Abstract
Application of a multifactor alpha model across a diverse range of stocks is a popular way to forecast security expected returns, but it is a one-size-fits-all approach. An alternative alpha-modeling approach represents a parsimonious way to model securities individually in order to capture idiosyncratic return behavior in different security contexts. The investment objective is information ratio maximization through optimal alpha factor weights. This technique demonstrates the importance of factor categories such as cheapness, quality, and sentiment that vary significantly across various security contexts. Practitioners can see that the approach improves the ex post information ratio over a one-size-fits-all approach.
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