Do Risk Factors Eat Alphas?

Abstract

Although widespread, the practice in portfolio optimization of using different factor models for risk and alpha has potential pitfalls. Discrepancies between risk and alpha factors can create unintended exposures in optimized portfolios that may hamper performance. An analysis reveals the root of the problem. The optimizer emphasizes the portion of the manager's alpha that is not captured by the risk factors. Aligning the risk and alpha models may lead to better portfolios, even if doing so worsens the overall risk forecasts. In this article, four ways of remedying these problems are presented and compared using familiar optimization problems. The results are promising.

TOPICS: Volatility measures, statistical methods, factor-based models