Estimating stochastic volatility diffusion using conditional moments of integrated volatility

Published

Journal Article

We exploit the distributional information contained in high-frequency intraday data in constructing a simple conditional moment estimator for stochastic volatility diffusions. The estimator is based on the analytical solutions of the first two conditional moments for the latent integrated volatility, the realization of which is effectively approximated by the sum of the squared high-frequency increments of the process. Our simulation evidence indicates that the resulting GMM estimator is highly reliable and accurate. Our empirical implementation based on high-frequency five-minute foreign exchange returns suggests the presence of multiple latent stochastic volatility factors and possible jumps. © 2002 Elsevier Science B.V. All rights reserved.

Full Text

Duke Authors

Cited Authors

  • Bollerslev, T; Zhou, H

Published Date

  • July 1, 2002

Published In

Volume / Issue

  • 109 / 1

Start / End Page

  • 33 - 65

International Standard Serial Number (ISSN)

  • 0304-4076

Digital Object Identifier (DOI)

  • 10.1016/S0304-4076(01)00141-5

Citation Source

  • Scopus