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Reevaluating Factor Models: Feature Extraction of the Factor Zoo
Abstract
Since the introduction of CAPM in the 1960s, the asset pricing literature has documented hundreds of characteristics that capture the cross-sectional variation in stock returns. Traditionally, multifactor models seek a multidimensional representation of common risks; this approach entails selecting a small number of representative characteristics from a set of candidate characteristics that, together, explain most of the cross-sectional variation in stock returns. Characteristics-based long-short portfolios are partially loaded on the true underlying risk factors and are at best noisy proxies for true latent factors. However, the expansive list of potential characteristics, along with developments in the field of dimensionality reduction, offers us an opportunity to seek better approximations of the unobservable latent risk factors. A recent stream of literature has investigated how to appropriately extract relevant features from the “factor zoo” while incorporating information from the expansive list of factors. This chapter aims to summarize this novel paradigm in factor modeling.
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