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Calendar Anomalies in an Emerging African Market: Evidence from the Ghana Stock Exchange

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Abstract

This paper investigates two calendar anomalies in an emerging African market. Both the day of the week and month of the year effects are examined for Ghana. The latter is an interesting case because i) it operates for only three days per week during the sample period and ii) the increased focus that African stock markets have received lately both from academics and practitioners. We employ rolling techniques to asses the affects of policy and institutional changes. This allows deviations from the linear paradigm. We finally employ non-linear models from the GARCH family in a rolling framework to investigate the role of asymmetries. Contrary to a January return pattern in most markets, an April effect is found for Ghana. The evidence also shows the presence of the day of the week effects with asymmetric volatility performing better than the benchmark linear estimates. This seasonality though disappears when only the latest information is used (time-varying asymmetric GARCH). Our approach provides a new framework for investigating this well-known puzzle in finance.

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  • Paul Alagidede & Theodore Panagiotidis, 2006. "Calendar Anomalies in an Emerging African Market: Evidence from the Ghana Stock Exchange," Discussion Paper Series 2006_13, Department of Economics, Loughborough University, revised Jun 2006.
    • Handle: RePEc:lbo:lbowps:2006_13
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    File URL: http://www.lboro.ac.uk/departments/ec/RePEc/lbo/lbowps/Ghana12062006.pdf
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    Cited by:

    1. Obalade Adefemi A. & Muzindutsi Paul-Francois, 2019. "Calendar Anomalies, Market Regimes, and the Adaptive Market Hypothesis in African Stock Markets," Journal of Management and Business Administration. Central Europe, Sciendo, vol. 27(4), pages 71-94, December.
    2. Carl H. Korkpoe & Peterson Owusu Junior, 2018. "Behaviour of Johannesburg Stock Exchange All Share Index Returns - An Asymmetric GARCH and News Impact Effects Approach," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 68(1), pages 26-42, January-M.
    3. Balaban, Ercan & Ozgen, Tolga & Karidis, Socrates, 2018. "Intraday and interday distribution of stock returns and their asymmetric conditional volatility: Firm-level evidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 905-915.
    4. Plastun, Alex & Sibande, Xolani & Gupta, Rangan & Wohar, Mark E., 2020. "Historical evolution of monthly anomalies in international stock markets," Research in International Business and Finance, Elsevier, vol. 52(C).
    5. Giovanis, Eleftherios, 2009. "Calendar Effects and Seasonality on Returns and Volatility," MPRA Paper 64404, University Library of Munich, Germany.
    6. Obalade Adefemi A. & Muzindutsi Paul-Francois, 2019. "The Adaptive Market Hypothesis and the Day-of-the-Week Effect in African Stock Markets: the Markov Switching Model," Comparative Economic Research, Sciendo, vol. 22(3), pages 145-162, September.
    7. 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.
    8. Frimpong, Joseph Magnus & Oteng-Abayie, Eric Fosu, 2006. "Modelling and Forecasting Volatility of Returns on the Ghana Stock Exchange Using GARCH Models," MPRA Paper 593, University Library of Munich, Germany, revised 07 Oct 2006.

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    More about this item

    Keywords

    Calendar Anomalies; Non-Linearity; Market Efficiency; Asymmetric Volatility; Rolling windows.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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