Capital Preservation Allocation Using Linear Programming

Overview

This project demonstrates the use of Linear Programming (LP) to optimize the allocation of $250,000 across 25 ETFs, prioritizing capital preservation and achieving a minimum annual return of 2%. The model minimizes risk while adhering to diversification constraints.

Key Results

• Total Investment: $249,792
• Annual Return: 6.66% (exceeds 2% threshold)
• Top Allocations:
  • GLD (Gold): $49,984
  • BND (Bonds): $49,982
  • VXUS (International Stocks): $49,981

Features

• Risk Minimization: Allocates funds to stable, low-risk ETFs.
• Constraints:
  • Max 20% allocation per ETF.
  • No short selling.
• Diversified Portfolio: Balances bonds, gold, and dividend-paying stocks.

Why It Matters

This project showcases:

• Real-world application of algorithms.
• Financial data analysis and portfolio optimization.
• Expertise in translating mathematical models into actionable investment strategies.

Check out the implementation in the accompanying Jupyter Notebook.