Production multi-agent trading platform with rigorous walk-forward validation. TSMOM momentum (1.097 Sharpe) + GEX regime filtering. Interactive CLI, autonomous trade lifecycle, daily scheduler. Alpaca integration. Built on Microsoft AutoGen. Research-driven approach with statistical validation. Educational - not financial advice.

Rigorous ML framework for alpha generation research. Demonstrates that apparent alpha from public market data is primarily overfitting. Key finding: IC flips from +0.036 to -0.084 when regularization is increased 100x.

Time series forecasting project predicting PM2.5 air quality using Linear Regression, AR, and ARMA models — from MongoDB data wrangling to model evaluation and visualization.

systematic trading strategies developed and validated using walk-forward analysis. The code is modular and structured for production backtesting.

Time series and machine learning modeling to analyze and predict Seattle’s weather patterns using climate variables like precipitation, temperature, and wind.

Time series forecasting of telecom revenue using Auto-ARIMA and walk-forward validation.