Monotonic Effects of Characteristics on Returns

33 Pages Posted: 1 Aug 2018 Last revised: 8 Apr 2020

See all articles by Jared Fisher

Jared Fisher

University of California, Berkeley

David Puelz

University of Chicago - Booth School of Business

Carlos M. Carvalho

University of Texas at Austin - Red McCombs School of Business

Date Written: December 14, 2018

Abstract

This paper considers the problem of modeling a firm’s expected return as a nonlinear function of its observable characteristics. We investigate whether theoretically-motivated monotonicity constraints on characteristics and nonstationarity of the conditional expectation function provide statistical and economic benefit. We present an interpretable model that has similar out-of-sample performance to black-box machine learning methods. With this model, the data provide support for monotonicity and time variability of the conditional expectation function. Additionally, we develop an approach for characteristic selection using loss functions to summarize the posterior distribution. Standard unexplained volume, short-term reversal, size, and variants of momentum are found to be significant characteristics, and there is evidence this set changes over time.

Keywords: Cross Section of Returns, posterior summarization, Bayesian modeling

Suggested Citation

Fisher, Jared and Puelz, David and Carvalho, Carlos M., Monotonic Effects of Characteristics on Returns (December 14, 2018). Available at SSRN: https://ssrn.com/abstract=3212934 or http://dx.doi.org/10.2139/ssrn.3212934

Jared Fisher (Contact Author)

University of California, Berkeley ( email )

United States

David Puelz

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

Carlos M. Carvalho

University of Texas at Austin - Red McCombs School of Business ( email )

Austin, TX 78712
United States

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