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A Reality Check on Technical Trading Rule Profits in US Futures Markets

  • Park, Cheol-Ho
  • Irwin, Scott H.

This paper investigates the profitability of technical trading rules in US futures markets over the 1985-2004 period. To account for data snooping biases, we evaluate statistical significance of performance across technical trading rules using White's Bootstrap Reality Check test and Hansen's Superior Predictive Ability test. These methods directly quantify the effect of data snooping by testing the performance of the best rule in the context of the full universe of technical trading rules. Results show that the best rules generate statistically significant economic profits only for two of 17 futures contracts traded in the US. This evidence indicates that technical trading rules generally have not been profitable in US futures markets after correcting for data snooping biases.

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File URL: http://purl.umn.edu/19039
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Paper provided by NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management in its series 2005 Conference, April 18-19, 2005, St. Louis, Missouri with number 19039.

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Date of creation: 2005
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Handle: RePEc:ags:ncrfiv:19039
Contact details of provider: Web page: http://www.agebb.missouri.edu/ncrext/ncr134/

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  1. Cheung, Yin-Wong & Chinn, Menzie David, 2001. "Currency traders and exchange rate dynamics: a survey of the US market," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 439-471, August.
  2. De Long, J. Bradford & Shleifer, Andrei & Summers, Lawrence H. & Waldmann, Robert J., 1991. "The Survival of Noise Traders in Financial Markets," Scholarly Articles 3725470, Harvard University Department of Economics.
  3. Sullivan, Ryan & Timmermann, Allan & White, Halbert, 2003. "Forecast evaluation with shared data sets," International Journal of Forecasting, Elsevier, vol. 19(2), pages 217-227.
  4. Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February.
  5. 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.
  6. De Long, J Bradford, et al, 1990. " Positive Feedback Investment Strategies and Destabilizing Rational Speculation," Journal of Finance, American Finance Association, vol. 45(2), pages 379-95, June.
  7. Kidd, Willis V. & Brorsen, B. Wade, 2004. "Why have the returns to technical analysis decreased?," Journal of Economics and Business, Elsevier, vol. 56(3), pages 159-176.
  8. Lukac, Louis P & Brorsen, B Wade, 1990. "A Comprehensive Test of Futures Market Disequilibrium," The Financial Review, Eastern Finance Association, vol. 25(4), pages 593-622, November.
  9. Dale, Charles & Workman, Rosemarie, 1981. "Measuring patterns of price movements in the Treasury bill futures market," MPRA Paper 48639, University Library of Munich, Germany.
  10. Peter Hansen, 2003. "Asymptotic Tests of Composite Hypotheses," Working Papers 2003-09, Brown University, Department of Economics.
  11. 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.
  12. Timmermann, Allan & Granger, Clive W. J., 2004. "Efficient market hypothesis and forecasting," International Journal of Forecasting, Elsevier, vol. 20(1), pages 15-27.
  13. Park, Cheol-Ho & Irwin, Scott H., 2004. "The Profitability of Technical Analysis: A Review," AgMAS Project Research Reports 37487, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
  14. Denton, Frank T, 1985. "Data Mining as an Industry," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 124-27, February.
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