On the Economic Sources of Stock Market Volatility

54 Pages Posted: 21 Mar 2007 Last revised: 18 Sep 2012

Robert F. Engle

New York University - Leonard N. Stern School of Business - Department of Economics; New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER)

Eric Ghysels

University of North Carolina Kenan-Flagler Business School; University of North Carolina (UNC) at Chapel Hill - Department of Economics

Bumjean Sohn

Korea University Business School

Multiple version iconThere are 2 versions of this paper

Date Written: August 31, 2008

Abstract

We revisit the relation between stock market volatility and macroeconomic activity using a new class of component models that distinguish short run from secular movements. We combine insights from Engle and Rangel (2007) and the recent work on mixed data sampling (MIDAS), as in e.g. Ghysels, Santa-Clara, and Valkanov (2005). The new class of models is called GARCH-MIDAS, since it uses a mean reverting unit daily GARCH process, similar to Engle and Rangel (2007), and a MIDAS polynomial which applies to monthly, quarterly, or bi-annual macroeconomic or financial variables. We study long historical data series of aggregate stock market volatility, starting in the 19th century, as in Schwert (1989). We formulate models with the long term component driven by inflation and industrial production growth that are at par in terms of out-of-sample prediction for horizons of one quarter and out-perform more traditional time series volatility models at longer horizons. Hence, imputing economic fundamentals into volatility models pays off in terms of long horizon forecasting. We also find that at a daily level, inflation and industrial production growth, account for between 10 % and 35 % of one-day ahead volatility prediction. Hence, macroeconomic fundamentals play a significant role even at short horizons. Unfortunately, all the models - purely time series ones as well as those driven by economic variables - feature structural breaks over the entire sample spanning roughly a century and a half of daily data. Consequently, our analysis also focuses on subsamples - pre-WWI, the Great Depression era, and post-WWII (also split to examine the so called Great Moderation). Our main findings remain valid across subsamples.

Keywords: stock market volatility, macroeconomic variables, volatility decomposition, cross-section of returns

JEL Classification: G10, G12

Suggested Citation

Engle, Robert F. and Ghysels, Eric and Sohn, Bumjean, On the Economic Sources of Stock Market Volatility (August 31, 2008). AFA 2008 New Orleans Meetings Paper. Available at SSRN: https://ssrn.com/abstract=971310 or http://dx.doi.org/10.2139/ssrn.971310

Robert F. Engle

New York University - Leonard N. Stern School of Business - Department of Economics ( email )

269 Mercer Street
New York, NY 10003
United States

New York University (NYU) - Department of Finance

Stern School of Business
44 West 4th Street
New York, NY 10012-1126
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Eric Ghysels

University of North Carolina Kenan-Flagler Business School ( email )

Kenan-Flagler Business School
Chapel Hill, NC 27599-3490
United States

University of North Carolina (UNC) at Chapel Hill - Department of Economics ( email )

Gardner Hall, CB 3305
Chapel Hill, NC 27599
United States
919-966-5325 (Phone)
919-966-4986 (Fax)

HOME PAGE: http://www.unc.edu/~eghysels/

Bumjean Sohn (Contact Author)

Korea University Business School ( email )

Seoul, 136-701

HOME PAGE: http://biz.korea.ac.kr/professor/sohnb

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