Integrated Covariance Estimation using High-frequency Data in the Presence of Noise
| Autor: | Asger Lunde, Valeri Voev |
|---|---|
| Rok vydání: | 2006 |
| Předmět: |
Independent and identically distributed random variables
Economics and Econometrics Covariance function Computer science Integrated covariance Nonsynchronous trading Estimator Covariance Synchronization Noise Estimation of covariance matrices Market microstructure noise Statistics Epps effect Martingale (probability theory) Algorithm Subsampling Finance Interpolation Mathematics Complement (set theory) |
| Zdroj: | Voev, V & Lunde, A 2007, ' Integrated covariance estimation using high-frequency data in the presence of noise ', Journal of Financial Econometrics, vol. 5, no. 1, pp. 68-104 . < http://jfec.oxfordjournals.org/cgi/reprint/5/1/68 > |
| ISSN: | 1479-8417 1479-8409 |
| DOI: | 10.1093/jjfinec/nbl011 |
| Popis: | We analyze the effects of nonsynchronicity and market microstructure noise on realized covariance type estimators. Hayashi and Yoshida (2005) propose a simple estimator that resolves the problem of nonsynchronicity and is unbiased and consistent for the integrated covariance in the absence of noise. When noise is present, however, we find that this estimator is biased, and show how the bias can be corrected for. Ultimately, we propose a subsampling version of the bias-corrected estimator which improves its efficiency. Empirically, we find that the usual assumption of a martingale price process plus an independently and identically distributed (i.i.d.) noise does not describe the dynamics of the observed price process across stocks, which confirms the practical relevance of our general noise specification and the estimation techniques we propose.Finally, a simulation experiment is carried out to complement the theoretical results. Udgivelsesdato: WIN We analyze the effects of nonsynchronicity and market microstructure noise on realized covariance type estimators. Hayashi and Yoshida (2005) propose a simple estimator that resolves the problem of nonsynchronicity and is unbiased and consistent for the integrated covariance in the absence of noise. When noise is present, however, we find that this estimator is biased, and show how the bias can be corrected for. Ultimately, we propose a subsampling version of the bias-corrected estimator which improves its efficiency. Empirically, we find that the usual assumption of a martingale price process plus an independently and identically distributed (i.i.d.) noise does not describe the dynamics of the observed price process across stocks, which confirms the practical relevance of our general noise specification and the estimation techniques we propose.Finally, a simulation experiment is carried out to complement the theoretical results. |
| Databáze: | OpenAIRE |
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