Stock Price Prediction AI
The "Big Move" strategy is based on the assumption that our AI stock trading model is more accurate at making predictions after a stock goes up or down by a large amount. For example, if the stock goes down 3% in a day, is it likely to keep going down the next day?
To test this theory, we ran a backtest, which means we simulated how much profit it would have made if we had traded it for real using historical data. This is a good indication of how well the Big Move strategy would do in live trading for real.
Results: In our backtest, the AI model's accuracy (up or down prediction) was ______.
The profit/loss backtest had a Profit Factor (PF) of ____ and is shown in the table and chart below. A PF greater than 1 means it would have made a profit. This backtest does not include commissions or the bid/ask spread.
You can run this backtest yourself in our Big Move Google Colab notebook: Pickstocks.com - Machine Learning. It uses our open-source GitHub repo at Pickstocks GitHub. You can also change the data or AI strategy yourself if you want and then backtest it using our repo.