Python Based Investment Portfolio Optimization & Evaluation Tool

I am designing and boiling a custom portfolio evaluation and optimization tool to analyze and manage my Robinhood investments. This project grew out of my interest in applying quantitative finance, data visualization, and engineering principles to personal investing.

Objectives

  • Track and evaluate the performance of my portfolio in real-time

  • Measure risk and return metrics using modern portfolio theory (MPT)

  • Provide data-driven recommendations for optimal asset allocation

  • Offer clear, intuitive visualizations of portfolio health

Core Features

  • Portfolio Performance Dashboard: Displays historical and real-time returns, growth over time, and comparisons against benchmarks.

  • Risk Analysis: Calculates volatility, Sharpe ratio, drawdowns, and correlation between assets to show diversification strength.

  • Optimization Engine: Uses mean-variance optimization and efficient frontier modeling to suggest allocations that balance return and risk.

  • Scenario Testing: Allows for stress testing under market shifts (e.g., interest rate hikes, recessions, sector downturns).

  • Customization: Inputs constraints like risk tolerance, target return, or allocation caps to generate personalized strategies.

  • Visualization Suite: Includes efficient frontier plots, risk-return scatter charts, and allocation breakdowns for quick insights.

Technical Approach

  • Data Integration: Pulls Robinhood portfolio data via API and supplements with external financial market data sources.

  • Computation: Implements optimization models in Python (NumPy, pandas, SciPy) with visualization using Matplotlib/Plotly.

  • User Interface: Built with Streamlit, making the tool interactive and easy to use. Sliders, dropdowns, and real-time charts provide a smooth experience for testing portfolio strategies.

  • Architecture: Modular backend with room to expand into a larger web application if desired.

Why I’m Building This…

This project blends my engineering background with my passion for finance. By creating my own tool, I gain deeper insight into my portfolio’s behavior, test investment strategies with rigor, and sharpen my technical skills in data analysis, optimization, GUI development, and financial modeling.