XGTraderAGI Training and Model Only XGBOOST

This repository contains a trading strategy script that leverages the XGBoost machine learning algorithm to predict trading signals (Buy, Sell, or Hold) for various cryptocurrencies based on a series of technical indicators.

Learn How to use this:

Link

Features:

1. Data Loading: Functions to load data from single or multiple CSV files.
2. Preprocessing: Handles missing values, encodes categorical variables, and scales numerical features.
3. Feature Generation: Creates various technical indicators like EMA, MACD, RSI, and more.
4. Model Training: Uses Bayesian optimization for hyperparameter tuning and trains an XGBoost classifier.
5. Signal Generation: Predicts trading signals based on the trained model.
6. Evaluation: Computes various performance metrics such as accuracy, precision, recall, and ROC-AUC.
7. Visualization: Plots the stock's close prices and overlays Buy and Sell signals.

Prerequisites:

Ensure you have the following libraries installed:

• pandas
• numpy
• xgboost
• scikit-learn
• matplotlib
• joblib
• ta
• skopt
• logging

You can install these using pip:

pip install pandas numpy xgboost scikit-learn matplotlib joblib ta[all] scikit-optimize logging

Usage:

1. Data Format:

   • Make sure your data is in CSV format with columns like 'Close', 'High', 'Low', 'Volume', etc.
   • For training, you can use multiple CSV files representing data from different cryptocurrencies.

2. Training the Model:

   • Place your CSV files in a folder named data.
   • Run the script and choose the training option:

   python trading_script.py

   When prompted, choose:

   Enter '1' to train the model or '2' to generate signals: 1
   

3. Generating Trading Signals:

   • Make sure you've trained the model at least once.
   • Place the new data CSV in the data folder.
   • Run the script and choose the signal generation option:

   python trading_script.py

   When prompted, choose:

   Enter '1' to train the model or '2' to generate signals: 2
   

4. Visualizing Results:

   • After generating signals, the script will automatically display a plot of the cryptocurrency's close prices with Buy and Sell signals.

Contributing:

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License:

MIT

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