Open Access
December 2020 Monotonic effects of characteristics on returns
Jared D. Fisher, David W. Puelz, Carlos M. Carvalho
Ann. Appl. Stat. 14(4): 1622-1650 (December 2020). DOI: 10.1214/20-AOAS1351


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.


Download Citation

Jared D. Fisher. David W. Puelz. Carlos M. Carvalho. "Monotonic effects of characteristics on returns." Ann. Appl. Stat. 14 (4) 1622 - 1650, December 2020.


Received: 1 June 2019; Revised: 1 March 2020; Published: December 2020
First available in Project Euclid: 19 December 2020

MathSciNet: MR4194241
Digital Object Identifier: 10.1214/20-AOAS1351

Keywords: Bayesian modeling , Cross-section of returns , posterior summarization

Rights: Copyright © 2020 Institute of Mathematical Statistics

Vol.14 • No. 4 • December 2020
Back to Top