A novel nonlinear neural network ensemble model for financial time series forecasting

Kin Keung Lai; Lean Yu; Shouyang Wang; Huang Wei

doi:10.1007/11758501_106

A novel nonlinear neural network ensemble model for financial time series forecasting

Kin Keung Lai
, Lean Yu
, Shouyang Wang
, Huang Wei

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

34 Citations (Scopus)

Abstract

In this study, a new nonlinear neural network ensemble model is proposed for financial time series forecasting. In this model, many different neural network models are first generated. Then the principal component analysis technique is used to select the appropriate ensemble members. Finally, the support vector machine regression method is used for neural network ensemble. For further illustration, two real financial time series are used for testing. © Springer-Verlag Berlin Heidelberg 2006.

Original language	English
Title of host publication	Computational Science - ICCS 2006
Subtitle of host publication	6th International Conference, Proceedings
Publisher	Springer Verlag
Pages	790-793
Volume	3991 LNCS - I
ISBN (Print)	3540343792, 9783540343790
DOIs	https://doi.org/10.1007/11758501_106
Publication status	Published - 2006
Event	ICCS 2006: 6th International Conference on Computational Science - Reading, United Kingdom Duration: 28 May 2006 → 31 May 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3991 LNCS - I
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	ICCS 2006: 6th International Conference on Computational Science
Place	United Kingdom
City	Reading
Period	28/05/06 → 31/05/06

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10.1007/11758501_106

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Lai, K. K., Yu, L., Wang, S., & Wei, H. (2006). A novel nonlinear neural network ensemble model for financial time series forecasting. In Computational Science - ICCS 2006: 6th International Conference, Proceedings (Vol. 3991 LNCS - I, pp. 790-793). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3991 LNCS - I). Springer Verlag. https://doi.org/10.1007/11758501_106

Lai, Kin Keung ; Yu, Lean ; Wang, Shouyang et al. / A novel nonlinear neural network ensemble model for financial time series forecasting. Computational Science - ICCS 2006: 6th International Conference, Proceedings. Vol. 3991 LNCS - I Springer Verlag, 2006. pp. 790-793 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{c507c9ce31164abb8b96cca42b8e6f06,

title = "A novel nonlinear neural network ensemble model for financial time series forecasting",

abstract = "In this study, a new nonlinear neural network ensemble model is proposed for financial time series forecasting. In this model, many different neural network models are first generated. Then the principal component analysis technique is used to select the appropriate ensemble members. Finally, the support vector machine regression method is used for neural network ensemble. For further illustration, two real financial time series are used for testing. {\textcopyright} Springer-Verlag Berlin Heidelberg 2006.",

author = "Lai, \{Kin Keung\} and Lean Yu and Shouyang Wang and Huang Wei",

year = "2006",

doi = "10.1007/11758501\_106",

language = "English",

isbn = "3540343792",

volume = "3991 LNCS - I",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "790--793",

booktitle = "Computational Science - ICCS 2006",

address = "Germany",

note = "ICCS 2006: 6th International Conference on Computational Science ; Conference date: 28-05-2006 Through 31-05-2006",

}

Lai, KK, Yu, L, Wang, S & Wei, H 2006, A novel nonlinear neural network ensemble model for financial time series forecasting. in Computational Science - ICCS 2006: 6th International Conference, Proceedings. vol. 3991 LNCS - I, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3991 LNCS - I, Springer Verlag, pp. 790-793, ICCS 2006: 6th International Conference on Computational Science, Reading, United Kingdom, 28/05/06. https://doi.org/10.1007/11758501_106

A novel nonlinear neural network ensemble model for financial time series forecasting. / Lai, Kin Keung; Yu, Lean; Wang, Shouyang et al.
Computational Science - ICCS 2006: 6th International Conference, Proceedings. Vol. 3991 LNCS - I Springer Verlag, 2006. p. 790-793 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3991 LNCS - I).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - A novel nonlinear neural network ensemble model for financial time series forecasting

AU - Lai, Kin Keung

AU - Yu, Lean

AU - Wang, Shouyang

AU - Wei, Huang

PY - 2006

Y1 - 2006

N2 - In this study, a new nonlinear neural network ensemble model is proposed for financial time series forecasting. In this model, many different neural network models are first generated. Then the principal component analysis technique is used to select the appropriate ensemble members. Finally, the support vector machine regression method is used for neural network ensemble. For further illustration, two real financial time series are used for testing. © Springer-Verlag Berlin Heidelberg 2006.

AB - In this study, a new nonlinear neural network ensemble model is proposed for financial time series forecasting. In this model, many different neural network models are first generated. Then the principal component analysis technique is used to select the appropriate ensemble members. Finally, the support vector machine regression method is used for neural network ensemble. For further illustration, two real financial time series are used for testing. © Springer-Verlag Berlin Heidelberg 2006.

UR - https://www.scopus.com/pages/publications/33746619148

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-33746619148&origin=recordpage

U2 - 10.1007/11758501_106

DO - 10.1007/11758501_106

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 3540343792

SN - 9783540343790

VL - 3991 LNCS - I

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 790

EP - 793

BT - Computational Science - ICCS 2006

PB - Springer Verlag

T2 - ICCS 2006: 6th International Conference on Computational Science

Y2 - 28 May 2006 through 31 May 2006

ER -

Lai KK, Yu L, Wang S, Wei H. A novel nonlinear neural network ensemble model for financial time series forecasting. In Computational Science - ICCS 2006: 6th International Conference, Proceedings. Vol. 3991 LNCS - I. Springer Verlag. 2006. p. 790-793. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11758501_106

A novel nonlinear neural network ensemble model for financial time series forecasting

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