Range-based estimation of stochastic volatility models

Published

Journal Article

We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and empirically that range-based volatility proxies are not only highly efficient, but also approximately Gaussian and robust to microstructure noise. Hence range-based Gaussian quasi-maximum likelihood estimation produces highly efficient estimates of stochastic volatility models and extractions of latent volatility. We use our method to examine the dynamics of daily exchange rate volatility and find the evidence points strongly toward two-factor models with one highly persistent factor and one quickly mean-reverting factor.

Full Text

Duke Authors

Cited Authors

  • Alizadeh, S; Brandt, MW; Diebold, FX

Published Date

  • January 1, 2002

Published In

Volume / Issue

  • 57 / 3

Start / End Page

  • 1047 - 1091

International Standard Serial Number (ISSN)

  • 0022-1082

Digital Object Identifier (DOI)

  • 10.1111/1540-6261.00454

Citation Source

  • Scopus