05
AI Trading System
An experimental algorithmic trading system combining market data, machine learning, backtesting, and MT5 integration.
Overview
A personal engineering experiment exploring algorithmic trading — not a commercial product claim. Combines Python pipelines, strategy backtesting, and broker integration for learning and iteration.
Problem
Understanding how automated strategies behave across market conditions requires reproducible backtests, clean data pipelines, and safe integration with live trading environments.
Approach
Built incrementally: data ingestion first, then strategy modules, then backtesting framework, then cautious live integration. Every layer is inspectable and logged.
Architecture
Python services for market data ingestion and feature engineering, modular strategy definitions, backtesting engine with performance metrics, and MT5/Exness bridge for execution experiments.
Result
A functional research environment for testing strategies and studying market behavior. Presented as an engineering experiment — outcomes vary and past performance is not indicative of future results.
Technology
Python · Pandas · scikit-learn · Backtesting · MT5 · Exness API