Statistical Inference for Duration Model using High-Frequency Financial Time Series

使用高频金融时间序列对持续时间模型进行统计推断

• 批准号: 17530165
• 负责人: NAGAI Keiji
• 金额: $ 2.24万
• 依托单位: Yokohama National University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2005
• 资助国家: 日本
• 起止时间: 2005 至 2006
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-17530165/
• 关键词: 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

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.

对于高频金融时间序列的分析，与京都大学经济研究所Yosihiko Nishiyama教授的联合研究“多元综合波动率的非参数估计”是关于非同步观测的多维扩散过程波动率的估计方式，其中我们考虑了Malliavin-Mancino估计器和Hayashi-Yoshida估计器 理论和模拟的观点。我们的结论是 Hayashi-Yoshida 估计量更优。我们还使用国债期货报价数据估计协方差作为实证研究。在与宋明子的联合研究“多元伊藤过程高频观测的非参数估计”中，我们提供了利用半鞅局部时间估计的伊藤过程多元波动性的非参数估计。在“随机游走的非线性更新定理”中 中阶扰动”（与张存辉合作），我们证明了具有扰动项的随机游走的非线性更新定理，这在统计序贯分析理论中变得越来越重要。我们将其应用于非参数序贯概率比检验。我们还在2007年日本统计协会会议特邀会议上报告的论文中提出了通过序贯检验的方式进行单位根检验的新方法。

项目成果

Sequential estimation of autoregressive parameter with ARCH errors

具有 ARCH 误差的自回归参数的序贯估计

• 发表时间: 2005
• 期刊: Proceedings of Japan Statistical Society
• 作者: Keiji Nagai;Yosuke Takahashi
• 通讯作者: Yosuke Takahashi

Nonlinear renewal theorems for random walks with perturbations of intermediate order

具有中阶扰动的随机游走的非线性更新定理

• 发表时间: 2006
• 期刊: IMS Lecture Notes-Monograph Series Recent Developments in Nonparametric Inference and Probability 50
• 作者: Keiji Nagai;Cun-Hui Zhang
• 通讯作者: Cun-Hui Zhang

Empirical likelihood estimation for regression model with ARCH errors

具有 ARCH 误差的回归模型的经验似然估计

• 发表时间: 2005
• 期刊: 統計関連学会連合大会報告集
• 作者: 永井圭二;秋山宣久
• 通讯作者: 秋山宣久

Nonparametric Estimation for the High Frequency Observations of Multivariate Ito Processes

多元 Ito 过程高频观测的非参数估计

• 作者: 永井 圭二;宋明子
• 通讯作者: 宋明子

「研究成果報告書概要(和文)」より

摘自《研究结果报告摘要（日文）》

• 发表时间: 2005
• 作者: Kawauchi;et. al.;Nishimura et al.;Dezawa et al.;Yoshizawa et al.;星野 幹雄;星野 幹雄
• 通讯作者: 星野 幹雄