Estimating stochastic volatility diffusion using conditional moments of integrated volatility
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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- Econometrics
- 4905 Statistics
- 3802 Econometrics
- 3801 Applied economics
- 1403 Econometrics
- 1402 Applied Economics
- 0104 Statistics
Citation
Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Econometrics
- 4905 Statistics
- 3802 Econometrics
- 3801 Applied economics
- 1403 Econometrics
- 1402 Applied Economics
- 0104 Statistics