MT5-PY-AI-Tbot/flow.md

Project Flow

This document outlines the workflow of the AI-Enhanced MQL5 Trading Bot project.

1. Data Export:

   • The process starts with the Export_EURUSD_History.mq5 script, which is an MQL5 script that runs on the MetaTrader 5 terminal.
   • This script exports historical price data for the EUR/USD pair to a CSV file named raw_price_data.csv.

2. Model Training:

   • The raw_price_data.csv file is then used by the Python scripts to train the machine learning models.
   • The create_benchmark_model.py script trains a logistic regression model and exports it to benchmark_logistic_model.onnx.
   • The Model_Development.py script trains a neural network model using hyperparameter tuning and exports it to trading_neural_network_model.onnx.

3. Trading:

   • The exported ONNX models are used by the MQL5 Expert Advisors (EAs) to make trading decisions.
   • The Benchmark_Model_EA.mq5 EA uses the benchmark_logistic_model.onnx model.
   • The Neural_Network_Trader_EA.mq5 EA uses the trading_neural_network_model.onnx model.
   • The EAs run on the MetaTrader 5 terminal, and on each new bar, they get the latest price data, feed it to the ONNX model, and execute a trade based on the model's prediction.