TY  - JOUR
AU  - Alizadeh,Sassan
AU  - Brandt,Michael W.
AU  - Diebold,Francis X.
TI  - High- and Low-Frequency Exchange Rate Volatility Dynamics: Range-Based Estimation of Stochastic Volatility Models
JF  - National Bureau of Economic Research Working Paper Series
VL  - No. 8162
PY  - 2001
Y2  - March 2001
UR  - http://www.nber.org/papers/w8162
L1  - http://www.nber.org/papers/w8162.pdf
N1  - Author contact info:
Sassan Alizadeh
Highbridge Capital Management
9 West 57th Street, 27th Floor
New York, NY 10019
E-Mail: salizadeh@yahoo.com

Michael W. Brandt
Fuqua School of Business
Duke University
One Towerview Drive
Durham, NC  27708
Tel: 919/660-1948
Fax: 919/660-8038
E-Mail: mbrandt@duke.edu

Francis X. Diebold
Department of Economics
University of Pennsylvania
3718 Locust Walk
Philadelphia, PA  19104-6297
Tel: 215/898-1507
Fax: 212/573-4217
E-Mail: fdiebold@sas.upenn.edu
AB  - 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 two-factor models with one highly persistent factor and one quickly mean-reverting factor.
ER  -