The SIML Estimation of Integrated Covariance and Hedging Coefficient under Round-off Errors, Micro-market Price Adjustments and Random Sampling

Naoto Kunitomo, Hiroumi Misaki and Seisho Sato
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Naoto Kunitomo: Faculty of Economics, The University of Tokyo
Hiroumi Misaki: Research Center for Advanced Science and Technology, The University of Tokyo
Seisho Sato: Faculty of Economics, The University of Tokyo

No CIRJE-F-965, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: For estimating the integrated volatility and covariance by using high frequency data, Kunitomo and Sato (2011, 2013) have proposed the Separating Information Maximum Likelihood (SIML) method when there are micro-market noises. The SIML estimator has reasonable nite sample properties and asymptotic properties when the sample size is large when the hidden efficient price process follow a Brownian semi-martingale. We shall show that the SIML estimation is useful for estimating the integrated covariance and hedging coefficient when we have round-off errors, micro-market price adjustments, noises and high-frequency data are randomly sampled. The SIML estimation is consistent, asymptotically normal in the stable convergence sense under a set of reasonable assumptions and it has reasonable nite sample properties with these effects. --

Pages: 47pages
Date: 2015-03
New Economics Papers: this item is included in nep-ecm and nep-mst
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Citations: View citations in EconPapers (1)

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