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Risk adjusted returns from technical trading: a genetic programming approach

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  • Colin Fyfe
  • John Paul Marney
  • Heather Tarbert

Abstract

In this study, Genetic Programming is used to generate technical trading rules. These are assessed in terms of their basic returns and their risk adjusted returns. It is found that while the basic returns are impressive by comparison with buy and hold, they do not outperform buy and hold after risk-adjustment.

Suggested Citation

  • Colin Fyfe & John Paul Marney & Heather Tarbert, 2005. "Risk adjusted returns from technical trading: a genetic programming approach," Applied Financial Economics, Taylor & Francis Journals, vol. 15(15), pages 1073-1077.
    • Handle: RePEc:taf:apfiec:v:15:y:2005:i:15:p:1073-1077
    DOI: 10.1080/09603100500306709
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    References listed on IDEAS

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    1. J.P. Marney & H. Tarbert & C. Fyfe, 2000. "Technical Trading Versus Market Efficiency-A Genetic Programming Approach," Computing in Economics and Finance 2000 169, Society for Computational Economics.
    2. Boswijk, H.P. & Griffioen, G.A.W. & Hommes, C.H., 2000. "Succes and Failure of Technical Trading Strategies in the Cocoa Futures Markets," CeNDEF Working Papers 00-06, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
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    7. Colin Fyfe & John Paul Marney & Heather Tarbert, 1999. "Technical analysis versus market efficiency - a genetic programming approach," Applied Financial Economics, Taylor & Francis Journals, vol. 9(2), pages 183-191.
    8. Franklin Allen & Risto Karjalainen, "undated". "Using Genetic Algorithms to Find Technical Trading Rules (Revised: 20-95)," Rodney L. White Center for Financial Research Working Papers 20-93, Wharton School Rodney L. White Center for Financial Research.
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    Cited by:

    1. Janice How & Martin Ling & Peter Verhoeven, 2010. "Does size matter? A genetic programming approach to technical trading," Quantitative Finance, Taylor & Francis Journals, vol. 10(2), pages 131-140.

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