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Market Returns and Weak-Form Efficiency: the case of the Ghana Stock Exchange

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  • Frimpong, Joseph Magnus
  • Oteng-Abayie, Eric Fosu

Abstract

This paper examines the weak-form efficient market hypothesis (EMH) in the case of the Ghana Stock Exchange (GSE) an emerging market. Daily returns from the Databank Stock Index (DSI) over a 5-year period 1999-2004 were used for the exercise. Random walk (RW) and GARCH(1,1) models are used as the basis for our analysis. The GSE DSI returns series exhibit volatility clustering, an indication of inefficiency on the GSE. The weak-form efficient market (random walk) hypothesis was rejected for the GSE, meaning that the market is inefficient. The inefficient market has important implications for investors, both domestic and international. Knowledge of profitable arbitrage opportunities due to market predictability serves to attract investors to diversify from more efficient markets to invest on the GSE bourse to increase their returns.

Suggested Citation

  • Frimpong, Joseph Magnus & Oteng-Abayie, Eric Fosu, 2007. "Market Returns and Weak-Form Efficiency: the case of the Ghana Stock Exchange," MPRA Paper 7582, University Library of Munich, Germany, revised 09 Mar 2008.
    • Handle: RePEc:pra:mprapa:7582
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    References listed on IDEAS

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    1. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    2. Chris Brooks & Simon Burke, 2003. "Information criteria for GARCH model selection," The European Journal of Finance, Taylor & Francis Journals, vol. 9(6), pages 557-580.
    3. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    4. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
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    Cited by:

    1. Feyyaz Zeren & Filiz Konuk, 2013. "Testing The Random Walk Hypothesis For Emerging Markets: Evidence From Linear And Non-Linear Unit Root Tests," Romanian Economic Business Review, Romanian-American University, vol. 8(4), pages 61-71, december.
    2. 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.
    3. Gideon Boako & Maurice Omane-Adjepong & Joseph Magnus Frimpong, 2016. "Stock Returns and Exchange Rate Nexus in Ghana: A Bayesian Quantile Regression Approach," South African Journal of Economics, Economic Society of South Africa, vol. 84(1), pages 149-179, March.
    4. James Mark Gbeda & James Atta Peprah, 2018. "Day of the week effect and stock market volatility in Ghana and Nairobi stock exchanges," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(4), pages 727-745, October.

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    More about this item

    Keywords

    Ghana Stock Exchange; FINSAP; efficient market hypothesis; nonlinearity test;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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