Range-Based Estimation of Stochastic Volatility Models or Exchange Rate Dynamics are More Interesting than You Think

Wharton FIC Working Paper No. 00-28

50 Pages Posted: 20 Nov 2000

See all articles by Sassan Alizadeh

Sassan Alizadeh

University of Pennsylvania - Department of Economics; Bear, Stearns & Co., Inc.

Michael W. Brandt

Duke University - Fuqua School of Business; National Bureau of Economic Research (NBER)

Francis X. Diebold

University of Pennsylvania - Department of Economics; National Bureau of Economic Research (NBER)

Date Written: December 1999

Abstract

We propose using the price range, a recently-neglected volatility proxy with a long histoy in finance, in the estimation of stochastic volatility models. We show both theoretically and empirically that the log range is approximately Gaussian, in sharp contrast to popular volatility proxies, such as log absolute or squared returns. Hence Gaussian quasi-maximum likelihood estimation based on the range is not only simple, but also highly efficient. We illustrate and enrich our theoretical results with a Monte Carlo study and a substantive empirical application to daily exchange rate volatility. Our empirical work produces sharp conclusions. In particular, the evidence points strongly to the inadequacy of one-factor volatility models, favoring instead two-factor models with one highly persistent factor and one quickly mean reverting factor.

JEL Classification: C12, C22

Suggested Citation

Alizadeh, Sassan and Brandt, Michael W. and Diebold, Francis X., Range-Based Estimation of Stochastic Volatility Models or Exchange Rate Dynamics are More Interesting than You Think (December 1999). Wharton FIC Working Paper No. 00-28, Available at SSRN: https://ssrn.com/abstract=231165 or http://dx.doi.org/10.2139/ssrn.231165

Sassan Alizadeh

University of Pennsylvania - Department of Economics ( email )

Ronald O. Perelman Center for Political Science
133 South 36th Street
Philadelphia, PA 19104-6297
United States
(212) 289-8892 (Phone)

Bear, Stearns & Co., Inc. ( email )

245 Park Avenue
New York, NY 10167
United States

Michael W. Brandt

Duke University - Fuqua School of Business ( email )

1 Towerview Drive
Durham, NC 27708-0120
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Francis X. Diebold (Contact Author)

University of Pennsylvania - Department of Economics ( email )

Ronald O. Perelman Center for Political Science
133 South 36th Street
Philadelphia, PA 19104-6297
United States
215-898-1507 (Phone)
215-573-4217 (Fax)

HOME PAGE: http://www.ssc.upenn.edu/~fdiebold/

National Bureau of Economic Research (NBER)

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United States