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Risk-adjusted, ex ante, optimal technical trading rules in equity markets

  • Christopher J. Neely

Allen and Karjalainen (1999) used genetic programming to develop optimal ex ante trading rules for the S&P 500 index. They found no evidence that the returns to these rules were higher than buy-and-hold returns but some evidence that the rules had predictive ability. This comment investigates the risk-adjusted usefulness of such rules and more fully characterizes their predictive content. These results extend Allen and Karjalainen's (1999) conclusion by showing that although the rules' relative performance improves, there is no evidence that the rules significantly outperform the buy-and-hold strategy on a risk-adjusted basis. Therefore, the results are consistent with market efficiency. Nevertheless, risk-adjustment techniques should be seriously considered when evaluating trading strategies.

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Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 1999-015.

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Date of creation: 2001
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Publication status: Published in International Review of Economics and Finance, Spring 2003, 12(1), pp. 69-87
Handle: RePEc:fip:fedlwp:1999-015
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  1. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules," Journal of Financial Economics, Elsevier, vol. 51(2), pages 245-271, February.
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  17. Dacorogna, Michel M. & Gençay, Ramazan & Müller, Ulrich A. & Pictet, Olivier V., 2001. "Effective return, risk aversion and drawdowns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(1), pages 229-248.
  18. Sweeney, Richard J., 1988. "Some New Filter Rule Tests: Methods and Results," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 23(03), pages 285-300, September.
  19. Sullivan, Ryan & Timmermann, Allan G & White, Halbert, 1998. "Data-Snooping, Technical Trading Rule Performance and the Bootstrap," CEPR Discussion Papers 1976, C.E.P.R. Discussion Papers.
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