Bayesian Reconciliation of Return Predictability

Koval Borys (), Frühwirth-Schnatter Sylvia () and Sögner Leopold ()
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Koval Borys: Vienna Graduate School of Finance, WU Vienna University of Economics and Business, 1020 Vienna, Austria
Frühwirth-Schnatter Sylvia: Department of Finance, Accounting and Statistics, WU Vienna University of Economics and Business, 1020 Vienna, Austria
Sögner Leopold: Department of Economics and Finance, Institute for Advanced Studies, 1080 Vienna, Austria

Studies in Nonlinear Dynamics & Econometrics, 2024, vol. 28, issue 2, 337-378

Abstract: This article considers a stable vector autoregressive (VAR) model and investigates return predictability in a Bayesian context. The bivariate VAR system comprises asset returns and a further prediction variable, such as the dividend-price ratio, 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. “Predictive Regressions: A Reduced-Bias Estimation Method.” Journal of Financial and Quantitative Analysis 39: 813–41). 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 a system comprising annual CRSP value-weighted returns running, respectively, from 1926 to 2004 and from 1953 to 2021, and the logarithmic dividend-price ratio. 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. Then, instead of the dividend-price ratio, some prediction variables proposed in Welch and Goyal (2008. “A Comprehensive Look at the Empirical Performance of Equity Premium Prediction.” Review of Financial Studies 21: 1455–508) are used. Also with these prediction variables, only weak evidence for return predictability is supported by Bayesian testing. These results are corroborated with an out-of-sample forecasting analysis.

Keywords: VAR; return predictability; Bayesian control function approach; shrinkage priors; Bayes Factor (search for similar items in EconPapers)
JEL-codes: C11 C58 G12 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1515/snde-2022-0110

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