On the Economic Sources of Stock Market Volatility
Robert F. Engle
New York University - Leonard N. Stern School of Business - Department of Economics; National Bureau of Economic Research (NBER); New York University (NYU) - Department of Finance
University of North Carolina (UNC) at Chapel Hill - Department of Economics; University of North Carolina (UNC) at Chapel Hill - Finance Area
Georgetown University - McDonough School of Business
August 31, 2008
AFA 2008 New Orleans Meetings Paper
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.
Number of Pages in PDF File: 54
Keywords: stock market volatility, macroeconomic variables, volatility decomposition, cross-section of returns
JEL Classification: G10, G12working papers series
Date posted: March 21, 2007 ; Last revised: September 18, 2012
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