Oct 2024 - Present
Skills: Python, R, SQL, Pandas, NumPy, scikit-learn, PyTorch, Backtesting, Portfolio Optimization
Siddhant Shah, Eugene Pinsky
Technical Analysis of STOCKS & COMMODITIES
Research on momentum-based trading strategies in crude oil ETFs and futures, developing long-short models yielding up to 19.9% annualized returns over an 18-year testing period.
Siddhant Shah, Eugene Pinsky
Technical Analysis of STOCKS & COMMODITIES
Strategy leveraging overnight silver returns to predict Bitcoin price movements, exhibiting lower drawdowns in a 10-year backtest with 68.65% annualized returns.
Siddhant Shah, Eugene Pinsky
Machine Learning and Applications: An International Journal (MLAIJ)
Probabilistic framework to reduce computational overhead in model fine-tuning, using various distributions to estimate Random Forest performance with less than 3% relative error.
High-performance financial analytics system comparison achieving 50-300x performance improvements with KDB+/q over traditional systems for time-series operations. Microsecond-level query response and 5-8x memory compression.
End-to-end machine learning framework for F1 lap time prediction using real-time telemetry data, achieving 94.8% R² through advanced feature engineering with track curvature, elevation profiles, and driver performance metrics.
Introduction to working as a Business Analyst with MS Excel & Power BI
This is a demo for AI model development.
A collection of apps that help me get the most usability out of my MacBook.