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Technical Trading Rules and the Size of the Risk Premium in Security Returns

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Author Info
Ramazan Gencay (University of Windsor)
Thanasis Stengos (University of Guelph)

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Abstract

Among analysts, technical trading rules are widely used for forecasting security returns. Recent literature provides evidence that these rules may provide positive profits after accounting for transaction costs. This would be contrary to the theory of the efficient market hypothesis which states that security prices cannot be forecasted from their past values or other past variables. This paper uses the daily Dow Jones Industrial Average Index from 1963 to 1988 to examine the linear and nonlinear predictability of stock market returns with simple technical trading rules, by using the nearest neighbors and the feedforward network regressions. Evidence of nonlinear predictability is found in the stock market returns by using the past returns and the buy and sell signals of the moving average rules.

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Publisher Info
Article provided by Berkeley Electronic Press in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 2 (1997)
Issue (Month): 2 ()
Pages: 23-34
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Handle: RePEc:bep:sndecm:2:1997:2:23-34

Note: oai:bepress:snde-1026
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Related research
Keywords: market efficiency technical trading rules feedforward networks

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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.:
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  2. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May. [Downloadable!] (restricted)
  3. Jensen, Michael C., 1978. "Some anomalous evidence regarding market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 95-101. [Downloadable!] (restricted)
  4. Kurt Hornik & Maxwell Stinchcombe & Halbert White, 1990. "Universal Approximation of an Unknown Mapping And Its Derivatives Using Multilayer Feedforward Networks," University of California at San Diego, Economics Working Paper Series 89-36r, Department of Economics, UC San Diego.
  5. Jegadeesh, Narasimhan, 1990. " Evidence of Predictable Behavior of Security Returns," Journal of Finance, American Finance Association, vol. 45(3), pages 881-98, July. [Downloadable!] (restricted)
  6. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March. [Downloadable!] (restricted)
  7. Chong, Yock Y & Hendry, David F, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Blackwell Publishing, vol. 53(4), pages 671-90, August. [Downloadable!] (restricted)
  8. Poterba, James M. & Summers, Lawrence H., 1988. "Mean reversion in stock prices : Evidence and Implications," Journal of Financial Economics, Elsevier, vol. 22(1), pages 27-59, October. [Downloadable!] (restricted)
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  9. Lo, Andrew W & MacKinlay, A Craig, 1990. "When Are Contrarian Profits Due to Stock Market Overreaction?," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 3(2), pages 175-205. [Downloadable!] (restricted)
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  10. Cutler, David M & Poterba, James M & Summers, Lawrence H, 1991. "Speculative Dynamics," Review of Economic Studies, Blackwell Publishing, vol. 58(3), pages 529-46, May. [Downloadable!] (restricted)
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  11. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 1(1), pages 41-66. [Downloadable!] (restricted)
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  12. 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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  13. Conrad, Jennifer & Kaul, Gautam, 1988. "Time-Variation in Expected Returns," Journal of Business, University of Chicago Press, vol. 61(4), pages 409-25, October. [Downloadable!] (restricted)
  14. Lehmann, Bruce N, 1990. "Fads, Martingales, and Market Efficiency," The Quarterly Journal of Economics, MIT Press, vol. 105(1), pages 1-28, February. [Downloadable!] (restricted)
  15. Bruce Mizrach, 1996. "Forecast Comparison in L2," Departmental Working Papers 199524, Rutgers University, Department of Economics. [Downloadable!]
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  17. De Bondt, Werner F M & Thaler, Richard, 1985. " Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July. [Downloadable!] (restricted)
  18. Fama, Eugene F, 1991. " Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-617, December. [Downloadable!] (restricted)
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  20. Bruce N. Lehmann, 1990. "Fads, Martingales, and Market Efficiency," NBER Working Papers 2533, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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Cited by:
(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. Mariano Matilla-García & Carlos Argüello, 2005. "A hybrid approach based on neural networks and genetic algorithms to the study of profitability in the Spanish Stock Market," Applied Economics Letters, Taylor and Francis Journals, vol. 12(5), pages 303-308, April. [Downloadable!] (restricted)
  2. Christopher J. Neely, 2001. "Risk-adjusted, ex ante, optimal technical trading rules in equity markets," Working Papers 1999-015, Federal Reserve Bank of St. Louis. [Downloadable!]
    Other versions:
  3. Yochanan Shachmurove & Uri BenZion & Paul Klein & Joseph Yagil, 2001. "A Moving Average Comparison of the Tel-Aviv 25 and S&P 500 Stock Indices," Penn CARESS Working Papers 4731f3394c43bebf4d3191c81, UCLA Department of Economics. [Downloadable!]
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