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A Practical Guide to Volatility Forecasting through Calm and Storm

23 Pages Posted: 10 Nov 2009 Last revised: 15 Nov 2013

Christian T. Brownlees

Universitat Pompeu Fabra - Department of Economics and Business; Barcelona Graduate School of Economics (Barcelona GSE)

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)

Bryan T. Kelly

University of Chicago - Finance; National Bureau of Economic Research (NBER)

Date Written: August 1, 2011

Abstract

We present a volatility forecasting comparative study within the ARCH class of models. Our goal is to identify successful predictive models over multiple horizons and to investigate how predictive ability is influenced by choices for estimation window length, innovation distribution, and frequency of parameter re-estimation. Test assets include a range of domestic and international equity indices and exchange rates. We find that model rankings are insensitive to forecast horizon and suggestions for estimation best practices emerge. While our main sample spans 1990-2008, we take advantage of the near-record surge in volatility during the last half of 2008 to ask if forecasting models or best practices break down during periods of turmoil. Surprisingly, we find that volatility during the 2008 crisis was well approximated by predictions one-day ahead, and should have been within risk managers' 1% confidence intervals up to one month ahead.

Keywords: Volatility, ARCH, Forecasting, Forecast Evaluation

Suggested Citation

Brownlees, Christian T. and Engle, Robert F. and Kelly, Bryan T., A Practical Guide to Volatility Forecasting through Calm and Storm (August 1, 2011). Available at SSRN: https://ssrn.com/abstract=1502915 or http://dx.doi.org/10.2139/ssrn.1502915

Christian T. Brownlees (Contact Author)

Universitat Pompeu Fabra - Department of Economics and Business ( email )

Ramon Trias Fargas 25-27
Barcelona, 08005
Spain

HOME PAGE: http://www.econ.upf.edu/~cbrownlees/

Barcelona Graduate School of Economics (Barcelona GSE) ( email )

Ramon Trias Fargas 25-27
Barcelona, Catalonia 08014
Spain

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

Bryan T. Kelly

University of Chicago - Finance ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States
773-702-8359 (Phone)

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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