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Succes and Failure of Technical Trading Strategies in the Cocoa Futures Markets


  • Boswijk, H.P.

    () (Universiteit van Amsterdam)

  • Griffioen, G.A.W.
  • Hommes, C.H.

    () (Universiteit van Amsterdam)


A large set of 5350 trend following technical trading rules is applied to LIFFE and CSCE cocoa futures prices, and to the Pound-Dollar exchange rate, in the period 1983:1 - 1997:6. We find that 72% of the trading rules generates positive profits, even when correcting for transaction and borrowing costs, when applied to the LIFFE cocoa futures prices. Moreover, a large set of trading rules exhibits statistically significant forecasting power of the LIFFE cocoa futures series. On the other hand the same set of strategies performs poor on the CSCE cocoa futures prices, with only 18% generating positive net profits and hardly any statistically significant forecasting power. The large difference in the performance of technical trading may be attributed to a combination of the demand/supply mechanism in the cocoa market and an accidental influence of the Pound-Dollar exchange rate, reinforcing trends in the LIFFE cocoa futures but weakening trends in the CSCE cocoa futures. Our case-study suggests a connection between the succes and failure of technical trading and the relative magnitudes of trend and volatility of the underlying series.

Suggested Citation

  • Boswijk, H.P. & Griffioen, G.A.W. & Hommes, C.H., 2000. "Succes and Failure of Technical Trading Strategies in the Cocoa Futures Markets," CeNDEF Working Papers 00-06, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  • Handle: RePEc:ams:ndfwpp:00-06

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    References listed on IDEAS

    1. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    2. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    4. 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.
    5. Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
    6. Hiemstra, Craig & Jones, Jonathan D, 1994. " Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
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    Cited by:

    1. Chiarella, Carl & He, Xue-Zhong & Hommes, Cars, 2006. "A dynamic analysis of moving average rules," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1729-1753.
    2. Colin Fyfe & John Paul Marney & Heather Tarbert, 2005. "Risk adjusted returns from technical trading: a genetic programming approach," Applied Financial Economics, Taylor & Francis Journals, vol. 15(15), pages 1073-1077.

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    Technical trading strategies; commodity futures; exchange rate.;

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