Research

Published papers, preprints, and academic contributions.

Greek Vase Volume Analysis Using Mathematical Modeling

Siddhant Shah, Minfei Liang, Eugene Pinsky

MDPI Journal (Metrology)

Advanced interdisciplinary research combining mathematical modeling, statistical analysis, and Python programming to compute volumes of ancient Greek vases using geometric principles and modern computational methods. Achieved 4.91% mean relative error.

Mathematical Modeling Statistical Analysis Python Data Analytics Archaeological Research Computational Methods

Momentum-Based Trading Strategies in Crude Oil ETFs And Futures

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.

Research Momentum Strategies Crude Oil ETFs Futures

The Silver Lining of Daily Bitcoin Trading

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.

Cryptocurrency Bitcoin Silver Cross-Asset Trading Predictive Modeling

Estimating the Accuracy of a Bagged Ensemble

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.

Machine Learning Random Forests Ensemble Methods Probabilistic Modeling Computational Efficiency
DOI: 10.5121/mlaij.2025.12106