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Success and Failure of Technical Trading Strategies in the Cocoa Futures Market

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Listed:
  • Peter Boswijk

    (University of Amsterdam)

  • Gerwin Griffioen

    (University of Amsterdam)

  • Cars Hommes

    (University of Amsterdam)

Abstract

A large set of 5350 trend following technica! trading rules is applied to LIFFEand CSCE cocoa futures prices, and tothe Pound-Dollar exchange rate, in the period 1983:1-1997:6. We find that 72% ofthe trading rules generatespositive profits, even when correcting for transaction and borrowing costs, whenapplied to the LIFFE cocoa futuresprices. Moreover, a large set of trading rules exhibits statisticallysignificant forecasting power of the LIFFE cocoafutures series. On the other hand the same set of strategies performs poor onthe CSCE cocoa futures prices, withonly 18% generating positive net profits and hardly any statisticallysignificant forecasting power. The largedifference in the performance of technical trading may be attributed to acombination of the demand/supplymechanism in the cocoa market and an accident al influence of the Pound- Dollarexchange rate, reinforcing trendsin the LIFFE cocoa futures but weakening trends in the CSCE cocoa futures. Ourcase-study suggests a connectionbetween the succes or failure of technical trading and the relative magnitudes of trend and volatility of the underlying series. See also chapter 3 'Success and failure of technical analysis in the cocoa futures market' in (C. Kyrtsou & C. Vorlow (Eds.)), Progress in financial markets research (Financial institutions and services) (pp. 25-70). New York: Nova Science, 2012.

Suggested Citation

  • Peter Boswijk & Gerwin Griffioen & Cars Hommes, 2001. "Success and Failure of Technical Trading Strategies in the Cocoa Futures Market," Tinbergen Institute Discussion Papers 01-016/1, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20010016
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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. He, Xue-Zhong & Zheng, Min, 2010. "Dynamics of moving average rules in a continuous-time financial market model," Journal of Economic Behavior & Organization, Elsevier, vol. 76(3), pages 615-634, December.
    3. Guanqing Liu, 2019. "Technical Trading Behaviour: Evidence from Chinese Rebar Futures Market," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 669-704, August.
    4. 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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