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An Empirical Evaluation of Non-Linear Trading Rules

Author

Listed:
  • Andrada-Félix Julián

    (University of Las Palmas de Gran Canaria. Spain)

  • Fernadez-Rodriguez Fernando

    (Universidad de Las Palmas de Gran Canaria, Spain)

  • Garcia-Artiles Maria-Dolores

    (Universidad de Las Palmas de Gran canaria, Spain)

  • Sosvilla-Rivero Simon

    (FEDEA)

Abstract

In this paper we investigate the profitability of non-linear trading rules based on nearest neighbour (NN) predictors. Applying this investment strategy to the New York Stock Exchange for the 1997-2002 period, our results suggest that, taking into account transaction costs, the NN-based trading rule is superior to both a risk-adjusted buy-and-hold strategy and a linear ARIMA-based strategy in terms of returns for all of the years studied, except for 2000 and 2001. In addition, the NN-based trading rule produces higher net returns than those from a simple buy-and-hold strategy, except for 1997. Regarding other profitability measures, the NN-based trading rule yields higher Sharpe ratios than the ARIMA-based strategy for all of the years in the sample except for 2001. As for 2001, in 36 out of the 101 cases considered, the ARIMA-based strategy gives higher Sharpe ratios than those from the NN-trading rule, in 18 cases the opposite is true, and in the remaining 36 cases both strategies yield the same ratios.

Suggested Citation

  • Andrada-Félix Julián & Fernadez-Rodriguez Fernando & Garcia-Artiles Maria-Dolores & Sosvilla-Rivero Simon, 2003. "An Empirical Evaluation of Non-Linear Trading Rules," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(3), pages 1-32, October.
    • Handle: RePEc:bpj:sndecm:v:7:y:2003:i:3:n:4
    DOI: 10.2202/1558-3708.1160
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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.
    2. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    3. 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.
    4. Hardle, Wolfgang & Linton, Oliver, 1986. "Applied nonparametric methods," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 38, pages 2295-2339, Elsevier.
    5. Scheinkman, Jose A & LeBaron, Blake, 1989. "Nonlinear Dynamics and Stock Returns," The Journal of Business, University of Chicago Press, vol. 62(3), pages 311-337, July.
    6. William C. Clyde & Carol L. Osler, 1997. "Charting: Chaos theory in disguise?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 17(5), pages 489-514, August.
    7. Hsieh, David A, 1991. "Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    8. Pesaran, M Hashem & Timmermann, Allan, 2000. "A Recursive Modelling Approach to Predicting UK Stock Returns," Economic Journal, Royal Economic Society, vol. 110(460), pages 159-191, January.
    9. Pesaran, M Hashem & Timmermann, Allan, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-1228, September.
    10. Fernandez-Rodriguez, Fernando & Sosvilla-Rivero, Simon & Andrada-Felix, Julian, 1999. "Exchange-rate forecasts with simultaneous nearest-neighbour methods: evidence from the EMS," International Journal of Forecasting, Elsevier, vol. 15(4), pages 383-392, October.
    11. Engle, R. F. & Granger, C. W. J. (ed.), 1991. "Long-Run Economic Relationships: Readings in Cointegration," OUP Catalogue, Oxford University Press, number 9780198283393.
    12. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
    13. 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.
    14. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
    15. Sweeney, Richard J., 1988. "Some New Filter Rule Tests: Methods and Results," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 23(3), pages 285-300, September.
    16. 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 1731-1764, December.
    17. F. FernAndez-RodrIguez & S. Sosvilla-Rivero & J. Andrada-FElix, 2003. "Technical analysis in foreign exchange markets: evidence from the EMS," Applied Financial Economics, Taylor & Francis Journals, vol. 13(2), pages 113-122.
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    2. Kian-Ping Lim & Muzafar Shah Habibullah & Melvin J. Hinich, 2009. "The Weak-form Efficiency of Chinese Stock Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 8(2), pages 133-163, May.
    3. Terence Tai-Leung Chong & Sheung Tat Chan, 2008. "Structural Change in the Efficiency of the Japanese Stock Market after the Millennium," Economics Bulletin, AccessEcon, vol. 7(7), pages 1-7.
    4. Chong, Terence Tai-Leung & Lam, Tau-Hing & Yan, Isabel Kit-Ming, 2012. "Is the Chinese stock market really inefficient?," China Economic Review, Elsevier, vol. 23(1), pages 122-137.
    5. repec:ebl:ecbull:v:7:y:2008:i:7:p:1-7 is not listed on IDEAS
    6. Hanias, M.P. & Tombras, G.S., 2009. "Time series cross prediction in a single transistor chaotic circuit," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1167-1173.

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