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Market efficiency before and after the introduction of electronic trading at the Toronto stock exchange

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  • William C. Freund
  • Maurice Larrain
  • Michael S. Pagano

Abstract

The trend toward automation of the trading activity on stock exchanges has spread around the world in recent years. Using rescaled range analysis, we test the effect of automation at the TSE on the market's efficiency using daily and monthly return data. Significant departures from a random walk model were found for selected individual stocks in the daily data. However, monthly returns of various stock indexes were more closely described by a random walk process. Differences in the daily and monthly data may be attributable to the effects of aggregation and indexation on return data. In addition, several simple ‘technical’ trading strategies were compared with a ‘buy and hold’ strategy using daily data for 25 stocks. Despite the presence of non‐random patterns in the return data, the technical trading rules could not exploit this information to out‐perform the buy and hold strategy. Thus, the presence of deviations from a random walk do not necessarily translate into abnormal performance. Overall, the results suggest automation did not significantly alter the degree of market efficiency at the TSE.

Suggested Citation

  • William C. Freund & Maurice Larrain & Michael S. Pagano, 1997. "Market efficiency before and after the introduction of electronic trading at the Toronto stock exchange," Review of Financial Economics, John Wiley & Sons, vol. 6(1), pages 29-56.
    • Handle: RePEc:wly:revfec:v:6:y:1997:i:1:p:29-56
    DOI: 10.1016/S1058-3300(97)90013-6
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    References listed on IDEAS

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    1. Hsieh, David A, 1991. "Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    2. 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.
    3. Scheinkman, Jose A & LeBaron, Blake, 1989. "Nonlinear Dynamics and Stock Returns," The Journal of Business, University of Chicago Press, vol. 62(3), pages 311-337, July.
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    Cited by:

    1. Chung I Lu & Julian Sester, 2024. "Generative model for financial time series trained with MMD using a signature kernel," Papers 2407.19848, arXiv.org, revised Dec 2024.
    2. Adamolekun, Gbenga & Sakariyahu, Rilwan & Lawal, Rodiat & Ahmed, Ammar, 2023. "Electronic trading and stock market participation in Africa: Does technology induce participation?," Economics Letters, Elsevier, vol. 224(C).

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