Aggregation of Information About the Cross Section of Stock Returns: A Latent Variable Approach

Authors

Nathaniel Light, St. John Fisher UniversityFollow
Denys Maslov, Moody's Analytics
Oleg Rytchkov, Temple University

Document Type

Article

Publication Date

2-6-2017

Abstract

We propose a new approach for estimating expected returns on individual stocks from a large number of firm characteristics. We treat expected returns as latent variables and apply the partial least squares (PLS) estimator that filters them out from the characteristics under an assumption that the characteristics are linked to expected returns through one or few common latent factors. The estimates of expected returns constructed by our approach from 26 firm characteristics generate a wide cross-sectional dispersion of realized returns and outperform estimates obtained by alternative techniques. Our results also provide evidence of commonality in asset pricing anomalies.

DOI

https://doi.org/10.1093/rfs/hhw102

Publication Information

Light, Nathaniel; Maslov, Denys; and Rytchkov, Oleg (2017). "Aggregation of Information About the Cross Section of Stock Returns: A Latent Variable Approach." The Review of Financial Studies 30.4, 1339-1381.

Please note that the Publication Information provides general citation information and may not be appropriate for your discipline. To receive help in creating a citation based on your discipline, please visit http://libguides.sjfc.edu/citations.