文章基本信息

标题：Anticipating Long-Term Stock Market Volatility
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作者：Christian Conrad ; Karin Loch
期刊名称：Discussion Paper Series / Universität Heidelberg, Department of Economics
出版年度：2012
卷号：2012
出版社：Universität Heidelberg, Department of Economics
摘要：We investigate the relationship between long-term U.S. stock market risks andthe 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 datasetthe term spread, housing starts, corporate profits and the unemployment rate havethe highest predictive ability for stock market volatility. While the term spreadand housing starts are leading variables with respect to stock market volatility, forcorporate profits and the unemployment rate expectations data from the Surveyof Professional Forecasters regarding the future development are most informative.Our results suggest that macro variables carry information on stock market riskbeyond that contained in lagged realized volatilities, in particular when it comes tolong-term forecasting
关键词：Volatility Components; MIDAS; Survey Data; Macro Finance Link