Portfolio Optimization

Analyze and optimize portfolios of assets

Portfolio optimization is a formal mathematical approach to making investment decisions across a collection of financial instruments or assets. The classical approach, known as modern portfolio theory (MPT), involves categorizing the investment universe based on risk (standard deviation) and return, and then choosing the mix of investments that achieve a desired risk versus return tradeoff.

You can perform asset allocation in MATLAB using Financial Toolbox. The toolbox provides a comprehensive suite of portfolio optimization and analysis tools for performing capital allocation, asset allocation, and risk assessment. These tools enable you to:

• Estimate asset return and total return moments from price or return data
• Compute portfolio-level statistics
• Perform constrained mean-variance optimization and analysis
• Examine the time evolution of efficient portfolio allocations
• Perform capital allocation
• Account for turnover and transaction costs

Examples and How To

• Using MATLAB to Optimize Portfolios with Financial Toolbox (Webinar)
• Building a Portfolio Analysis Product Application (Webinar)
• Mean-Variance Efficient Frontier (Example)
• Capital Asset Pricing Model with Missing Data (Example)
• Efficient Frontier (Example)
• Optimal Risky Portfolio (Example)
• Portfolio Constraint Specification (Example)
• Asset Allocation (Example)
• Using Quadratic Programming on Portfolio Optimization Problems (Example)
• CVaR Portfolio Optimization 5:33 (Video)

Software Reference

• Portfolio Analysis (Documentation)
• Portfolio Optimization Tools (Documentation)
• Portfolio Object (Function)
• Mean-Variance Efficient Frontier (Function)
• Rolling Efficient Frontier (Function)
• Portfolios on Constrained Efficient Frontier (Function)

See also: Portfolio Optimization and Analysis, Financial Toolbox, Optimization Toolbox, Global Optimization Toolbox, Black-Litterman Model