Separating Information Maximum Likelihood Estimation of Realized Volatility and Covariance with Micro-Market Noise
For estimating the realized volatility and covariance by using high frequency data, we introduce the Separating Information Maximum Likelihood (SIML) method when there are possibly micro-market noises. The resulting estimator is simple and it has the representation as a specific quadratic form of returns. The SIML estimator has reasonable asymptotic properties; it is consistent and it has the asymptotic normality (or the stable convergence in the general case) when the sample size is large under general conditions including non-Gaussian processes and volatility models. Based on simulations, we find that the SIML estimator has reasonable finite sample properties and thus it would be useful for practice. It is also possible to use the limiting distribution of the SIML estimator for constructing testing procedures and confidence intervals.
|Date of creation:||Aug 2008|
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- Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2006.
"Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise,"
2006-W03, Economics Group, Nuffield College, University of Oxford.
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- Ole E Barndorff-Nielsen & Peter Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," OFRC Working Papers Series 2006fe05, Oxford Financial Research Centre.
- Yacine Aït-Sahalia, 2005.
"How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise,"
Review of Financial Studies,
Society for Financial Studies, vol. 18(2), pages 351-416.
- Yacine Ait-Sahalia & Per A. Mykland, 2003. "How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise," NBER Working Papers 9611, National Bureau of Economic Research, Inc.
- repec:oxf:wpaper:2006-w03 is not listed on IDEAS
- Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005.
"A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data,"
Journal of the American Statistical Association,
American Statistical Association, vol. 100, pages 1394-1411, December.
- Lan Zhang & Per A. Mykland & Yacine Ait-Sahalia, 2003. "A Tale of Two Time Scales: Determining Integrated Volatility with Noisy High Frequency Data," NBER Working Papers 10111, National Bureau of Economic Research, Inc.
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