Estimating Latent Asset-Pricing Factors

46 Pages Posted: 15 May 2018 Last revised: 11 Jun 2018

See all articles by Martin Lettau

Martin Lettau

University of California - Haas School of Business; Centre for Economic Policy Research (CEPR); National Bureau of Economic Research (NBER)

Markus Pelger

Stanford University - Management Science & Engineering

Multiple version iconThere are 3 versions of this paper

Date Written: May 2018

Abstract

We develop an estimator for latent factors in a large-dimensional panel of financial data that can explain expected excess returns. Statistical factor analysis based on Principal Component Analysis (PCA) has problems identifying factors with a small variance that are important for asset pricing. We generalize PCA with a penalty term accounting for the pricing error in expected returns. Our estimator searches for factors that can explain both the expected return and covariance structure. We derive the statistical properties of the new estimator and show that our estimator can find asset-pricing factors, which cannot be detected with PCA, even if a large amount of data is available. Applying the approach to portfolio data we find factors with Sharpe-ratios more than twice as large as those based on conventional PCA and with significantly smaller pricing errors.

Keywords: Anomalies, Cross Section of Returns, expected returns, high-dimensional data, Latent Factors, PCA, Weak Factors

JEL Classification: C14, C38, C52, C58, G12

Suggested Citation

Lettau, Martin and Pelger, Markus, Estimating Latent Asset-Pricing Factors (May 2018). CEPR Discussion Paper No. DP12926. Available at SSRN: https://ssrn.com/abstract=3178097

Martin Lettau (Contact Author)

University of California - Haas School of Business ( email )

Haas School of Business
545 Student Services Building
Berkeley, CA 94720
United States
5106436349 (Phone)

HOME PAGE: http://faculty.haas.berkeley.edu/lettau/

Centre for Economic Policy Research (CEPR)

London
United Kingdom

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Markus Pelger

Stanford University - Management Science & Engineering ( email )

473 Via Ortega
Stanford, CA 94305-9025
United States

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