A novel adaptive learning algorithm for stock market prediction

Lean Yu; Shouyang Wang; Kin Keung Lai

doi:10.1007/11602613_45

A novel adaptive learning algorithm for stock market prediction

Lean Yu, Shouyang Wang, Kin Keung Lai

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

10 Citations (Scopus)

Abstract

In this study, a novel adaptive learning algorithm for feed-forward network based on optimized instantaneous learning rates is proposed to predict stock market movements. In this new algorithm, the optimized adaptive learning rates are used to adjust the weight changes dynamically. For illustration and testing purposes the proposed algorithm is applied to two main stock price indices: S&P 500 and Nikkei 225. The experimental results reveal that the proposed algorithm provides a promising alternative to stock market prediction. © Springer-Verlag Berlin Heidelberg 2005.

Original language	English
Title of host publication	Algorithms and Computation
Subtitle of host publication	16th International Symposium, ISAAC 2005, Proceedings
Publisher	Springer Verlag
Pages	443-452
Volume	3827 LNCS
ISBN (Print)	3540309357, 9783540309352
DOIs	https://doi.org/10.1007/11602613_45
Publication status	Published - 2005
Event	16th International Symposium on Algorithms and Computation (ISAAC 2005) - Hainan, China Duration: 19 Dec 2005 → 21 Dec 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3827 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Symposium on Algorithms and Computation (ISAAC 2005)
Place	China
City	Hainan
Period	19/12/05 → 21/12/05

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Yu, L., Wang, S., & Lai, K. K. (2005). A novel adaptive learning algorithm for stock market prediction. In Algorithms and Computation: 16th International Symposium, ISAAC 2005, Proceedings (Vol. 3827 LNCS, pp. 443-452). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3827 LNCS). Springer Verlag. https://doi.org/10.1007/11602613_45

Yu, Lean ; Wang, Shouyang ; Lai, Kin Keung. / A novel adaptive learning algorithm for stock market prediction. Algorithms and Computation: 16th International Symposium, ISAAC 2005, Proceedings. Vol. 3827 LNCS Springer Verlag, 2005. pp. 443-452 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{8da04759ed494a2598895550a425c927,

title = "A novel adaptive learning algorithm for stock market prediction",

abstract = "In this study, a novel adaptive learning algorithm for feed-forward network based on optimized instantaneous learning rates is proposed to predict stock market movements. In this new algorithm, the optimized adaptive learning rates are used to adjust the weight changes dynamically. For illustration and testing purposes the proposed algorithm is applied to two main stock price indices: S&P 500 and Nikkei 225. The experimental results reveal that the proposed algorithm provides a promising alternative to stock market prediction. {\textcopyright} Springer-Verlag Berlin Heidelberg 2005.",

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

year = "2005",

doi = "10.1007/11602613_45",

language = "English",

isbn = "3540309357",

volume = "3827 LNCS",

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

publisher = "Springer Verlag",

pages = "443--452",

booktitle = "Algorithms and Computation",

address = "Germany",

note = "16th International Symposium on Algorithms and Computation (ISAAC 2005) ; Conference date: 19-12-2005 Through 21-12-2005",

}

Yu, L, Wang, S & Lai, KK 2005, A novel adaptive learning algorithm for stock market prediction. in Algorithms and Computation: 16th International Symposium, ISAAC 2005, Proceedings. vol. 3827 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3827 LNCS, Springer Verlag, pp. 443-452, 16th International Symposium on Algorithms and Computation (ISAAC 2005), Hainan, China, 19/12/05. https://doi.org/10.1007/11602613_45

A novel adaptive learning algorithm for stock market prediction. / Yu, Lean; Wang, Shouyang; Lai, Kin Keung.
Algorithms and Computation: 16th International Symposium, ISAAC 2005, Proceedings. Vol. 3827 LNCS Springer Verlag, 2005. p. 443-452 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3827 LNCS).

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

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AU - Yu, Lean

AU - Wang, Shouyang

AU - Lai, Kin Keung

PY - 2005

Y1 - 2005

N2 - In this study, a novel adaptive learning algorithm for feed-forward network based on optimized instantaneous learning rates is proposed to predict stock market movements. In this new algorithm, the optimized adaptive learning rates are used to adjust the weight changes dynamically. For illustration and testing purposes the proposed algorithm is applied to two main stock price indices: S&P 500 and Nikkei 225. The experimental results reveal that the proposed algorithm provides a promising alternative to stock market prediction. © Springer-Verlag Berlin Heidelberg 2005.

AB - In this study, a novel adaptive learning algorithm for feed-forward network based on optimized instantaneous learning rates is proposed to predict stock market movements. In this new algorithm, the optimized adaptive learning rates are used to adjust the weight changes dynamically. For illustration and testing purposes the proposed algorithm is applied to two main stock price indices: S&P 500 and Nikkei 225. The experimental results reveal that the proposed algorithm provides a promising alternative to stock market prediction. © Springer-Verlag Berlin Heidelberg 2005.

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U2 - 10.1007/11602613_45

DO - 10.1007/11602613_45

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

SN - 3540309357

SN - 9783540309352

VL - 3827 LNCS

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

SP - 443

EP - 452

BT - Algorithms and Computation

PB - Springer Verlag

T2 - 16th International Symposium on Algorithms and Computation (ISAAC 2005)

Y2 - 19 December 2005 through 21 December 2005

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Yu L, Wang S, Lai KK. A novel adaptive learning algorithm for stock market prediction. In Algorithms and Computation: 16th International Symposium, ISAAC 2005, Proceedings. Vol. 3827 LNCS. Springer Verlag. 2005. p. 443-452. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11602613_45

A novel adaptive learning algorithm for stock market prediction

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