Firm Characteristics and Empirical Factor Models: A Model-Mining Experiment

FRB International Finance Discussion Paper

58 Pages Posted: 29 Nov 2012 Last revised: 22 Jun 2017

See all articles by Leonid Kogan

Leonid Kogan

Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER)

Mary H. Tian

Board of Governors of the Federal Reserve System

Date Written: June 12, 2015

Abstract

''A three-factor model using momentum and cashflow-to-price factors explains 14 asset pricing anomalies.'' Our model-mining experiment provides a backdrop to evaluate such claims. We construct three-factor linear pricing models that match return spreads associated with as many as 14 out of 27 commonly used firm characteristics over the 1971-2011 sample. 71% and 48% of the factor models match a larger fraction of target return cross-sections than the CAPM or Fama-French three-factor model, respectively. The relative performance of factor models is highly sensitive to sample choice and factor construction methodology. Simulation analysis indicates that the empirical performance across the mined models provides virtually no evidence in support of the underlying risk-return relations.

Keywords: Anomalies, Factor Models, Data-mining, Firm Characteristic

JEL Classification: G12

Suggested Citation

Kogan, Leonid and Tian, Mary H., Firm Characteristics and Empirical Factor Models: A Model-Mining Experiment (June 12, 2015). FRB International Finance Discussion Paper. Available at SSRN: https://ssrn.com/abstract=2182139 or http://dx.doi.org/10.2139/ssrn.2182139

Leonid Kogan (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
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Cambridge, MA 02142
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617-253-2289 (Phone)
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HOME PAGE: http://web.mit.edu/lkogan2/www/

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Mary H. Tian

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

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