Overview
AI-Trader is an open-source project that explores using AI for trading strategy generation and evaluation. It provides a modular backtesting engine, data pipelines, simulation components, and visualization tools to monitor strategy performance. The project emphasizes reproducibility and engineering readiness so researchers and engineers can prototype and validate end-to-end trading workflows.
Key Features
- Full-featured backtesting and simulation engine supporting multi-timeframe and multi-asset evaluations.
- Modular strategy plugins allowing integration of ML/DL-based signal generators.
- Visualization dashboard and logging for observing and tuning strategy behavior.
Use Cases
- Research teams validating AI-driven trading strategies and robustness checks.
- Quant engineers conducting parameter sweeps and stress testing.
- Teaching and demos to illustrate AI decision-making in trading contexts.
Technical Highlights
- Python-first modular architecture for easy extension and custom strategy integration.
- Supports both offline backtesting and online simulated execution with data cleaning and feature pipelines.
- Designed for observability with dashboards and logs to speed up debugging and analysis.