Asia-Pacific Financial Markets

, Volume 22, Issue 3, pp 333–368 | Cite as

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

Article

Abstract

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.

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) 

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Copyright information

© Springer Japan 2015

Authors and Affiliations

  1. 1.Graduate School of EconomicsUniversity of TokyoTokyoJapan
  2. 2.Faculty of Engineering, Information and SystemsUniversity of TsukubaTsukuba CityJapan

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