Title(题名):  Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and
Authors(作者):  Daniele Bianchi, Massimo Guidolin, and Francesco Ravazzolo
Source title(刊名):  Journal of Business &Economic Statistics:A Publication of the American Statistical Association
Volume, Issue, Issue date
(卷,期,年):
 April 2017,Vol35,Issue1
Pages(页码):  p110-129
ISSN:  0735-0015
Abstract(摘要):  This article 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. publicly traded assets. The model assumes that risk exposures and idiosyncratic volatility follow a break-point latent process, allowing for changes at any point on time but not restricting them to change at all points. The empirical application t0 40 years of U.S. data and 23 portfolios shows that the approach yields sensible results compared to previous two-step methods based on na?ve 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 massively favors the proposed change-point model. Supplementary materials for this article are available online.
Key words(关键词):  Asset pricing; Multi-factor linear models; Stochastic volatility; Structural breaks.
Where(馆藏地):  304外文报刊阅览室
Available online
(提交时间):
 2018/3/7 10:22:16
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