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Are trading rules based on genetic algorithms profitable?

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  • Mariano Matilla-Garcia

Abstract

In this letter the profitability of a simple trading rule based upon genetic algorithms has been investigated. The referred technical trading rule has been contrasted in four different sample periods of the Spanish stock market index known as IBEX-35. Results suggest that in general the profitability of the simple trading rule is superior to the buy-and-hold strategy. This conclusion is clearer in 'bull', 'bear' and 'volatile' market episodes. These results can be compared with those that apply artificial neural networks as simple trading strategies to the general index of Madrid.

Suggested Citation

  • Mariano Matilla-Garcia, 2006. "Are trading rules based on genetic algorithms profitable?," Applied Economics Letters, Taylor & Francis Journals, vol. 13(2), pages 123-126.
    • Handle: RePEc:taf:apeclt:v:13:y:2006:i:2:p:123-126
    DOI: 10.1080/13504850500392321
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    References listed on IDEAS

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    1. Fernando Fernandez-Rodriguez & Simon Sosvilla-Rivero & Maria Dolores Garcia-Artiles, 1997. "Using nearest neighbour predictors to forecast the Spanish stock market," Investigaciones Economicas, Fundación SEPI, vol. 21(1), pages 75-91, January.
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    3. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    4. Fernandez-Rodriguez, Fernando & Gonzalez-Martel, Christian & Sosvilla-Rivero, Simon, 2000. "On the profitability of technical trading rules based on artificial neural networks:: Evidence from the Madrid stock market," Economics Letters, Elsevier, vol. 69(1), pages 89-94, October.
    5. Farley, Arthur M & Jones, Samuel, 1994. "Using a Genetic Algorithm to Determine an Index of Leading Economic Indicators," Computational Economics, Springer;Society for Computational Economics, vol. 7(3), pages 163-173.
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    7. Dorsey, Robert E & Mayer, Walter J, 1995. "Genetic Algorithms for Estimation Problems with Multiple Optima, Nondifferentiability, and Other Irregular Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 53-66, January.
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    Cited by:

    1. Yu-Lieh Huang, 2009. "Identifying turbulent and calm regimes in stock prices: evidence from the Taiwan stock market," Applied Economics Letters, Taylor & Francis Journals, vol. 16(14), pages 1477-1481.
    2. Sylvie Geisendorf, 2011. "Internal selection and market selection in economic Genetic Algorithms," Journal of Evolutionary Economics, Springer, vol. 21(5), pages 817-841, December.
    3. Metghalchi, Massoud & Chen, Chien-Ping & Hayes, Linda A., 2015. "History of share prices and market efficiency of the Madrid general stock index," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 178-184.

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