Bayesian Reconciliation of Return Predictability

48 Pages Posted: 11 Dec 2022

See all articles by Borys Koval

Borys Koval

Vienna Graduate School of Finance (VGSF)

Sylvia Fruhwirth-Schnatter

Johannes Kepler University - Department of Applied Statistics and Econometrics

Leopold Sögner

Institute for Advanced Studies (IHS); Vienna Graduate School of Finance (VGSF)

Date Written: November 29, 2022

Abstract

This article considers a stable vector autoregressive (VAR) model and investigates return predictability in a Bayesian context. The VAR system comprises asset returns and the dividend-price ratio as proposed in Cochrane (2008), and allows pinning down the question of return predictability to the value of one particular model parameter. We develop a new shrinkage type prior for this parameter and compare our Bayesian approach to ordinary least squares estimation and to the reduced-bias estimator proposed in Amihud and Hurvich (2004). A simulation study shows that the Bayesian approach dominates the reduced-bias estimator in terms of observed size (false positive) and power (false negative). We apply our methodology to annual CRSP value-weighted returns running, respectively, from 1926 to 2004 and from 1953 to 2021. For the first sample, the Bayesian approach supports the hypothesis of no return predictability, while for the second data set weak evidence for predictability is observed.

Keywords: VAR, Return predictability, Bayesian Control Function approach, Shrinkage Priors

JEL Classification: C11, C58, G12

Suggested Citation

Koval, Borys and Fruhwirth-Schnatter, Sylvia and Sögner, Leopold, Bayesian Reconciliation of Return Predictability (November 29, 2022). Available at SSRN: https://ssrn.com/abstract=4288973 or http://dx.doi.org/10.2139/ssrn.4288973

Borys Koval (Contact Author)

Vienna Graduate School of Finance (VGSF) ( email )

Welthandelsplatz 1
Vienna, 1020
Austria

Sylvia Fruhwirth-Schnatter

Johannes Kepler University - Department of Applied Statistics and Econometrics ( email )

Altenbergerstrasse 69
Linz
Austria

Leopold Sögner

Institute for Advanced Studies (IHS) ( email )

Josefstädter Straße 39
1080 Vienna
Austria

Vienna Graduate School of Finance (VGSF) ( email )

Welthandelsplatz 1
Vienna, 1020
Austria

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