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

Naoto Kunitomo, Hiroumi Misaki, Seisho Sato

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)333-368
Number of pages36
JournalAsia-Pacific Financial Markets
Volume22
Issue number3
DOIs
Publication statusPublished - 7 Sep 2015

Keywords

  • Hedging coefficient
  • High-frequency financial data
  • Integrated covariance
  • Micro-market price adjustments and noises
  • Random sampling
  • Round-off errors
  • Separating information maximum likelihood (SIML)

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