Asset Allocation for Robust Portfolios

Abstract

A new risk/return optimization model is described that overcomes much of the instability inherent in traditional mean-variance optimizers with a minimal sacrifice of efficiency. The robust frontier model identifies portfolios that are close to the efficient frontier, less likely to produce extreme results, and—most importantly—are much more stable to changes in input assumptions. Practitioners using this model can approach the task of asset allocation with confidence that small errors in forecasts will not be the primary driver of asset allocation outputs, and that if the model is used over time it will not produce huge swings in allocations with consequent high transaction costs.