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Asset pricing and information efficiency of the Ghana Stock Market

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  • Kofi A. Osei

    (University of Ghana)

Abstract

The study looks at two main objectives, the asset pricing characteristics and the response to annual earnings announcements of the Ghana Stock Market (GSM). The study hypothesizes that the GSM, as a typical African emerging stock market, is not efficient with respect to annual earnings information releases to the market. The assessment of the market response to information is done by measuring abnormal returns over a 17-week event window when the annual earnings information is released. Analysis of cumulative abnormal returns (CAR) is also carried out. The study establishes that 13 out of the 16 stocks studied have systematic risk lower than the market risk. Three stocks have betas greater than the market beta of one. Five out of the 13 stocks with systematic risk lower than the market risk have negative betas. Their t-values are also not significant. There are considerable intra-industry differences in systematic risk values of the listed stocks. On the market response to earnings information, the analysis of CAR shows that the market learns about the impending annual earnings announcements. The market drifts up for good news and down for bad news over the period before the event announcement date. The study establishes that the market continues drifting up or down beyond the announcement week, i.e., week zero. This is inconsistent with the efficient market hypothesis (EMH). The conclusion is that the Ghana Stock Market is inefficient with respect to annual earnings information releases by the companies listed on the exchange

Suggested Citation

  • Kofi A. Osei, 2002. "Asset pricing and information efficiency of the Ghana Stock Market," Working Papers 115, African Economic Research Consortium, Research Department.
    • Handle: RePEc:aer:wpaper:115
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    Cited by:

    1. Isaac Quaye & Alfred Sarbah & Joseph Boadi Nyamaah & Mavis Aidoo & Yinping Mu, 2020. "Intra-Industry Information Transfers and Firm Value: Evidence From Ghana’s Banking Industry," SAGE Open, , vol. 10(4), pages 21582440209, November.
    2. 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.
    3. Edward A. E. Jones & Anthony K. Kyiu & Hao Li, 2021. "Earnings informativeness and trading frequency: Evidence from African markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1064-1086, January.
    4. Jean-François Casta & Alioune Badara Mbengue, 2016. "De la pertinence informationnelle des chiffres comptables publiés par les sociétés cotées sur les Bourses d'Afrique de l'Ouest (B.R.V.M et Ghana Stock Exchange)," Post-Print hal-01902539, HAL.
    5. Nageri Kamaldeen Ibraheem & Abdulkadir Rihanat Idowu, 2019. "Is the Nigerian Stock Market Efficient? Pre and Post 2007-2009 Meltdown Analysis," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 29(3), pages 38-63, September.
    6. Nageri Kamaldeen Ibraheem, 2020. "Ease of Doing Business and Capital Market Development in a Demand Following Hypothesis: Evidence from ECOWAS," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 30(4), pages 24-54, December.
    7. Alexander Ayertey Odonkor & Emmanuel Nkrumah Ababio & Emmanuel Amoah- Darkwah & Richard Andoh, 2022. "Stock Returns and Long-range Dependence," Global Business Review, International Management Institute, vol. 23(1), pages 37-47, February.

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