Members: Agnij Moitra, Isabella, Harpreet_Wazir and Pranav Srikanth
Using this, you can:
- Use a quantum algorithm to predict new stock prices.
- Make informed choices of stocks to invest in.
For as long as they have existed, stock markets have played a crucial role in the lives of all of us as they allow us to make financial gains, and a strengthened economy leads to an improved quality of life overall. However, most of these calculations in working out which markets to invest in are done by classical computers which have many limits. For example, they are unable to process large amounts of data at one time and also are slower in their computation times and as more data is generated on the conditions of stock markets around the world, we need to find a quicker method of predicting stock markets and shares around the world in order to continue predicting at the same rate that we are at the moment else we will be unable to keep up with the increasing amount of data that we have. Building more and more classical computers is not going to solve the problem as the amount of data rises, they will still be slow and unable to process the data; we need to find a new solution which can process large quantities of data at quicker speeds. We cannot only rely on quantum computing, however, because the technology has not fully been developed yet. However, by using a hybrid of the two, specifically VQE, we can use a combination of the two methods to find the best possible stocks to buy, without being limited by time, storage or available technology.
To solve the problem of finding the best way to effectively predict the best stock prices to buy, we used VQE which combines quantum and classical computing to allow us to calculate and predict stocks more effectively. To do this, we web scraped data from Qandl on several different stock markets over the last four years and then used qiskit finance portfolio optimisation to calculate which ones are most likely to be the strongest and most valuable within the near future. By doing this, we are able to work out using a quantum approximate optimisation algorithm which stocks are the best to invest in and which ones perhaps are not worth investing in, in the near future. If successful, this will help many people in the finance industry as it will allow them to invest only in stock markets which are likely to increase their investment, leading to growth of both the national and global economy. This can allow services and the overall quality of people’s lives to improve as investment can be more successful and effective due to QAOA being one of the most effective optimisation processes at the moment. This means that the calculations are likely to be more accurate than the classical algorithms that we mostly rely on using today.
Entered Stocks
Result Stocks
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