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

70 Pages Posted: 10 Aug 2013 Last revised: 5 Jun 2017

See all articles by Nathaniel Light

Nathaniel Light

American University in Dubai

Denys Maslov

Moody's Analytics

Oleg Rytchkov

Temple University - Department of Finance

Date Written: January 21, 2016

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 twenty six 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.

Keywords: asset pricing, expected returns, anomaly, latent variables, PLS

JEL Classification: G12, C58

Suggested Citation

Light, Nathaniel and Maslov, Denys and Rytchkov, Oleg, Aggregation of Information About the Cross Section of Stock Returns: A Latent Variable Approach (January 21, 2016). Review of Financial Studies (RFS), Vol. 30, No. 4, pp. 1339-1381, 2017, Available at SSRN: https://ssrn.com/abstract=2307563 or http://dx.doi.org/10.2139/ssrn.2307563

Nathaniel Light

American University in Dubai ( email )

Dubai, UAE 28282
United Arab Emirates

Denys Maslov

Moody's Analytics ( email )

405 Howard St.
Suite 300
San Francisco, CA 94105
United States

Oleg Rytchkov (Contact Author)

Temple University - Department of Finance ( email )

Fox School of Business and Management
Philadelphia, PA 19122
United States

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