Mean-Variance Optimization with ESG score constraint

Machine Learning portfolio optimization : Ridge, LogisticRegressions,LightGBM, XGBoost , RSI clustering, Sharpe maximization. Python/scikit-learn/PyPortfolioOpt

Selecting and optimizing portfolios involving FTSE 100 top 10 stocks. Comparison of each strategy performance over time with rolling statistics and tail risk metrics.

Aqui está parte do meu trabalho de conclusão de curso, onde faço a otimização de uma carteira de investimento usando a Teoria do Portfólio de Markwitz e a linguagem Python.

AI-driven bond portfolio optimizer using the Black-Litterman model to blend market equilibrium with subjective views

making professional portfolio management methods accessible through point and click. methods such as mean var opt and portfolio rebalancing is available. try the app from the link

Efficient Frontier and Tangency Portfolio modeling using Python, Markowitz Theory, and PyPortfolioOpt with domestic and global diversification.

ML-driven portfolio optimization comparing HRP clustering vs. Max Sharpe (MVO) for robust asset allocation.

Interactive Modern Portfolio Theory tool with Streamlit UI. Optimizes US and BIST stock portfolios using Markowitz mean-variance analysis.

Streamlit app forked for debugging purposes

Long-only ETF portfolio optimization (PyPortfolioOpt) with walk-forward backtesting, monthly rebalancing, transaction costs and a min-volatility fallback — benchmarked vs SPY

This project fetches historical OHLCV data for a universe of large, liquid stocks (z.B., MSFT, AAPL) and consolidates them into a tidy dataset suitable for downstream analytics, risk monitoring, and corporate‑action–aware time‑series analysis.

Automated interaction and data extraction tool for Jackson National Life Insurance website

Open-source portfolio optimization platform (Markowitz & Black-Litterman) with stock analysis, built on Streamlit + PyPortfolioOpt. Educational.