      <td>119.079049</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.005541</td>\n",
       "      <td>-0.005541</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-10</th>\n",
       "      <td>44</td>\n",
       "      <td>121.550003</td>\n",
       "      <td>122.099998</td>\n",
       "      <td>121.180000</td>\n",
       "      <td>121.739998</td>\n",
       "      <td>118.651110</td>\n",
       "      <td>119.060953</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.004033</td>\n",
       "      <td>-0.004033</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-13</th>\n",
       "      <td>45</td>\n",
       "      <td>122.800003</td>\n",
       "      <td>122.830002</td>\n",
       "      <td>122.029999</td>\n",
       "      <td>122.639999</td>\n",
       "      <td>119.382222</td>\n",
       "      <td>119.131429</td>\n",
       "      <td>1</td>\n",
       "      <td>0.007366</td>\n",
       "      <td>-0.007366</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-14</th>\n",
       "      <td>46</td>\n",
       "      <td>123.000000</td>\n",
       "      <td>123.059998</td>\n",
       "      <td>122.300003</td>\n",
       "      <td>122.769997</td>\n",
       "      <td>120.141110</td>\n",
       "      <td>119.181905</td>\n",
       "      <td>1</td>\n",
       "      <td>0.001059</td>\n",
       "      <td>0.001059</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "            day        Open        High         Low       Close       9-day  \\\n",
       "Date                                                                          \n",
       "2016-06-08   42  120.300003  120.779999  120.230003  120.580002  117.452222   \n",
       "2016-06-09   43  120.610001  121.480003  120.550003  121.250000  117.971111   \n",
       "2016-06-10   44  121.550003  122.099998  121.180000  121.739998  118.651110   \n",
       "2016-06-13   45  122.800003  122.830002  122.029999  122.639999  119.382222   \n",
       "2016-06-14   46  123.000000  123.059998  122.300003  122.769997  120.141110   \n",
       "\n",
       "                21-day  signal    return  system_return  entry  \n",
       "Date                                                            \n",
       "2016-06-08  119.066192      -1  0.014704      -0.014704    0.0  \n",
       "2016-06-09  119.079049      -1  0.005541      -0.005541    0.0  \n",
       "2016-06-10  119.060953      -1  0.004033      -0.004033    0.0  \n",
       "2016-06-13  119.131429       1  0.007366      -0.007366    0.0  \n",
       "2016-06-14  119.181905       1  0.001059       0.001059    2.0  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gld['signal'] = np.where(gld['9-day'] > gld['21-day'], 1, 0)\n",
    "gld['signal'] = np.where(gld['9-day'] < gld['21-day'], -1, gld['signal'])\n",
    "gld.dropna(inplace=True)\n",
    "gld.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Calculate Instantaneous returns/system returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>day</th>\n",
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       "      <th>Close</th>\n",
       "      <th>9-day</th>\n",
       "      <th>21-day</th>\n",
       "      <th>signal</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-06-08</th>\n",
       "      <td>42</td>\n",
       "      <td>120.300003</td>\n",
       "      <td>120.779999</td>\n",
       "      <td>120.230003</td>\n",
       "      <td>120.580002</td>\n",
       "      <td>117.452222</td>\n",
       "      <td>119.066192</td>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-09</th>\n",
       "      <td>43</td>\n",
       "      <td>120.610001</td>\n",
       "      <td>121.480003</td>\n",
       "      <td>120.550003</td>\n",
       "      <td>121.250000</td>\n",
       "      <td>117.971111</td>\n",
       "      <td>119.079049</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.005541</td>\n",
       "      <td>-0.005541</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-10</th>\n",
       "      <td>44</td>\n",
       "      <td>121.550003</td>\n",
       "      <td>122.099998</td>\n",
       "      <td>121.180000</td>\n",
       "      <td>121.739998</td>\n",
       "      <td>118.651110</td>\n",
       "      <td>119.060953</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.004033</td>\n",
       "      <td>-0.004033</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-13</th>\n",
       "      <td>45</td>\n",
       "      <td>122.800003</td>\n",
       "      <td>122.830002</td>\n",
       "      <td>122.029999</td>\n",
       "      <td>122.639999</td>\n",
       "      <td>119.382222</td>\n",
       "      <td>119.131429</td>\n",
       "      <td>1</td>\n",
       "      <td>0.007366</td>\n",
       "      <td>0.007366</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-14</th>\n",
       "      <td>46</td>\n",
       "      <td>123.000000</td>\n",
       "      <td>123.059998</td>\n",
       "      <td>122.300003</td>\n",
       "      <td>122.769997</td>\n",
       "      <td>120.141110</td>\n",
       "      <td>119.181905</td>\n",
       "      <td>1</td>\n",
       "      <td>0.001059</td>\n",
       "      <td>0.001059</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            day        Open        High         Low       Close       9-day  \\\n",
       "Date                                                                          \n",
       "2016-06-08   42  120.300003  120.779999  120.230003  120.580002  117.452222   \n",
       "2016-06-09   43  120.610001  121.480003  120.550003  121.250000  117.971111   \n",
       "2016-06-10   44  121.550003  122.099998  121.180000  121.739998  118.651110   \n",
       "2016-06-13   45  122.800003  122.830002  122.029999  122.639999  119.382222   \n",
       "2016-06-14   46  123.000000  123.059998  122.300003  122.769997  120.141110   \n",
       "\n",
       "                21-day  signal    return  system_return  entry  \n",
       "Date                                                            \n",
       "2016-06-08  119.066192      -1       NaN            NaN    NaN  \n",
       "2016-06-09  119.079049      -1  0.005541      -0.005541    0.0  \n",
       "2016-06-10  119.060953      -1  0.004033      -0.004033    0.0  \n",
       "2016-06-13  119.131429       1  0.007366       0.007366    2.0  \n",
       "2016-06-14  119.181905       1  0.001059       0.001059    0.0  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gld['return'] = np.log(gld['Close']).diff()\n",
    "gld['system_return'] = gld['signal'] * gld['return']\n",
    "gld['entry'] = gld.signal.diff()\n",
    "gld.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot trades on time series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['figure.figsize'] = 12, 6\n",
    "plt.grid(True, alpha = .3)\n",
    "plt.plot(gld.iloc[-252:]['Close'], label = 'GLD')\n",
    "plt.plot(gld.iloc[-252:]['9-day'], label = '9-day')\n",
    "plt.plot(gld.iloc[-252:]['21-day'], label = '21-day')\n",
    "plt.plot(gld[-252:].loc[gld.entry == 2].index, gld[-252:]['9-day'][gld.entry == 2], '^',\n",
    "         color = 'g', markersize = 12)\n",
    "plt.plot(gld[-252:].loc[gld.entry == -2].index, gld[-252:]['21-day'][gld.entry == -2], 'v',\n",
    "         color = 'r', markersize = 12)\n",
    "plt.legend(loc=2);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(np.exp(gld['return']).cumprod(), label='Buy/Hold')\n",
    "plt.plot(np.exp(gld['system_return']).cumprod(), label='System')\n",
    "plt.legend(loc=2)\n",
    "plt.grid(True, alpha=.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.3653996523304317"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.exp(gld['return']).cumprod()[-1] -1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6523109676509895"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.exp(gld['system_return']).cumprod()[-1] -1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}