Consistent estimation of covariation under nonsynchronicity

Takaki Hayashi; Shigeo Kusuoka

doi:10.1007/s11203-007-9009-9

Consistent estimation of covariation under nonsynchronicity

Takaki Hayashi, Shigeo Kusuoka

Graduate School of Business Administration

Research output: Contribution to journal › Article

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 language	English
Pages (from-to)	93-106
Number of pages	14
Journal	Statistical Inference for Stochastic Processes
Volume	11
Issue number	1
DOIs	https://doi.org/10.1007/s11203-007-9009-9
Publication status	Published - 2008 Feb 1

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Keywords

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

ASJC Scopus subject areas

Statistics and Probability

Cite this

Hayashi, T., & Kusuoka, S. (2008). Consistent estimation of covariation under nonsynchronicity. Statistical Inference for Stochastic Processes, 11(1), 93-106. https://doi.org/10.1007/s11203-007-9009-9

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10.1007/s11203-007-9009-9