Outperforming buy-and-hold with evolved technical trading rules: Daily, weekly and monthly trading

Dome Lohpetch, David Corne

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Genetic programming (GP) is increasingly popular as a research tool for applications in finance and economics. One thread in this area is the use of GP to discover effective technical trading rules. In a seminal article, Allen & Karjalainen (1999) used GP to find rules that were profitable, but were nevertheless outperformed by the simple "buy and hold" trading strategy. Many succeeding attempts have reported similar findings. There are a small handful of cases in which such work has managed to find rules that outperform buy-and-hold, but these have tended to be difficult to replicate. Recently, however, Lohpetch & Corne (2009) investigated work by Becker & Seshadri (2003), which showed outperformance of buy-and-hold. In turn, Becker & Seshadri's work had made several modifications to Allen & Karjalainen's work, including the adoption of monthly rather than daily trading. Lohpetch et al (2009) provided a replicable account of this, and also showed how further modifications enabled fairly reliable outperformance of buy-and-hold. It remained unclear, however, whether adoption of monthly trading is necessary to achieve robust outperformance of buy-and-hold. Here we investigate and compare each of daily, weekly and monthly trading; we find that outperformance of buy-and-hold can be achieved even for daily trading, but as we move from monthly to daily trading the performance of evolved rules becomes increasingly dependent on prevailing market conditions. © 2010 Springer-Verlag Berlin Heidelberg.

Original languageEnglish
Title of host publicationApplications of Evolutionary Computation - EvoApplications 2010: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoMUSART, and EvoTRANSLOG, Proceedings
Pages171-181
Number of pages11
Volume6025 LNCS
EditionPART 2
DOIs
Publication statusPublished - 2010
EventEvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, and EvoSTOC, EvoApplicatons 2010 - Istanbul, Turkey
Duration: 7 Apr 20109 Apr 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6025 LNCS
ISSN (Print)0302-9743

Conference

ConferenceEvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, and EvoSTOC, EvoApplicatons 2010
CountryTurkey
CityIstanbul
Period7/04/109/04/10

Keywords

  • Data mining
  • Genetic programming
  • Technical trading rules

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