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.

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.

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.