Evolving market index trading rules using grammatical evolution

Michael O’neill; Anthony Brabazon; Conor Ryan; J. J. Collins

doi:10.1007/3-540-45365-2_36

Evolving market index trading rules using grammatical evolution

Michael O’neill, Anthony Brabazon, Conor Ryan, J. J. Collins

Department of Computer Science & Information Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This study examines the potential of an evolutionary automatic programming methodology to uncover a series of useful technical trading rules for the UK FTSE 100 stock index. Index values for the period 26/4/1984 to 4/12/1997 are used to train and test the model. The preliminary findings indicate that the methodology has much potential, outperforming the benchmark strategy adopted.

Original language	English
Title of host publication	Applications of Evolutionary Computing - EvoWorkshops 2001
Subtitle of host publication	EvoCOP, EvoFlight, EvoIASP, EvoLearn and EvoSTIM, Proceedings
Editors	Egbert J. W. Boers
Publisher	Springer Verlag
Pages	343-352
Number of pages	10
ISBN (Print)	3540419209
DOIs	https://doi.org/10.1007/3-540-45365-2_36
Publication status	Published - 2001
Event	European Workshop Applications of Evolutionary Computing, EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn, and EvoSTIM - Como, Italy Duration: 18 Apr 2001 → 20 Apr 2001

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2037
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	European Workshop Applications of Evolutionary Computing, EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn, and EvoSTIM
Country/Territory	Italy
City	Como
Period	18/04/01 → 20/04/01

Access to Document

10.1007/3-540-45365-2_36

Cite this

O’neill, M., Brabazon, A., Ryan, C., & Collins, J. J. (2001). Evolving market index trading rules using grammatical evolution. In E. J. W. Boers (Ed.), Applications of Evolutionary Computing - EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn and EvoSTIM, Proceedings (pp. 343-352). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2037). Springer Verlag. https://doi.org/10.1007/3-540-45365-2_36

O’neill, Michael ; Brabazon, Anthony ; Ryan, Conor et al. / Evolving market index trading rules using grammatical evolution. Applications of Evolutionary Computing - EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn and EvoSTIM, Proceedings. editor / Egbert J. W. Boers. Springer Verlag, 2001. pp. 343-352 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{2c720043076747a9ba1ff2dfc6f178a3,

title = "Evolving market index trading rules using grammatical evolution",

abstract = "This study examines the potential of an evolutionary automatic programming methodology to uncover a series of useful technical trading rules for the UK FTSE 100 stock index. Index values for the period 26/4/1984 to 4/12/1997 are used to train and test the model. The preliminary findings indicate that the methodology has much potential, outperforming the benchmark strategy adopted.",

author = "Michael O{\textquoteright}neill and Anthony Brabazon and Conor Ryan and Collins, {J. J.}",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2001.; European Workshop Applications of Evolutionary Computing, EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn, and EvoSTIM ; Conference date: 18-04-2001 Through 20-04-2001",

year = "2001",

doi = "10.1007/3-540-45365-2_36",

language = "English",

isbn = "3540419209",

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

publisher = "Springer Verlag",

pages = "343--352",

editor = "Boers, {Egbert J. W.}",

booktitle = "Applications of Evolutionary Computing - EvoWorkshops 2001",

}

O’neill, M, Brabazon, A, Ryan, C & Collins, JJ 2001, Evolving market index trading rules using grammatical evolution. in EJW Boers (ed.), Applications of Evolutionary Computing - EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn and EvoSTIM, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2037, Springer Verlag, pp. 343-352, European Workshop Applications of Evolutionary Computing, EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn, and EvoSTIM, Como, Italy, 18/04/01. https://doi.org/10.1007/3-540-45365-2_36

Evolving market index trading rules using grammatical evolution. / O’neill, Michael; Brabazon, Anthony; Ryan, Conor et al.
Applications of Evolutionary Computing - EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn and EvoSTIM, Proceedings. ed. / Egbert J. W. Boers. Springer Verlag, 2001. p. 343-352 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2037).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Evolving market index trading rules using grammatical evolution

AU - O’neill, Michael

AU - Brabazon, Anthony

AU - Ryan, Conor

AU - Collins, J. J.

N1 - Publisher Copyright: © Springer-Verlag Berlin Heidelberg 2001.

PY - 2001

Y1 - 2001

N2 - This study examines the potential of an evolutionary automatic programming methodology to uncover a series of useful technical trading rules for the UK FTSE 100 stock index. Index values for the period 26/4/1984 to 4/12/1997 are used to train and test the model. The preliminary findings indicate that the methodology has much potential, outperforming the benchmark strategy adopted.

AB - This study examines the potential of an evolutionary automatic programming methodology to uncover a series of useful technical trading rules for the UK FTSE 100 stock index. Index values for the period 26/4/1984 to 4/12/1997 are used to train and test the model. The preliminary findings indicate that the methodology has much potential, outperforming the benchmark strategy adopted.

UR - http://www.scopus.com/inward/record.url?scp=84958047647&partnerID=8YFLogxK

U2 - 10.1007/3-540-45365-2_36

DO - 10.1007/3-540-45365-2_36

M3 - Conference contribution

AN - SCOPUS:84958047647

SN - 3540419209

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

SP - 343

EP - 352

BT - Applications of Evolutionary Computing - EvoWorkshops 2001

A2 - Boers, Egbert J. W.

PB - Springer Verlag

T2 - European Workshop Applications of Evolutionary Computing, EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn, and EvoSTIM

Y2 - 18 April 2001 through 20 April 2001

ER -

O’neill M, Brabazon A, Ryan C , Collins JJ. Evolving market index trading rules using grammatical evolution. In Boers EJW, editor, Applications of Evolutionary Computing - EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn and EvoSTIM, Proceedings. Springer Verlag. 2001. p. 343-352. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-45365-2_36

Evolving market index trading rules using grammatical evolution

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this