The "Prediction_Strategy" is a trading strategy implemented in Python for backtesting purposes. It uses various technical indicators and a machine learning model to generate buy and sell signals for trading. Here's a breakdown of the strategy:
Indicator Calculation:
The strategy calculates multiple indicators such as moving averages (SMA), maximum difference, minimum difference, standard deviation, and returns for different periods.
It also calculates the z-score based on the 13-period moving average.
Machine Learning Model: The strategy loads a pre-trained machine learning model from a pickle file.
The model is used to make predictions on a set of features derived from the indicator values. Buy Signal Generation: The strategy generates a buy signal when the predicted probability of a specific class (pred4) is greater than 0.45. The volume of the asset being traded must be greater than 0 for the buy signal to be considered. Sell Signal Generation: The strategy generates a sell signal when the predicted probability of a specific class (pred4) is less than 0.28. The volume of the asset being traded must be greater than 0 for the sell signal to be considered. Overall, the strategy aims to identify potential buying opportunities when the predicted probability of a positive outcome is high and selling opportunities when the predicted probability of a negative outcome is high. It uses a combination of technical indicators and machine learning to make these predictions.
It also calculates the z-score based on the 13-period moving average.
Machine Learning Model: The strategy loads a pre-trained machine learning model from a pickle file.
The model is used to make predictions on a set of features derived from the indicator values. Buy Signal Generation: The strategy generates a buy signal when the predicted probability of a specific class (pred4) is greater than 0.45. The volume of the asset being traded must be greater than 0 for the buy signal to be considered. Sell Signal Generation: The strategy generates a sell signal when the predicted probability of a specific class (pred4) is less than 0.28. The volume of the asset being traded must be greater than 0 for the sell signal to be considered. Overall, the strategy aims to identify potential buying opportunities when the predicted probability of a positive outcome is high and selling opportunities when the predicted probability of a negative outcome is high. It uses a combination of technical indicators and machine learning to make these predictions.
stoploss: -0.9 timeframe: 1h hash(sha256): cb4c9523b5b38a9bc87112156d573affc87b23cdeadc328bbd33071c10d2d55b indicators: volume time_dayofweek pred4 z_score_120 f"ma_i close f"maxdiff_i date time_hourmin f"smadiff_i f"std_i time_hour
No similar strategies found. (based on used indicators)
last change: 2024-04-29 19:37:28