Semi-analytical dynamic mean-variance allocation and terminal-wealth risk under regime-switching jump-diffusions
Goldfarb/Idnani dual quadratic programming solver in pure NumPy and SciPy. A reimplementation of quadprog/quadprog with no compiler required.
Mean-Variance Optimization using DL (pytorch)
Black-Litterman portfolio construction on the EURO STOXX 50 top 15: reverse-optimised equilibrium, Idzorek view-confidence, Theil posterior, max-Sharpe / min-variance / efficient frontier, Streamlit dashboard.
Institutional-style market risk pipeline for a multi-asset $1M portfolio. Computes VaR and CVaR via three methods (Historical Simulation, Parametric, Monte Carlo), validates models with Kupiec and Christoffersen backtests, and stress tests against GFC, COVID, and 2022 rate shock scenarios.
Convex portfolio optimizer: mean-variance / min-variance / max-Sharpe / risk-parity / max-diversification with weight caps, sector & exposure neutrality and turnover limits. Research/education only, not investment advice.
Factor-structured mean-variance portfolio optimization for Rust and Python
FastAPI service for Markowitz mean-variance portfolio optimization — efficient frontier + max-Sharpe allocation via SciPy SLSQP
Adaptive portfolio optimization using Kalman Filter estimation of time-varying expected returns — working paper with backtests, regime analysis, and statistical testing
From-scratch mean-variance portfolio optimization toolkit reproducing canonical literature results.
Full-stack quantum portfolio optimizer using QAOA to solve asset allocation. React frontend, FastAPI backend, real-time stock data via yfinance.
Mean-variance optimal delta-hedging of short strangles on Bitcoin futures options (HKUST IEDA3330)
Mean-variance portfolio optimization model - Devin Bulna
평균-분산 최적 비중과 월별 리밸런싱 백테스트 | Mean-variance allocation and rebalancing backtest
Interactive S&P 500 portfolio allocation app — Markowitz framework, CVXPY optimization, Ledoit-Wolf covariance, Streamlit UI
Constrained static mean-variance optimization, covariance repair, and sensitivity analysis in Python.
Python library for mean-variance portfolio optimization — Black-Litterman returns, Ledoit-Wolf covariance, efficient frontier, risk parity, CVaR minimization, and walk-forward backtesting with transaction costs.
Mean-variance portfolio optimization and factor model performance evaluation across mutual funds, smart beta ETFs, and hedge fund indices
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