A robust, regime-adaptive QQQ trading strategy utilizing ensemble machine learning and options market microstructure signals (GEX, VRP, Skew).

A Python trading bot that combines momentum, mean reversion, and volatility signals to run a long-short strategy. Includes a custom walk-forward optimizer to automatically tune the model as market conditions change.

End-to-end algorithmic trading system using PyTorch LSTM. Features a custom Cross-Sectional Alpha ranking engine, dynamic portfolio compounding, and event-driven backtesting (+483% return vs SPY).

A quantitative framework modeling recursive interactions between technology, capital, and delayed information absorption.

An open-source framework for autonomous digital entities, focused on decentralized threat & alpha intelligence.

A comprehensive, production-grade implementation of quantitative trading strategies across 18 asset classes. Features modular Python architecture, institutional risk management, and deep-dive research papers for every strategy.