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Modelling long memory in volatility in sub-Saharan African equity markets

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  • Kuttu, Saint

Abstract

This study examines the long memory properties in the second moments of the return series in the equity markets of Ghana, Kenya, Nigeria and South Africa. Using 5219 daily observations of thin-trading adjusted total equity market return data, we find the presence of long-range dependency in the second moments of the return innovations in all the four countries’ equity markets in the full sample. To isolate spurious long memory, we perform structural breaks analysis to guide us in splitting the data for further examination. We find that all the four countries exhibited two structural breaks each during the sample period, and long memory identified in these two markets were not influenced by the structural breaks. This finding may have an influence on portfolio diversification and risk management. The long memory characteristics in the conditional volatility may also provide useful information to market participants in pricing long-term derivative contracts.

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  • Kuttu, Saint, 2018. "Modelling long memory in volatility in sub-Saharan African equity markets," Research in International Business and Finance, Elsevier, vol. 44(C), pages 176-185.
    • Handle: RePEc:eee:riibaf:v:44:y:2018:i:c:p:176-185
    DOI: 10.1016/j.ribaf.2017.07.073
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    More about this item

    Keywords

    Long memory; Thin-trading; FIEGARCH; Sub-Sahara African equity markets; Structural breaks;
    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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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