| Project/Area Number |
17530165
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Economic statistics
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| Research Institution | Yokohama National University |
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Principal Investigator |
NAGAI Keiji Yokohama National Univ., International Graduate School of Social Sciences, Associate Professor, 大学院・国際社会科学研究科, 助教授 (50311866)
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| Project Period (FY) |
2005 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2006: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2005: ¥2,400,000 (Direct Cost: ¥2,400,000)
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| Keywords | Financial Econometrics / High-frequency data / Volatility / Nonsyncronous Observation / Unit Root Test / Nonparametrics / Sequential test / Renewal theory / らんだむ / GARCH / 経験尤度法 / ベイズ法 |
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| Research Abstract |
For the analysis using high-frequency financial time series, a joint research "Nonparametric Estimation of Multivariate Integrated Volatilities" with Prof. Yosihiko Nishiyama of Institute of Economic Research, Kyoto University is about the estimate manner of volatility of multi-dimensional diffusion process observed nonsynchronously, in which we consider the Malliavin-Mancino estimator and the Hayashi-Yoshida estimator from views of theory and simulation. We conclude that the Hayashi-Yoshida estimator is superior. We also estimated the covariance using government bond futures tick data as empirical study.
In the joint research "Nonparametric Estimation for the High Frequency Observations of Multivariate Ito Processes" with Song Mingzi, we provide a nonparametric estimator of multivariate volatility of Ito processes which exploits the estimator of the local time of semimartingale.
In "Nonlinear renewal theorems for random walks with perturbations of intermediate order," (with Cun-Hui Zhang), we prove a nonlinear renewal theorem for a random walk having perturbation terms, which is becoming important in a theory of statistical sequential analysis. We apply it to the nonparametric sequential probability ratio test.
We also suggest new method of performing a unit root test by manner of a sequential test in the paper reported in the invited session of the meeting of Japanese Statistical Association in 2007.
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