Firm Characteristics and Empirical Factor Models: A Model Mining Experiment
Tian, M. 2020. Firm characteristics and empirical factor models: A model mining experiment. Review of Financial Studies. Advance Access published November 9, 2020, 10.1093/rfs/hhaa126.
Posted: 22 Jan 2021
Date Written: November 9, 2020
Abstract
In a novel model mining experiment, we data mine hundreds of randomly constructed three-factor models and find that many outperform well-known models from the literature, including those with four and five factors. The results provide compelling evidence that the threshold of factor model success needs to be raised. Confidence intervals for model rankings, derived from a bootstrap simulation, offer new insights into the consistency of a model's pricing ability. Rankings for some well-known models are unusually volatile, which have wider confidence intervals than that of most of the random factor models.
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2182139
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2976764
Keywords: factor model, model mining, data mining, bootstrap simulation, firm characteristic, anomaly, cross-section
JEL Classification: G12, C15, C18
Suggested Citation: Suggested Citation
Mary H. Tian (Contact Author)
Board of Governors of the Federal Reserve System ( email )
20th Street and Constitution Avenue NW
Washington, DC 20551
United States
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