Estimating Stochastic Volatility Diffusion Using Conditional Moments of Integrated Volatility

44 Pages Posted: 13 Dec 2001

See all articles by Hao Zhou

Hao Zhou

Tsinghua University - PBC School of Finance

Tim Bollerslev

Duke University - Finance; Duke University - Department of Economics; National Bureau of Economic Research (NBER)

Date Written: November 2001

Abstract

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.

Keywords: Stochastic volatility diffusions, integrated volatility, quadratic variation, realized volatility, high-frequency data, foreign exchange rates, GMM Estimation

JEL Classification: C13, C22

Suggested Citation

Zhou, Hao and Bollerslev, Tim, Estimating Stochastic Volatility Diffusion Using Conditional Moments of Integrated Volatility (November 2001). FEDS Working Paper No. 2001-49; Journal of Econometrics, Vol. 109, pp. 33-65, 2002. Available at SSRN: https://ssrn.com/abstract=293684 or http://dx.doi.org/10.2139/ssrn.293684

Hao Zhou (Contact Author)

Tsinghua University - PBC School of Finance ( email )

No. 43, Chengfu Road
Haidian District
Beijing, 100083
China
86-10-62790655 (Phone)

Tim Bollerslev

Duke University - Finance ( email )

Durham, NC 27708-0120
United States
919-660-1846 (Phone)
919-684-8974 (Fax)

Duke University - Department of Economics

213 Social Sciences Building
Box 90097
Durham, NC 27708-0204
United States

National Bureau of Economic Research (NBER)

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Cambridge, MA 02138
United States

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