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Illusory Profitability of Technical Analysis in Emerging Foreign Exchange Markets

We conduct an extensive examination of profitability of technical analysis in ten emerging foreign exchange markets. Studying 25988 trading strategies for emerging foreign exchange markets, we find that best rules can sometimes generate an annually mean excess return of more than 30%. Based on standard tests, we find hundreds to thousands of seemingly significant profitable strategies. Almost all these profits vanish once the data snooping bias is taken into account. Overall, we show that the profitability of technical analysis is illusory.

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Paper provided by Department of Economics, University of Birmingham in its series Discussion Papers with number 13-09.

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Length: 30 pages
Date of creation: Mar 2013
Date of revision:
Handle: RePEc:bir:birmec:13-09
Contact details of provider: Postal: Edgbaston, Birmingham, B15 2TT
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  1. Brock, W. & Lakonishok, J. & Lebaron, B., 1991. "Simple Technical Trading Rules And The Stochastic Properties Of Stock Returns," Working papers 90-22, Wisconsin Madison - Social Systems.
  2. Christopher J. Neely & Paul A. Weller & Joshua M. Ulrich, 2007. "The adaptive markets hypothesis: evidence from the foreign exchange market," Working Papers 2006-046, Federal Reserve Bank of St. Louis.
  3. Blake LeBaron, . "Technical Trading Rule Profitability and Foreign Exchange Intervention," Working papers _002, University of Wisconsin - Madison.
  4. Sweeney, Richard J, 1986. " Beating the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 41(1), pages 163-82, March.
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  6. Lo, Andrew W. (Andrew Wen-Chuan) & MacKinlay, Archie Craig, 1955-, 1989. "Data-snooping biases in tests of financial asset pricing models," Working papers 3020-89., Massachusetts Institute of Technology (MIT), Sloan School of Management.
  7. Joseph P. Romano & Michael Wolf, 2003. "Stepwise multiple testing as formalized data snooping," Economics Working Papers 712, Department of Economics and Business, Universitat Pompeu Fabra.
  8. Momtchil Pojarliev, 2005. "Performance of Currency Trading Strategies in Developed and Emerging Markets: Some Striking Differences," Financial Markets and Portfolio Management, Springer, vol. 19(3), pages 297-311, October.
  9. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
  10. Andrew Lo & Harry Mamaysky & Jiang Wang, 1999. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Computing in Economics and Finance 1999 402, Society for Computational Economics.
  11. Jensen, Michael C & Bennington, George A, 1970. "Random Walks and Technical Theories: Some Additional Evidence," Journal of Finance, American Finance Association, vol. 25(2), pages 469-82, May.
  12. Lee, Chun I & Gleason, Kimberly C. & Mathur, Ike, 2001. "Trading rule profits in Latin American currency spot rates," International Review of Financial Analysis, Elsevier, vol. 10(2), pages 135-156.
  13. 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.
  14. Martin Eichenbaum & Craig Burnside & Sergio Rebelo, 2007. "The Returns to Currency Speculation in Emerging Markets," American Economic Review, American Economic Association, vol. 97(2), pages 333-338, May.
  15. Oliver Ledoit & Michael Wolf, 2008. "Robust Performance Hypothesis Testing with the Sharpe Ratio," IEW - Working Papers 320, Institute for Empirical Research in Economics - University of Zurich.
  16. Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data-Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
  17. de Zwart, G.J. & Markwat, T.D. & Swinkels, L.A.P. & van Dijk, D.J.C., 2007. "The Economic Value of Fundamental and Technical Information in Emerging Currency Markets," ERIM Report Series Research in Management ERS-2007-096-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.
  18. Romano, Joseph P. & Shaikh, Azeem M. & Wolf, Michael, 2008. "Formalized Data Snooping Based On Generalized Error Rates," Econometric Theory, Cambridge University Press, vol. 24(02), pages 404-447, April.
  19. Chang, P H Kevin & Osler, Carol L, 1999. "Methodical Madness: Technical Analysis and the Irrationality of Exchange-Rate Forecasts," Economic Journal, Royal Economic Society, vol. 109(458), pages 636-61, October.
  20. Martin, Anna D., 2001. "Technical trading rules in the spot foreign exchange markets of developing countries," Journal of Multinational Financial Management, Elsevier, vol. 11(1), pages 59-68, February.
  21. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
  22. Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
  23. Po-Hsuan Hsu & Chung-Ming Kuan, 2005. "Reexamining the Profitability of Technical Analysis with Data Snooping Checks," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(4), pages 606-628.
  24. Hsu, Po-Hsuan & Hsu, Yu-Chin & Kuan, Chung-Ming, 2010. "Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 471-484, June.
  25. Lee, Chun I. & Mathur, Ike, 1996. "Trading rule profits in european currency spot cross-rates," Journal of Banking & Finance, Elsevier, vol. 20(5), pages 949-962, June.
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