Portafolio Optimizer App

In this video I walk through a Portfolio Optimizer web app I built for my AI for Finance course at Purdue University. The app takes 5–15 real stock tickers, pulls historical price data from Yahoo Finance, and uses mean-variance optimization to find the best portfolio allocation. What's covered: Switching between Max Sharpe Ratio, Minimum Variance, and Target Return optimization Adjusting constraints like max/min weight per stock and the risk-free rate How constraints change the optimal portfolio and the Sharpe ratio Reading the efficient frontier and understanding the risk-return tradeoff Correlation heatmap and side-by-side strategy comparison Built with Python, Streamlit, yfinance, SciPy, and Plotly. AI-assisted development using Claude. #portfoliooptimization #efficientfrontier #sharperatio #meanvariance #optimization #python #streamlit #finance #investing #modern-portfolio-theory