A multiscale neural network learning paradigm for financial crisis forecasting
文献类型：期刊论文
| 作者 | Yu, Lean1; Wang, Shouyang1; Lai, Kin Keung2; Wen, Fenghua3 |
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2010 |
| 卷号 | 73期号:4-6页码:716-725 |
| 关键词 | Artificial neural networks Empirical mode decomposition (EMD) Hilbert-EMD transform Multiscale learning Financial crisis forecasting |
| ISSN号 | 0925-2312 |
| DOI | 10.1016/j.neucom.2008.11.035 |
| 英文摘要 | A financial crisis is typically a rare kind of an event, but it hurts sustainable economic development when it occurs. This study proposes a multiscale neural network learning paradigm to predict financial crisis events for early-warning purposes. In the proposed multiscale neural network learning paradigm, currency exchange rate, a typical financial indicator that usually reflects economic fluctuations, is first chosen. Then a Hilbert-EMD algorithm is applied to the currency exchange rate series. Using the Hilbert-EMD procedure, some intrinsic mode components (IMCs) of the currency exchange rate series, with different scales, can be obtained. Subsequently, the internal correlation structures of different IMCs are explored by a neural network model. Using the neural network weights, some important IMCs are selected as the final neural network inputs and some unimportant IMCs that are of little use in mapping from inputs to output are discarded. Using these selected IMCs, a neural network learning paradigm is used to predict future financial crisis events, based upon some historical data. For illustration purpose, the proposed multiscale neural network learning paradigm is applied to exchange rate data of two Asian countries to evaluate the state of financial crisis. Experimental results reveal that the proposed multiscale neural network learning paradigm can significantly improve the generalization performance relative to conventional neural networks. (C) 2009 Elsevier B.V. All rights reserved. |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000275643000023 |
| 出版者 | ELSEVIER SCIENCE BV |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/9846]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 通讯作者 | Yu, Lean |
| 作者单位 | 1.Chinese Acad Sci, Inst Syst Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 2.City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China 3.Changsha Univ Sci & Technol, Sch Econ & Management, Changsha 410076, Hunan, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yu, Lean,Wang, Shouyang,Lai, Kin Keung,et al. A multiscale neural network learning paradigm for financial crisis forecasting[J]. NEUROCOMPUTING,2010,73(4-6):716-725. |
| APA | Yu, Lean,Wang, Shouyang,Lai, Kin Keung,&Wen, Fenghua.(2010).A multiscale neural network learning paradigm for financial crisis forecasting.NEUROCOMPUTING,73(4-6),716-725. |
| MLA | Yu, Lean,et al."A multiscale neural network learning paradigm for financial crisis forecasting".NEUROCOMPUTING 73.4-6(2010):716-725. |
入库方式： OAI收割
来源：数学与系统科学研究院
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