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 | |
| Publication status | Published - 2008 Feb |
Fingerprint
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 journal › Article
}
TY - JOUR
T1 - Consistent estimation of covariation under nonsynchronicity
AU - Hayashi, Takaki
AU - Kusuoka, Shigeo
PY - 2008/2
Y1 - 2008/2
N2 - 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)
AB - 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)
KW - Consistency
KW - Discrete-time sampling
KW - High-frequency data
KW - Nonsynchronous trading
KW - Quadratic variation
KW - Realized covariance
KW - Semimartingale
KW - Stopping time
UR - http://www.scopus.com/inward/record.url?scp=35648969629&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=35648969629&partnerID=8YFLogxK
U2 - 10.1007/s11203-007-9009-9
DO - 10.1007/s11203-007-9009-9
M3 - Article
AN - SCOPUS:35648969629
VL - 11
SP - 93
EP - 106
JO - Statistical Inference for Stochastic Processes
JF - Statistical Inference for Stochastic Processes
SN - 1387-0874
IS - 1
ER -