A neural-network-based nonlinear metamodeling approach to financial time series forecasting

doi:10.1016/j.asoc.2008.08.001

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	A neural-network-based nonlinear metamodeling approach to financial time series forecasting
	Yu, Lean 1; Wang, Shouyang1 ; Lai, Kin Keung 2
	2009-03-01
发表期刊	APPLIED SOFT COMPUTING
ISSN	1568-4946
卷号	9 期号:2 页码:563-574
摘要	In financial time series forecasting, the problem that we often encounter is how to increase the prediction accuracy as possible using the financial data with noise. In this study, we discuss the use of supervised neural networks as a meta-learning technique to design a financial time series forecasting system to solve this problem. In this system, some data sampling techniques are first used to generate different training subsets from the original datasets. In terms of these different training subsets, different neural networks with different initial conditions or training algorithms are then trained to formulate different prediction models, i.e., base models. Subsequently, to improve the efficiency of predictions of metamodeling, the principal component analysis (PCA) technique is used as a pruning tool to generate an optimal set of base models. Finally, a neural-network-based nonlinear metamodel can be produced by learning from the selected base models, so as to improve the prediction accuracy. For illustration and verification purposes, the proposed metamodel is conducted on four typical financial time series. Empirical results obtained reveal that the proposed neural-network-based nonlinear metamodeling technique is a very promising approach to financial time series forecasting. (c) 2008 Elsevier B.V. All rights reserved.
关键词	Artificial neural networks Metamodeling Data sampling Meta-learning PCA Financial time series forecasting
DOI	10.1016/j.asoc.2008.08.001
语种	英语
资助项目	National Natural Science Foundation of China[70601029] ; National Natural Science Foundation of China[70221001] ; Knowledge Innovation Program of Chinese Academy of Sciences[3547600] ; Strategic Research Grant of City University of Hong Kong[7001807]
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications
WOS记录号	WOS:000262888100012
出版者	ELSEVIER SCIENCE BV
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/7083
专题	系统科学研究所
通讯作者	Yu, Lean
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Beijing 100190, Peoples R China 2.City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China
推荐引用方式 GB/T 7714	Yu, Lean,Wang, Shouyang,Lai, Kin Keung. A neural-network-based nonlinear metamodeling approach to financial time series forecasting[J]. APPLIED SOFT COMPUTING,2009,9(2):563-574.
APA	Yu, Lean,Wang, Shouyang,&Lai, Kin Keung.(2009).A neural-network-based nonlinear metamodeling approach to financial time series forecasting.APPLIED SOFT COMPUTING,9(2),563-574.
MLA	Yu, Lean,et al."A neural-network-based nonlinear metamodeling approach to financial time series forecasting".APPLIED SOFT COMPUTING 9.2(2009):563-574.