Understanding Industry Betas
Tilburg University - Department of Finance
Juan M. Londono
Federal Reserve Board of Governors
December 14, 2012
This paper models and explains the dynamics of market betas for 30 US industry portfolios between 1970 and 2009. We use DCC-MIDAS and kernel regression techniques as alternatives to the standard ex-post measures. We find betas to exhibit substantial persistence, time variation, ranking variability, and heterogeneity in their business cycle exposure. While we find only a limited amount of structural breaks in the betas of individual industries, we do identify a common structural break in March 1998. We propose two practical applications to understand the economic significance of these results. We find the cross-sectional dispersion in industry betas to be countercyclical and negatively related to future market returns. We also find DCC-MIDAS betas to outperform other beta measures in terms of limiting the downside risk and ex-post market exposure of a market-neutral minimum-variance strategy.
Number of Pages in PDF File: 45
Keywords: industry betas, component models, kernel, DCC-MIDAS, dispersion in betas, stock return predictability, minimum variance strategies
JEL Classification: C33, E32, G12
Date posted: February 22, 2013
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