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Risk adjusted returns from technical trading: a genetic programming approach

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Author Info
Colin Fyfe
John 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.

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Publisher Info
Article provided by Taylor and Francis Journals in its journal Applied Financial Economics.

Volume (Year): 15 (2005)
Issue (Month): 15 (October)
Pages: 1073-1077
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:taf:apfiec:v:15:y:2005:i:15:p:1073-1077

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  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. [Downloadable!] (restricted)
  2. Boswijk, H.P., Griffioen, G.A.W., Hommes, C.H., 2001. "Succes and Failure of Technical Trading Strategies in the Cocoa Futures Market," Computing in Economics and Finance 2001 120, Society for Computational Economics.
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  3. Cars H. Hommes, 2001. "Financial Markets as Nonlinear Adaptive Evolutionary Systems," Tinbergen Institute Discussion Papers 01-014/1, Tinbergen Institute. [Downloadable!]
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  4. Hendrik Bessembinder & Kalok Chan, 1998. "Market Efficiency and the Returns to Technical Analysis," Financial Management, Financial Management Association, vol. 27(2), Summer.
  5. Routledge, Bryan R., 2001. "Genetic Algorithm Learning To Choose And Use Information," Macroeconomic Dynamics, Cambridge University Press, vol. 5(02), pages 303-325, April. [Downloadable!]
  6. Dittmar, Robert & Neely, Christopher J & Weller, Paul, 1996. "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach," CEPR Discussion Papers 1480, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  7. 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. [Downloadable!] (restricted)
  8. 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.
  9. Franklin Allen & Risto Karjalainen, . "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.
  10. Brock, W. & Lakonishok, J. & Lebaron, B., 1991. "Simple Technical Trading Rules And The Stochastic Properties Of Stock Returns," Working papers 90-22, Wisconsin Madison - Social Systems.
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This page was last updated on 2009-11-8.


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