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 ()
Asia-Pacific Financial Markets, 2015, vol. 22, issue 3, 333-368
For estimating the integrated volatility and covariance by using high frequency data, Kunitomo and Sato (Math Comput Simul 81:1272–1289, 2011 ; N Am J Econ Finance 26:289–309, 2013 ) have proposed the separating information maximum likelihood (SIML) method when there are micro-market noises. The SIML estimator has reasonable finite sample properties and asymptotic properties when the sample size is large when the hidden efficient price process follows 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 and noises, and when the 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 finite sample properties with these effects. Copyright Springer Japan 2015
Keywords: Integrated covariance; Hedging coefficient; High-frequency financial data; Round-off errors; Micro-market price adjustments and noises; Random sampling; Separating information maximum likelihood (SIML) (search for similar items in EconPapers)
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