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Market Efficiency in Specialist Markets Before and After Automation

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  • Freund, William C
  • Pagano, Michael S

Abstract

Using nonparametric statistical analysis, we measure the degree of market efficiency before and after automation at the New York and Toronto Stock Exchanges. Overall, the results show that the level of informational efficiency remains effectively unchanged during the automation period. Despite several deviations from a random walk process, the returns for stocks on these exchanges do not appear to exhibit consistent patterns that investors can exploit to generate abnormal returns. Automation also coincides with an improvement in market efficiency at the Toronto Stock Exchange when compared to the New York Stock Exchange. Copyright 2000 by MIT Press.

Suggested Citation

  • Freund, William C & Pagano, Michael S, 2000. "Market Efficiency in Specialist Markets Before and After Automation," The Financial Review, Eastern Finance Association, vol. 35(3), pages 79-104, August.
  • Handle: RePEc:bla:finrev:v:35:y:2000:i:3:p:79-104
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    Cited by:

    1. Mensah, Justice T. & Pomaa-Berko, Maame & Adom, Philip Kofi, 2012. "Does Automation Improve Stock Market Efficiency? Evidence from Ghana," MPRA Paper 43642, University Library of Munich, Germany.
    2. Aktham Maghyereh, 2005. "Electronic Trading and Market Efficiency in an Emerging Market: The Case of the Jordanian Capital Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 41(4), pages 5-19, August.
    3. Assaf, Ata, 2006. "The stochastic volatility in mean model and automation: Evidence from TSE," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(2), pages 241-253, May.
    4. Aktham Maghyereh, 2005. "Electronic Trading and Market Efficiency in an Emerging Market: The Case of the Jordanian Capital Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 41(4), pages 5-19, August.
    5. Liao, Huei-Chu & Lee, Yi-Huey & Suen, Yu-Bo, 2008. "Electronic trading system and returns volatility in the oil futures market," Energy Economics, Elsevier, vol. 30(5), pages 2636-2644, September.

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