Monotonic Effects of Characteristics on Returns
33 Pages Posted: 1 Aug 2018 Last revised: 8 Apr 2020
Date Written: December 14, 2018
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: Suggested Citation