Range-Based Estimation of Stochastic Volatility Models

65 Pages Posted: 2 May 2001

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)

Multiple version iconThere are 2 versions of this paper

Date Written: February 15, 2001

Abstract

We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and empirically that the range is not only a highly efficient volatility proxy, but also that it is approximately Gaussian and robust to microstructure noise. The good properties of the range imply that range-based Gaussian quasi-maximum likelihood estimation produces simple and highly efficient estimates of stochastic volatility models and extractions of latent volatility series. We use our method to examine the dynamics of daily exchange rate volatility and discover that traditional one-factor models are inadequate for describing simultaneously the high- and low-frequency dynamics of volatility. Instead, the evidence points strongly toward tw-factor models with one highly persistent factor and one quickly mean-reverting factor.

Suggested Citation

Alizadeh, Sassan and Brandt, Michael W. and Diebold, Francis X., Range-Based Estimation of Stochastic Volatility Models (February 15, 2001). PIER Working Paper No. 01-007. Available at SSRN: https://ssrn.com/abstract=267788 or http://dx.doi.org/10.2139/ssrn.267788

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)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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