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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.

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Bibliographic Info

Paper provided by 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 in its series ERIM Report Series Research in Management with number ERS-2003-052-F&A.

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Date of creation: 19 Jun 2003
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Handle: RePEc:ems:eureri:435

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Keywords: exchange rate; technical trading rule;

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References

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  1. LeBaron, Blake, 1999. "Technical trading rule profitability and foreign exchange intervention," Journal of International Economics, Elsevier, vol. 49(1), pages 125-143, October.
  2. 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.
  3. Spyros Skouras, 2001. "Risk Neutral Forecasting," Computing in Economics and Finance 2001 50, Society for Computational Economics.
  4. 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.
  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. 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.
  7. S. Skouras, 2001. "Learning to profit with discrete investment rules," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 284-288.
  8. 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.
  9. Christopher J. Neely & Paul A. Weller & Robert Dittmar, 1997. "Is technical analysis in the foreign exchange market profitable? a genetic programming approach," Working Papers 1996-006, Federal Reserve Bank of St. Louis.
  10. 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.
  11. LeBaron, B., 1992. "Do Moving Average Trading Rule Results Imply Nonlinearites in Foreign Exchange Markets?," Working papers 9222, Wisconsin Madison - Social Systems.
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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. Massimo Guidolin & Daniel L. Thornton, 2010. "Predictions of short-term rates and the expectations hypothesis," Working Papers 2010-013, Federal Reserve Bank of St. Louis.

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