44 Pages Posted: 12 Nov 2013 Last revised: 11 Jun 2015
Date Written: June 18, 2014
This paper proposes a Bayesian estimation framework for a typical multi-factor model with time-varying risk exposures to macroeconomic risk factors and corresponding premia to price U.S. stocks and bonds. The model assumes that risk exposures and idiosyncratic volatility follow a break-point latent process, allowing for changes at any point in time but not restricting them to change at all points. An empirical application to 40 years of U.S. data and 23 portfolios shows that the approach yields sensible results compared to previous two-step methods based on naive recursive estimation schemes, as well as a set of alternative model restrictions. A variance decomposition test shows that although most of the predictable variation comes from the market risk premium, a number of additional macroeconomic risks, including real output and inflation shocks, are significantly priced in the cross-section. A Bayes factor analysis decisively favors the proposed change-point model.
Keywords: Structural breaks, Change-point model, Stochastic volatility, Multi-factor linear models, Asset pricing
JEL Classification: G11, C53
Suggested Citation: Suggested Citation
Bianchi, Daniele and Guidolin, Massimo and Ravazzolo, Francesco, Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section (June 18, 2014). Journal of Business & Economic Statistics, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2353011 or http://dx.doi.org/10.2139/ssrn.2353011