We train the model based on the difference between the predicted price and the actual price as the criterion. Additionally, we also consider the accuracy of the predicted direction, not just the price.

Directional accuracy is a metric that measures how closely the predicted price and the actual price of an asset move in the same direction. For example, if the predicted price for the next day is higher and the actual price also increases, the DA result would be True (1). However, if the actual price moves in the opposite direction, the result would be False (0).

And, BTCGPT currently uses two models, one for daily predictions and the other for weekly predictions. Ideally, we would like both models to provide the same predictions, but in reality, due to differences in the training data and model architecture, they may produce different results. If you look at the direction accuracy at the bottom of the chart, you can see that there is also a difference in the prediction accuracy between the two models. Currently, the daily model is showing higher accuracy than the weekly model.