2012 Fiscal Year Final Research Report
Change-point analysis for time series using asymptotic theory for symmetric statistics
| Project/Area Number |
20540140
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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 |
General mathematics (including Probability theory/Statistical mathematics)
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| Research Institution | Tokyo City University |
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Principal Investigator |
KANAGAWA Shuya 東京都市大学, 知識工学部, 教授 (50185899)
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| Co-Investigator(Kenkyū-buntansha) |
MAEZONO Nobuhiko 九州大学, 大学院・数理学研究科, 教授 (30173701)
SAISHO Yasumasa 広島大学, 大学院・工学研究科, 准教授 (70195973)
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| Project Period (FY) |
2008 – 2012
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| Keywords | 変化点解析 / 混合性 / U-統計量 / 確率微分方程式 / 数理ファイナンス |
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| Research Abstract |
The aim of the research is to consider an estimation of thechange-point for a s e q u e n c e o f r a n d o m v a r i a b l e s s a t i s f i e s n o t o n l y i n d e p e n d e n c e b u t a l s o some mixing condition from the next reason. Even if these random variables of the sequenceare independent, there possibly exists a regression between them. Especially if they aresequences of linear time series e.g. moving average processes, they satisfy some mixingcondition under the assumptions for their coefficients. We consider not only SDE drivenby a Brownian motion but also by a process with stationary increments from the viewpointsof time series analysis for mathematical finance. For example, when we observe two dataseries of returns for different stocks, it is important to find the regression betweentwo stocks.
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