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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.
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