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Risk adjusted returns from technical trading: a genetic programming approach

Author

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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. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    2. W. Brian Arthur & Paul Tayler, "undated". "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Computing in Economics and Finance 1997 57, Society for Computational Economics.
    3. 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.
    4. Stephen Brown & William Goetzmann & Alok Kumar, 1998. "The Dow Theory: William Peter Hamilton's Track Record Re-Considered," Yale School of Management Working Papers ysm85, Yale School of Management, revised 01 Apr 2008.
    5. 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.
    6. 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.
    7. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    8. Neely, Christopher & Weller, Paul & Dittmar, Rob, 1997. "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(4), pages 405-426, December.
    9. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    10. repec:bla:jfinan:v:53:y:1998:i:4:p:1311-1333 is not listed on IDEAS
    11. Hendrik Bessembinder & Kalok Chan, 1998. "Market Efficiency and the Returns to Technical Analysis," Financial Management, Financial Management Association, vol. 27(2), Summer.
    12. Routledge, Bryan R., 2001. "Genetic Algorithm Learning To Choose And Use Information," Macroeconomic Dynamics, Cambridge University Press, vol. 5(02), pages 303-325, April.
    13. W. Brian Arthur & John H. Holland & Blake LeBaron & Richard Palmer & Paul Taylor, 1996. "Asset Pricing Under Endogenous Expectation in an Artificial Stock Market," Working Papers 96-12-093, Santa Fe Institute.
    14. C. H. Hommes, 2001. "Financial markets as nonlinear adaptive evolutionary systems," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 149-167.
    15. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    16. Bessembinder, Hendrik & Chan, Kalok, 1995. "The profitability of technical trading rules in the Asian stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 3(2-3), pages 257-284, July.
    17. 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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