Statistical inference for extended models in financial time series

金融时间序列扩展模型的统计推断

• 批准号: 23330075
• 负责人: MAEKAWA Koichi
• 金额: $ 6.32万
• 依托单位: Hiroshima University of Economics
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (B)
• 财政年份: 2011
• 资助国家: 日本
• 起止时间: 2011-04-01 至 2014-03-31
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-23330075/
• 关键词: Nonstandard time series; GARCH error; Error correction model; High frequency data; Structural change; Bootstrap method; Realized volatility; Long memory; 経済時系列分析; 誤差修正モデル; 構造変化の検定; 非定常時系列; ブートストラップ法; 高頻度データ; GARCHモデル; 長期記憶系列; ジャンプ過程; 誤差修正

We studied problems in statistical analysis of financial time series. Since those problems cannot be dealt with classical statistical theory and methods a new research field in econometrics has emerged. As the results the appropriate theory and methods have been developed for problems concerning to the keyword listed below. But even now we think there remain many unsolved problems for compound problems related to plural keywords, such as estimation problems related to vector error correction model with GARCH error, long memory in GARCH process, structural change in high frequency data, modeling of realized volatility by using high frequency time series and so on. We challenged to such problems and attained some significant results including a proposal of some suitable method to such new problems. In addition we evaluated our theoretical and methodological results by computer simulation and applied them to real data.

我们研究了金融时间序列统计分析的问题。由于这些问题无法用经典的统计理论和方法来解决，计量经济学这一新的研究领域就应运而生。作为结果，针对与下面列出的关键字有关的问题，已经开发了适当的理论和方法。但即使是现在，我们认为与复数关键字相关的复合问题仍然有许多未解决的问题，例如与带有 GARCH 误差的向量纠错模型相关的估计问题、GARCH 过程中的长记忆、高频数据的结构变化、通过使用高频时间序列等。我们对这些问题提出了挑战，并取得了一些重大成果，包括针对这些新问题提出了一些合适的方法。此外，我们通过计算机模拟评估了我们的理论和方法结果，并将其应用于实际数据。

项目成果

Bootstrapping Confidence Interval of Single Change Point in Time Series Regression Model(2)

时间序列回归模型中单个变化点的Bootstrapping置信区间（2）

• 作者: Akira Kawaguchi;Takato Kasai;Takayuki Morimoto;勝浦正樹;Shuichi Nagata;橋本紀子・荒木孝治;Shuichi Nagata;Tomoko Kishi;橋本紀子・荒木孝治;Setya H.Amirullah and Koichi Maekawa;川口章;有馬昌宏・福永征世・王程;Amirullah Setya Hardi and Koichi Maekawa
• 通讯作者: Amirullah Setya Hardi and Koichi Maekawa

A self normalization based change point test

基于自标准化的变点测试

• 发表时间: 2014
• 作者: Y.Kinari;N.Mizutani;F.Ohtake;H.Okudaira;周防節雄;Setya H. Amirullah;Akira Kawaguchi;Kusdhianto Setiawan and Koichi Maekawa;片山直也
• 通讯作者: 片山直也

GARCH誤差項を持つ多変量誤差修正モデルの推定

使用 GARCH 误差项估计多元误差校正模型

• 发表时间: 2014
• 期刊: 商学論究（関西学院大学商学研究会）
• 作者: Chigira;H. and Taku;Y;本名純;関源太郎;Yoshihiko Fukushima;前川功一
• 通讯作者: 前川功一

Estimation of Vector Error Correction Model with GARCH Errors: A Simulation Study

具有 GARCH 误差的矢量误差校正模型的估计：仿真研究

• 作者: Akira Kawaguchi;Takato Kasai;Takayuki Morimoto;勝浦正樹;Shuichi Nagata;橋本紀子・荒木孝治;Shuichi Nagata;Tomoko Kishi;橋本紀子・荒木孝治;Setya H.Amirullah and Koichi Maekawa;川口章;有馬昌宏・福永征世・王程;Amirullah Setya Hardi and Koichi Maekawa;Tomoko Kishi;Yoshiko Sugie;Kusdhianto Setiawan;水谷徳子;Setsuo Suoh;Koichi Maekawa
• 通讯作者: Koichi Maekawa

Predicting Volatility with Realized Absolute

用已实现绝对值预测波动率

• 发表时间: 2012
• 期刊: Values : Evidence from the Tokyo Stock Exchange
• 作者: 川口章;大黒俊介;金城ふみ子;Shuichi Nagata
• 通讯作者: Shuichi Nagata