This repository features a professional implementation of a diverse range of trading strategies across multiple asset classes, translating complex mathematical theory into modular, production-ready Python frameworks.
This repository is currently under active development. New strategies, institutional-grade code modules, and research documentation are being added regularly.
This library is built with a production-first mindset, focusing on high-quality engineering and financial rigor:
- Adaptive Architecture: Instead of a one-size-fits-all template, each folder uses a custom file structure tailored to the specific needs of the asset class (e.g., specialized Greeks modules for Options or feature engineering pipelines for ML).
- Institutional Rigor: Every implementation accounts for real-world constraints, including vectorized backtesting, slippage modeling, transaction cost analysis, and advanced position sizing.
- The Alpha Edge: Each strategy includes at least one advanced optimization such as Kalman Filters for noise reduction, Bayesian parameter tuning, or exotic risk-parity models to provide a competitive edge.
- Research-Backed: Every module is accompanied by documentation explaining the market anomaly being exploited, the mathematical core of the logic, and the specific market regimes where the strategy excels or fails.
The library spans the global financial spectrum, including:
- Equities: Momentum, Value, and Low-Volatility anomalies.
- Derivatives: Complex Option Greeks, Volatility Arbitrage, and Exotic Spreads.
- Fixed Income: Yield Curve modeling and CDS Basis Arbitrage.
- Alternative Assets: Commodities, FX Triangular Arbitrage, and Global Macro Hedges.
- AI/ML: Neural Networks, KNN, and Bayes-based predictive modeling.
For Educational and Research Purposes Only.
- Not Financial Advice: The code and documentation provided in this repository are for pedagogical and research purposes. Nothing here constitutes investment, legal, or tax advice. Trading involves significant risk of loss.
- No Warranties: All software and information are provided "as-is" without any warranties of accuracy, completeness, or profitability. Past performance (backtests) is not indicative of future results.
- Execution Risk: The implementations include simulated slippage and transaction costs, but real-market execution may vary significantly. Do not deploy this code in a live environment without independent testing and rigorous risk assessment.
- License: This project is an open-source contribution to the quant community. Please refer to the LICENSE file for details on usage and attribution.