2013 Fiscal Year Final Research Report
Study of forecasting system for financial economic data
| Project/Area Number |
23500364
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | The University of Tokyo (2013)
The Institute of Statistical Mathematics (2011-2012) |
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Principal Investigator |
SATO Seisho 東京大学, 経済学研究科(研究院), 准教授 (60280525)
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| Project Period (FY) |
2011 – 2013
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| Keywords | 時系列予測 / 多変量自己回帰モデル / 分離情報最尤法 / 季節調整法 / 逐次予測 / X12Decomp / AIC最適化 / ビッグデータ |
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| Research Abstract |
In this study, I developed a time series forecasting system for financial economic data from given data sets. Separating Information Maximum Likelihood method was used for robust estimating in the first step, then I utilized Vector Autoregressive models for the predicting models which are optimal in the sense of AIC. It is very important for "Big data" era that this system can be applied for large scaled data. A new knowledge discovery is expected when this method is applied for various economic data and business data.
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