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

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Author Info
Christopher J. Neely

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Abstract

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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Related research
Keywords: Trade ; Stock - Prices ; Econometric models;

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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. William N. Goetzmann & Stephen J. Brown & 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. [Downloadable!]
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  2. Jensen, Michael C., 1978. "Some anomalous evidence regarding market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 95-101. [Downloadable!] (restricted)
  3. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules1," Journal of Financial Economics, Elsevier, vol. 51(2), pages 245-271, February. [Downloadable!] (restricted)
  4. Hendrik Bessembinder & Kalok Chan, 1998. "Market Efficiency and the Returns to Technical Analysis," Financial Management, Financial Management Association, vol. 27(2), Summer.
  5. Gencay, Ramazan, 1998. "The predictability of security returns with simple technical trading rules," Journal of Empirical Finance, Elsevier, vol. 5(4), pages 347-359, October. [Downloadable!] (restricted)
  6. Cumby, Robert E. & Modest, David M., 1987. "Testing for market timing ability : A framework for forecast evaluation," Journal of Financial Economics, Elsevier, vol. 19(1), pages 169-189, September. [Downloadable!] (restricted)
  7. Ramazan Gencay & Thanasis Stengos, 1997. "Technical Trading Rules and the Size of the Risk Premium in Security Returns," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 2(2). [Downloadable!]
  8. Mark J Ready, 2002. "Profits from Technical Trading Rules," Financial Management, Financial Management Association, vol. 31(3), Fall.
  9. 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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  10. Allan Timmermann & Halbert White & Ryan Sullivan, 1998. "Data-Snooping, Technical Trading, Rule Performance and the Bootstrap," FMG Discussion Papers dp303, Financial Markets Group. [Downloadable!] (restricted)
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  11. Neely, Christopher J. & Weller, Paul A., 1999. "Technical trading rules in the European Monetary System," Journal of International Money and Finance, Elsevier, vol. 18(3), pages 429-458. [Downloadable!] (restricted)
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  12. Gencay, Ramazan, 1998. "Optimization of technical trading strategies and the profitability in security markets," Economics Letters, Elsevier, vol. 59(2), pages 249-254, May. [Downloadable!] (restricted)
  13. 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 1731-64, December. [Downloadable!] (restricted)
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  14. 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)
  15. Christopher Neely & Paul Weller, 2000. "Technical analysis and central bank intervention," Working Papers 1997-002, Federal Reserve Bank of St. Louis. [Downloadable!]
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  16. Philippe Jorion & William N. Goetzmann, 1999. "Global Stock Markets in the Twentieth Century," Journal of Finance, American Finance Association, vol. 54(3), pages 953-980, 06. [Downloadable!] (restricted)
  17. William F. Sharpe, 1965. "Mutual Fund Performance," Journal of Business, University of Chicago Press, vol. 39, pages 119. [Downloadable!]
  18. Dowd, Kevin, 2000. "Adjusting for risk:: An improved Sharpe ratio," International Review of Economics & Finance, Elsevier, vol. 9(3), pages 209-222, July. [Downloadable!] (restricted)
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(explanations, 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. Christopher J. Neely & Paul A. Weller, 2001. "Predicting exchange rate volatility: genetic programming vs. GARCH and RiskMetrics," Working Papers 2001-009, Federal Reserve Bank of St. Louis. [Downloadable!]
  2. GIOT, Pierre & PETITJEAN, Mikael, 2006. "International stock return predictability: statistical evidence and economic significance," CORE Discussion Papers 2006088, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
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