When it comes to using machine learning in the stock market, there are multiple approaches a trader can do to utilize ML models. From determining future risk to predicting stock prices, machine learning can be used for virtually any kind of financial modeling.

In our previous articles, we delved into the usage of two Time Series models: SARIMAX and Facebook Prophet. We utilized both of these models to forecast the potential, future prices of Bitcoin. Check out the following article if you are interested:

In another article, we used classification models to classify stocks based on their performance in quarterly reports. You can read about the entire process of how we engineered different features from these reports and trained our classification models to determine investment decisions in the article below:

These are just a couple examples of how we can utilize machine learning models for financial markets.

In these articles, we just used models to predict future prices, however, that is just half the battle. The next step is how do we evaluate these models if they were to actually be used while trading? The answer to that question is called — Backtesting.

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