Anticipating Long-Term Stock Market Volatility
Journal of Applied Econometrics, Forthcoming
35 Pages Posted: 2 Oct 2012 Last revised: 30 Apr 2014
Date Written: April 23, 2014
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 show that macroeconomic variables are important determinants of the secular component of 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 long-term stock market volatility. While the term spread and housing starts are leading variables with respect to stock market volatility, for industrial production and the unemployment rate expectations data from the Survey of Professional Forecasters regarding the future development are most informative.
Keywords: Volatility Components, GARCH-MIDAS, Survey Data, Macro Finance Link
JEL Classification: C53, C58, E32, G12
Suggested Citation: Suggested Citation