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Anticipating Long-Term Stock Market Volatility

Conrad, Christian and Loch, Karin

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Abstract

We investigate the relationship between long-term U.S. stock market risks and the macroeconomic environment using a two component GARCH-MIDAS model. Our results provide strong evidence in favor of counter-cyclical behavior of long-term stock market volatility. Among the various macro variables in our dataset the term spread, housing starts, corporate profits and the unemployment rate have the highest predictive ability for stock market volatility . While the term spread and housing starts are leading variables with respect to stock market volatility, for corporate profits and the unemployment rate expectations data from the Survey of Professional Forecasters regarding the future development are most informative. Our results suggest that macro variables carry information on stock market risk beyond that contained in lagged realized volatilities, in particular when it comes to long-term forecasting.

Item Type: Working paper
Date Deposited: 05 Oct 2012 15:38
Date: 2012
Faculties / Institutes: The Faculty of Economics and Social Studies > Alfred-Weber-Institut for Economics
Subjects: 330 Economics
Uncontrolled Keywords: Volatility Components , MIDAS , Survey Data , Macro Finance Link
Schriftenreihe ID: Discussion Paper Series / University of Heidelberg, Department of Economics
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