Estimating stochastic volatility diffusion using conditional moments of integrated volatility

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2002-07-01

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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.

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10.1016/S0304-4076(01)00141-5

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Bollerslev, T, and H Zhou (2002). Estimating stochastic volatility diffusion using conditional moments of integrated volatility. Journal of Econometrics, 109(1). pp. 33–65. 10.1016/S0304-4076(01)00141-5 Retrieved from https://hdl.handle.net/10161/1893.

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Bollerslev

Tim Bollerslev

Juanita and Clifton Kreps Distinguished Professor of Economics, in Trinity College of Arts and Sciences

Professor Bollerslev conducts research in the areas of time-series econometrics, financial econometrics, and empirical asset pricing finance. He is particularly well known for his developments of econometric models and procedures for analyzing and forecasting financial market volatility. Much of Bollerslev’s recent research has focused on the analysis of newly available high-frequency intraday, or tick-by-tick, financial data and so-called realized volatility measures, macroeconomic news announcement effects, and the pricing of volatility risk. Recent reviews of his work are available in the two Handbook chapters "Volatility and Correlation Forecasting” (with Torben G. Andersen, Peter Christoffersen and Francis X. Diebold), Handbook of Economic Forecasting, (eds. Graham Elliott, Clive W.J. Granger and Allan Timmermann), 2006, and "Parametric and Nonparametric Volatility Measurement” (with Torben G. Andersen and Francis X. Diebold), in Handbook of Financial Econometrics, (eds. Yacine Aït-Sahalia and Lars P. Hansen), 2009.


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