Consistent estimation of covariation under nonsynchronicity

Takaki Hayashi, Shigeo Kusuoka

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

We present a methodology to estimate the covariance of two time series when they are sampled from continuous semimartingales at general stopping times in a nonsynchronous manner. Approximation error bounds being explored, the estimators are shown to be consistent as the size of the sampling intervals tends to zero. The methodology is easy to be implemented with potentially broad applications, especially in financial modeling and analysis involving high-frequency transaction data. The results generalize those recently obtained by obtained by Hayashi and Yoshida (2005, Bernoulli 11(2):359-379)

Original languageEnglish
Pages (from-to)93-106
Number of pages14
JournalStatistical Inference for Stochastic Processes
Volume11
Issue number1
DOIs
Publication statusPublished - 2008 Feb

Fingerprint

Consistent Estimation
Financial Modeling
Methodology
Stopping Time
Semimartingale
Approximation Error
Bernoulli
Error Bounds
Transactions
Time series
Tend
Estimator
Generalise
Interval
Zero
Estimate

Keywords

  • Consistency
  • Discrete-time sampling
  • High-frequency data
  • Nonsynchronous trading
  • Quadratic variation
  • Realized covariance
  • Semimartingale
  • Stopping time

ASJC Scopus subject areas

  • Mathematics(all)

Cite this

Consistent estimation of covariation under nonsynchronicity. / Hayashi, Takaki; Kusuoka, Shigeo.

In: Statistical Inference for Stochastic Processes, Vol. 11, No. 1, 02.2008, p. 93-106.

Research output: Contribution to journalArticle

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