A Risk-Oriented Model for Factor Timing Decisions

Abstract

Alpha factors are built to perform well over time, on average. There are instances when they do not, and knowing these instances ex ante can be a significant source of added value for investors. The authors argue that factor failure is a function of its broad risk, and propose appropriate variables to measure it. They adopt a nonparametric model that predicts instances of likely factor failure, based on these variables, demonstrating that an implementable dynamic strategy based on our analysis generates a reward-to-risk ratio approximately four times that of a static approach, and about one and a half times that of an alternative dynamic approach based on momentum.