Portfolio optimization is the scientific process of constructing an investment portfolio that maximizes expected returns for a given level of risk, or minimizes risk for a given level of expected returns. Rooted in Harry Markowitz Modern Portfolio Theory (MPT), optimization seeks to identify the Efficient Frontier—the set of portfolios offering the highest expected return at each risk level.
Core Optimization Methods
- Mean-Variance Optimization (MVO): Calculates optimal weights by analyzing each asset expected return, standard deviation, and pairwise correlations. The result is a mathematically optimal portfolio along the Efficient Frontier.
- Risk Parity: Allocates capital so each asset contributes equally to total portfolio risk. This approach has gained popularity since 2008 for its resilience during market crises.
- Maximum Diversification: Maximizes the diversification ratio (weighted average volatility / portfolio volatility) to achieve the most balanced risk distribution.
Practical Implementation
For retail investors, the simplest optimization is a two-asset approach: adjust stock/bond ratios based on age and risk tolerance. More sophisticated approaches use Monte Carlo simulation to account for uncertainty in return estimates and to generate probability distributions of portfolio outcomes.