Stocks Portfolio Optimizer

Check out my live deployed project:
📊 Stocks Portfolio Optimizer

Project Overview

The Stocks Portfolio Optimizer is an interactive web application that helps users create optimized investment portfolios based on Modern Portfolio Theory. This tool enables investors to select stocks, set investment constraints, and visualize the efficient frontier to identify optimal asset allocations that maximize returns while minimizing risk.

Technologies Used

  • Python: Core programming language
  • Streamlit: Interactive web app framework
  • Financial Analysis: Historical stock data analysis and processing
  • Optimization Algorithms: Portfolio optimization using mathematical models
  • Data Visualization: Interactive charts and efficient frontier visualization
  • Render: Cloud hosting platform for the application

Key Features

  1. Stock Selection: Choose from a curated list of popular stocks or input custom tickers
  2. Portfolio Optimization: Find the optimal allocation of assets using Modern Portfolio Theory
  3. Efficient Frontier Visualization: Interactive chart showing risk-return tradeoffs
  4. Risk Analysis: Detailed breakdown of portfolio risk metrics
  5. Investment Constraints: Set minimum and maximum allocation constraints
  6. Performance Backtesting: Evaluate historical performance of optimized portfolios

Modern Portfolio Theory

This project implements Harry Markowitz’s Nobel Prize-winning Modern Portfolio Theory, which demonstrates that an optimized combination of assets can provide better risk-adjusted returns than individual assets. The application calculates expected returns, covariance matrices, and uses optimization algorithms to find the ideal portfolio weights.

Try It Yourself

Visit the Stocks Portfolio Optimizer to create your own optimized investment portfolio. Use the interactive interface to explore different combinations of stocks and see how changing constraints affects the optimal allocation.

Last updated: April 15, 2025