Portfolio optimization with deep learning.
Investment portfolio and stocks analyzing tools for Python with free historical data
A JavaScript library to allocate and optimize financial portfolios.
Markowitz portfolio optimization on synthetic and real stocks
Markowitzify will implement a variety of portfolio and stock/cryptocurrency analysis methods to optimize portfolios or trading strategies. The two primary classes are "portfolio" and "stonks."
Markowitz portfolio construction on CVXPY — DPP-compliant builders that solve long sequences of related problems without recompiling as assets and factors come and go
Python toolkit for Markowitz portfolio optimization. Efficient frontier, capital allocation line, and an interactive FastAPI web app.
critical line algorithm for efficient frontier
Backtesting of different trading strategies by applying different Modern Portfolio Theory (MPT) approaches on long-only ETFs portfolios in Python.
Portfolio Optimization on a Quantum computer.
Interactive Streamlit dashboard for market risk analysis, Markowitz portfolio optimization, and financial planning.
Reproducibility repository for 'Beyond De Prado and Cotton: Hierarchical and Iterative Methods for General Mean-Variance Portfolios' (Wuebben): Python code and result artifacts for HRP-μ, HRP-Σμ, and the CRISP iterative shrinkage solver.
This Python script performs portfolio optimization based on different optimization criteria: 'sharpe', 'cvar', 'sortino', and 'variance'. The script uses historical stock price data downloaded from Yahoo Finance.
Open-source quantitative finance research engine — Black-Litterman, Ledoit-Wolf shrinkage, Hierarchical Risk Parity, leakage-free CPCV backtesting. Independently reproduces the DeMiguel-Garlappi-Uppal "1/N puzzle": no tested optimization method reliably beats naive equal-weighting once estimation error is properly controlled for.
Inversion of a real matrix and the solution of a set of linear equations using Crout's method
Quantitative portfolio risk analyzer — VaR, Sharpe, Markowitz optimization, Monte Carlo simulation — Streamlit dashboard
Comparison of Return Forecasting Methods for Markowitz Portfolio Optimization: Historical Mean, AutoARIMA, PatchTST Transformer
Educator turned Financial Engineer & Builder | Python, Quantitative Finance, & Educational Tech | Building data-driven solutions and ML models.
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