Trading Bot Framework using MetaTrader5

This is a procedural trading bot framework in Python that leverages the MetaTrader5 library. It incorporates logging functionality and a backtesting module.

Key Features

• Establishes a connection to the MetaTrader5 platform
• Retrieves and processes market data
• Executes a simple Moving Average Crossover strategy
• Initiates trades based on generated signals
• Incorporates risk management for position sizing
• Offers a backtesting module to assess strategy performance
• Logs all activities and errors for monitoring and debugging purposes

Setup and Installation

1. Clone the Repository

   git clone https://github.com/yourusername/trading_bot.git
   cd trading_bot

2. Create and Activate a Virtual Environment

   Windows:

   python -m venv trading_env
   trading_env\Scripts\activate

   Unix or MacOS:

   python -m venv trading_env
   source trading_env/bin/activate

3. Install Required Packages

   pip install -r requirements.txt

4. Run the Trading Bot

   python main.py

File Descriptions

• connection_manager.py: Handles connections and disconnections from MetaTrader5.
• logger_setup.py: Configures the logging setup.
• data_handler.py: Manages the retrieval and processing of market data.
• strategy.py: Implements the trading strategy.
• trade_executor.py: Executes trades based on strategy signals.
• risk_manager.py: Manages risk and position sizing.
• backtesting.py: Facilitates backtesting of the trading strategy.
• main.py: The primary script to execute the trading bot.
• requirements.txt: Lists the required Python packages for the project.
• README.md: Provides instructions and information about the trading bot.

Important Notes

• Ensure MetaTrader5 is installed and properly configured on your machine.
• Adjust the main.py script as necessary to modify symbols, timeframes, and other parameters.
• Utilize a demo account for testing purposes before deploying on a live account.

Extending the Framework

Docker Environment: Create a separate Docker environment to implement and run the trading bot anywhere with ease.

Additional Strategies: Implement more strategies by adding new functions to strategy.py.

Risk Management Enhancements: Improve position sizing calculations and include features like trailing stops.

Scheduling: Use task schedulers or cron jobs to run the bot at specific intervals.

Database Integration: Store trade logs and performance data in a database for analysis.

Notification System: Add email or messaging notifications for important events.

Contact

• Author: Muhammad Noman Fareed
• Email: nomanfareed681@gmail.com
• LinkedIn: m-noman-fareed