Deja Vol: Predictive Regressions for Aggregate Stock Market Volatility Using Macroeconomic Variables

41 Pages Posted: 23 Aug 2005 Last revised: 18 Dec 2011

See all articles by Bradley S. Paye

Bradley S. Paye

Virginia Polytechnic Institute & State University - Department of Finance, Insurance, and Business Law

Date Written: December 15, 2011

Abstract

Aggregate stock return volatility is both persistent and countercyclical. This paper tests whether it is possible to improve volatility forecasts at monthly and quarterly horizons by conditioning on additional macroeconomic variables. I find that several variables related to macroeconomic uncertainty, time-varying expected stock returns, and credit conditions Granger cause volatility. It is more difficult to find evidence that forecasts exploiting macroeconomic variables outperform a univariate benchmark out-of-sample. The most successful approaches involve simple combinations of individual forecasts. Predictive power associated with macroeconomic variables appears to concentrate around the onset of recessions.

Keywords: Conditional Volatility, Realized Volatility, Granger Causality, Forecast Evaluation, Forecast Combination

JEL Classification: G12, C22

Suggested Citation

Paye, Bradley S., Deja Vol: Predictive Regressions for Aggregate Stock Market Volatility Using Macroeconomic Variables (December 15, 2011). Available at SSRN: https://ssrn.com/abstract=783986 or http://dx.doi.org/10.2139/ssrn.783986

Bradley S. Paye (Contact Author)

Virginia Polytechnic Institute & State University - Department of Finance, Insurance, and Business Law ( email )

1016 Pamplin Hall (0221)
Blacksburg, VA 24060-0221
United States

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