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
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: Suggested Citation
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