Strategy: Time of Day

"Time of Day" trading looks to see if there are certain times of the day that the AI model is more accurate, to then only trade during those times.

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 Time of Day strategy would do in live trading for real. To keep it simple, we enter each trade at the day's open and exit at the close of the day.

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 Time of Day 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.