Definition
MVO, the quantitative engine of MPT, uses expected returns, volatilities, and correlations to compute optimal portfolio weights. While mathematically elegant, MVO is highly sensitive to input estimates—small changes in expected returns can drastically shift optimal weights. Practical applications use constraints, shrinkage estimators, and robust optimization to address this sensitivity.
lightbulb Example
Given three assets with expected returns (8%, 12%, 6%), volatilities (12%, 20%, 8%), and correlations, MVO finds the optimal weights: 40%/35%/25% for a target return of 9% with minimum 11% volatility.
verified_user Key Points
- Quantitative engine of Modern Portfolio Theory
- Highly sensitive to input estimates
- Requires constraints to produce practical allocations
- Robust methods address estimation error