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Genetic Algorithms and Trading Strategies: New Evidences from Financially Interesting Time Series


  • Chueh-Inong Taso

    () (National Chengchi University)


In this paper, the performance of canonical GA-based trading strategies are evaluated under different time series. The time series considered include a variety of financial time series, ranging from linear and nonlinear stationary time series to chaotic time series. Unlike many existing applications of computational intelligence in financial engineering, for each performance criterion, we provide rigourous asymptotic statistical tests based on a Monte Carlo simulation. In addition, the criteria chosen are much more extensive than in the existing literature. These include the profit ratio, risk, the Sharpe ratio, maximum drawdown, and the luck coefficient. As a result, this study provides a thorough understanding of the effectiveness of canonical GAs for generating trading strategies under different financial time series.

Suggested Citation

  • Chueh-Inong Taso, 1999. "Genetic Algorithms and Trading Strategies: New Evidences from Financially Interesting Time Series," Computing in Economics and Finance 1999 552, Society for Computational Economics.
  • Handle: RePEc:sce:scecf9:552

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    References listed on IDEAS

    1. Tesfatsion, Leigh, 1998. "Preferential Partner Selection in Evolutionary Labor Markets: A Study in Agent-Based Computational Economics," Staff General Research Papers Archive 2048, Iowa State University, Department of Economics.
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    4. Roth, Alvin E. & Sotomayor, Marilda, 1992. "Two-sided matching," Handbook of Game Theory with Economic Applications,in: R.J. Aumann & S. Hart (ed.), Handbook of Game Theory with Economic Applications, edition 1, volume 1, chapter 16, pages 485-541 Elsevier.
    5. Olivier J. Blanchard & Lawrence H. Summers, 1986. "Hysteresis and the European Unemployment Problem," NBER Chapters,in: NBER Macroeconomics Annual 1986, Volume 1, pages 15-90 National Bureau of Economic Research, Inc.
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    7. Leigh TESFATSION, 1995. "How Economists Can Get Alife," Economic Report 37, Iowa State University Department of Economics.
    8. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, EconWPA, revised 15 Aug 2002.
    9. Diamond, Peter A, 1982. "Aggregate Demand Management in Search Equilibrium," Journal of Political Economy, University of Chicago Press, vol. 90(5), pages 881-894, October.
    10. Leigh TESFATSION, 1995. "A Trade Network Game With Endogenous Partner Selection," Economic Report 36, Iowa State University Department of Economics.
    11. Matthew Rabin & Joel L. Schrag, 1999. "First Impressions Matter: A Model of Confirmatory Bias," The Quarterly Journal of Economics, Oxford University Press, vol. 114(1), pages 37-82.
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