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Does Automation Improve Stock Market Efficiency? Evidence from Ghana

Author

Listed:
  • Mensah, Justice T.
  • Pomaa-Berko, Maame
  • Adom, Philip Kofi

Abstract

As a burgeoning capital market in an emerging economy, automation of the stock market is regarded as a major step towards integrating the financial market as a conduit for economic growth. The automation of the Ghana Stock Exchange (GSE) in 2008 is expected among other things to improve the efficiency of the market. This paper therefore investigates the impact of the automation on the efficiency of the GSE within the framework of the weak-form Efficient Market Hypothesis (EMH) using daily market returns from the Ghana Stock Exchange All-Share index from 2006 to 2011. The Unit Root Random Walk and the GARCH models were used to analyze the efficiency of the GSE in the pre and post automation sample periods. Results show that the GSE was weakly inefficient in both pre and post automation periods, suggesting that the automation of the GSE have not yielded the needed impact towards improving the efficiency of the exchange.

Suggested Citation

  • 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.
  • Handle: RePEc:pra:mprapa:43642
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    File URL: https://mpra.ub.uni-muenchen.de/43642/1/MPRA_paper_43642.pdf
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    References listed on IDEAS

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    1. Sharma, J. L. & Kennedy, Robert E., 1977. "A Comparative Analysis of Stock Price Behavior on the Bombay, London, and New York Stock Exchanges," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(03), pages 391-413, September.
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    3. M. Magnusson & B. Wydick, 2002. "How Efficient are Africa's Emerging Stock Markets?," Journal of Development Studies, Taylor & Francis Journals, vol. 38(4), pages 141-156.
    4. Graham Smith & Keith Jefferis & Hyun-Jung Ryoo, 2002. "African stock markets: multiple variance ratio tests of random walks," Applied Financial Economics, Taylor & Francis Journals, vol. 12(7), pages 475-484.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. Maria Rosa Borges, 2010. "Efficient market hypothesis in European stock markets," The European Journal of Finance, Taylor & Francis Journals, pages 711-726.
    7. Appiah-Kusi, Joe & Menyah, Kojo, 2003. "Return predictability in African stock markets," Review of Financial Economics, Elsevier, vol. 12(3), pages 247-270.
    8. Poterba, James M. & Summers, Lawrence H., 1988. "Mean reversion in stock prices : Evidence and Implications," Journal of Financial Economics, Elsevier, vol. 22(1), pages 27-59, October.
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    Cited by:

    1. E.O. Marfo & L. Chen & H. Xuhua & H.A. Antwi & E. Yiranbon, 2015. "Corporate Social Responsibility: Driving Dynamics on Firm’s Profitability in Ghana," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 5(3), pages 116-132, July.

    More about this item

    Keywords

    Stock; efficiency; automation; Ghana;

    JEL classification:

    • E0 - Macroeconomics and Monetary Economics - - General
    • A1 - General Economics and Teaching - - General Economics
    • G0 - Financial Economics - - General

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