Learn how to use Python to identify similarities in stock movements
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Whether you are crafting a portfolio and want to incorporate diversification or trying to find stocks for a Pairs Trading strategy, the ability to calculate the correlation between the movement of two stocks is a must.
Having a portfolio of stocks that are not closely correlated allows you to tap into different performing assets that will likely not drop too much together. For example, owning a portfolio of only airline stocks during the pandemic would have you down an average of about 38% on the year. However, by diversifying the portfolio with a combination of stocks from technology, retail, or virtually any other sector, the loss would be a lot less (if any at all).
Unless you are using a Pairs Trading strategy, the best bet is to lower the amount of correlation in your portfolio to maximize the amount of diversification! And that is what we’ll be doing today — calculating and sorting the correlation between a list of stocks. The process is entirely intuitive and by the end of this article, you too should be able to recreate the program within minutes and only a few lines of code!
The entire code to the project in this article is within this GitHub Gist.
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