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The Cost of Technical Trading Rules in the Forex Market: A Utility-based Evaluation

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  • Dewachter, H.D.R.
  • Lyrio, M.

Abstract

We compute the opportunity cost for rational risk averse agents of using technical trading rules in the foreign exchange rate market. Our purpose is to investigate whether these rules can be interpreted as near-rational investment strategies for rational investors. We analyze four di.erent exchange rates and find that the opportunity cost of using chartist rules tends to be prohibitively high. We also present a method to decompose this opportunity cost into parts related to investor's irrationality and misallocation of wealth. The results show that irrationality of chartist beliefs is an important component of the total opportunity cost of using technical trading rules.

Suggested Citation

  • Dewachter, H.D.R. & Lyrio, M., 2003. "The Cost of Technical Trading Rules in the Forex Market: A Utility-based Evaluation," ERIM Report Series Research in Management ERS-2003-052-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    • Handle: RePEc:ems:eureri:435
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    References listed on IDEAS

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    1. Neely, Christopher & Weller, Paul & Dittmar, Rob, 1997. "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(4), pages 405-426, December.
    2. LeBaron, Blake, 1999. "Technical trading rule profitability and foreign exchange intervention," Journal of International Economics, Elsevier, vol. 49(1), pages 125-143, October.
    3. Skouras, S., 1998. "Risk Neutral Forecasting," Economics Working Papers eco98/40, European University Institute.
    4. Michael W. Brandt, 1999. "Estimating Portfolio and Consumption Choice: A Conditional Euler Equations Approach," Journal of Finance, American Finance Association, vol. 54(5), pages 1609-1645, October.
    5. Hans Dewachter & Marco Lyrio, 2005. "The economic value of technical trading rules: a nonparametric utility-based approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 10(1), pages 41-62.
    6. LeBaron, B., 1992. "Do Moving Average Trading Rule Results Imply Nonlinearites in Foreign Exchange Markets?," Working papers 9222, Wisconsin Madison - Social Systems.
    7. Skouras, Spyros, 2001. "Financial returns and efficiency as seen by an artificial technical analyst," Journal of Economic Dynamics and Control, Elsevier, vol. 25(1-2), pages 213-244, January.
    8. S. Skouras, 2001. "Learning to profit with discrete investment rules," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 284-288.
    9. Blake LeBaron, "undated". "Do Moving Average Trading Rule Results Imply Nonlinearities in Foreign Exchange?," Working papers _005, University of Wisconsin - Madison.
    10. Gencay, Ramazan, 1999. "Linear, non-linear and essential foreign exchange rate prediction with simple technical trading rules," Journal of International Economics, Elsevier, vol. 47(1), pages 91-107, February.
    11. 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.
    12. Dewachter, Hans, 2001. "Can Markov switching models replicate chartist profits in the foreign exchange market?," Journal of International Money and Finance, Elsevier, vol. 20(1), pages 25-41, February.
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    Cited by:

    1. Narayan, Paresh Kumar & Narayan, Seema & Sharma, Susan Sunila, 2013. "An analysis of commodity markets: What gain for investors?," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3878-3889.
    2. Huisman, R. & Huurman, C., 2003. "Fat Tails in Power Prices," ERIM Report Series Research in Management ERS-2003-059-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Guidolin, Massimo & Thornton, Daniel L., 2018. "Predictions of short-term rates and the expectations hypothesis," International Journal of Forecasting, Elsevier, vol. 34(4), pages 636-664.
    4. Yung-Ho Chang, 2019. "Cross-market information spillover and the performance of technical trading in the foreign exchange market," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(2), pages 211-227, April.

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    More about this item

    Keywords

    exchange rate; technical trading rule;

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G3 - Financial Economics - - Corporate Finance and Governance
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

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