English, Article, Journal or magazine article edition: Range-Based Estimation of Stochastic Volatility Models or Exchange Rate Dynamics are More Interesting Than You Think Sassan Alizadeh; Michael W. Brandt; Francis X. Diebold

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Bookmark: http://trove.nla.gov.au/version/190199
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Range-Based Estimation of Stochastic Volatility Models or Exchange Rate Dynamics are More Interesting Than You Think
Author
  • Sassan Alizadeh
  • Michael W. Brandt
  • Francis X. Diebold
Physical Description
  • preprint
Notes
  • 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.
  • RePEc:wop:pennin:00-28
Language
  • English
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