OPES

A research-focused open-source Python library offering cutting-edge quantitative portfolio optimization schemes, a walk-forward backtesting engine with customizable slippage models, comprehensive performance metrics and hand-built vectorized objectives.

GARCH-FX

A novel stochastic volatility forecasting framework using a Gamma-distributed GARCH(1,1) extension with regime-switching noise scaling. Benchmarked against Heston dynamics and submitted research on SSRN & MPRA.

EGARCH-JDM-MVO Pipeline

Portfolio optimization pipeline with custom C++ EGARCH(1,1) for volatility forecasting, Merton Jump Diffusion Monte Carlo for returns and forward-looking covariance construction. Built from scratch in C++ and Python.