Estimating stochastic volatility diffusion using conditional moments of integrated volatility

Tim Bollerslev and Hao Zhou

No 2001-49, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

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: Econometric models; Finance (search for similar items in EconPapers)
Date: 2001
New Economics Papers: this item is included in nep-ecm, nep-ifn and nep-pke
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Citations: View citations in EconPapers (7)

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Journal Article: Estimating stochastic volatility diffusion using conditional moments of integrated volatility (2002)
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