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

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  • Sassan Alizadeh
  • Michael W. Brandt
  • Francis X. Diebold

Abstract

We propose using the price range, a recently-neglected volatility proxy with a long history 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.

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Bibliographic Info

Paper provided by Wharton School Center for Financial Institutions, University of Pennsylvania in its series Center for Financial Institutions Working Papers with number 00-28.

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Date of creation: Dec 1999
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Handle: RePEc:wop:pennin:00-28

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Cited by:
  1. Chan, Leo & Lien, Donald, 2003. "Using high, low, open, and closing prices to estimate the effects of cash settlement on futures prices," International Review of Financial Analysis, Elsevier, vol. 12(1), pages 35-47.
  2. John M. Maheu & Thomas H. McCurdy, 2002. "Nonlinear Features of Realized FX Volatility," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 668-681, November.
  3. Chan, Kam C. & Fung, Hung-Gay & Leung, Wai K., 2004. "Daily volatility behavior in Chinese futures markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(5), pages 491-505, December.
  4. Gregory H. Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Working Papers 07-20, Bank of Canada.
  5. Bollerslev, Tim, 2001. "Financial econometrics: Past developments and future challenges," Journal of Econometrics, Elsevier, vol. 100(1), pages 41-51, January.

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