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Testing Weak Form Efficiency on the Toronto Stock Exchange

  • Vitali Alexeev

    ()

    (Department of Economics, University of Guelph, Canada.)

  • Francis Tapon

    ()

    (Department of Economics, University of Guelph, Canada.)

We believe that in order to test for weak form efficiency in the market a vast pool of individual stocks must be analyzed rather than a stock market index. In this paper, we use a model-based bootstrap to generate a series of simulated trials and apply a modified chart pattern recognition algorithm to all stocks listed on the Toronto Stock Exchange (TSX). We compare the number of patterns detected in the original price series with the number of patterns found in the simulated series. By simulating the price path we eliminate specific time dependencies present in real data, making price changes purely random. Patterns, if consistently identified, carry information which adds value to the investment process, however, this informativeness does not guarantee profitability. We draw conclusions on the relative efficiency of some sectors of the economy. Although, we fail to reject the null hypothesis of weak form efficiency on the TSX, some sectors of the Canadian economy appear to be less efficient than others. In addition, we find negative dependency of pattern frequencies on the two moments of return distributions, variance and kurtosis.

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Paper provided by University of Guelph, Department of Economics and Finance in its series Working Papers with number 1002.

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Length: 29 pages
Date of creation: 2010
Date of revision:
Handle: RePEc:gue:guelph:2010-02.
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Web page: https://www.uoguelph.ca/economics/

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  1. Russell Davidson & James MacKinnon, 2000. "Bootstrap tests: how many bootstraps?," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 55-68.
  2. 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.
  3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  4. 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.
  5. Kim, Tae-Hwan & White, Halbert, 2004. "On more robust estimation of skewness and kurtosis," Finance Research Letters, Elsevier, vol. 1(1), pages 56-73, March.
  6. 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.
  7. 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.
  8. Cheol-Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, 09.
  9. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
  10. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
  11. Edward R Dawson & James M. Steeley, 2003. "On the Existence of Visual Technical Patterns in the UK Stock Market," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 30(1-2), pages 263-293.
  12. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
  13. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1770, 08.
  14. Sanford J Grossman & Joseph E Stiglitz, 1997. "On the Impossibility of Informationally Efficient Markets," Levine's Working Paper Archive 1908, David K. Levine.
  15. Robert F. Engle & Victor K. Ng, 1991. "Measuring and Testing the Impact of News on Volatility," NBER Working Papers 3681, National Bureau of Economic Research, Inc.
  16. Blume, Lawrence & Easley, David & O'Hara, Maureen, 1994. " Market Statistics and Technical Analysis: The Role of Volume," Journal of Finance, American Finance Association, vol. 49(1), pages 153-81, March.
  17. Lui, Yu-Hon & Mole, David, 1998. "The use of fundamental and technical analyses by foreign exchange dealers: Hong Kong evidence," Journal of International Money and Finance, Elsevier, vol. 17(3), pages 535-545, June.
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