IIARD International Institute of Academic Research and Development

WORLD JOURNAL OF FINANCE AND INVESTMENT RESEARCH (WJFIR )

E-ISSN 2550-7125
P-ISSN 2682-5902
VOL. 7 NO. 3 2023
DOI: https://doi.org/10.56201/wjfir.v7.no3.2023.pg16.30

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Parameterization of Asymmetric News Effect and African Stock Market Returns Volatility Within EGARCH Framework

Ejem, Chukwu Agwu, PhD

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Abstract

This study on parameterization of asymmetric news effect and African stock market returns volatility within EGARCH Framework engaged 15 stock exchanges. After, the analysis it was found that the asymmetric parameter for the countries under study except Cote D’Ivoire, Nigeria and Tunisia confirm that bad news create more volatility than good news of the same magnitude, corroborating with the leverage effect theory that opined that bad news create more volatility than good news of the same magnitude. Magnitude effect (volatility clustering) coefficient of EGARCH is positive and significant for countries. That means the conditional volatility will rise or fall when the absolute value of the standardized residual is larger (smaller). It was also found that volatility takes a long time to die following any crisis in the respective market. In the light of the above findings, the researcher is the opinion that African stock markets should endeavour to make timely disclosure and appropriate dissemination of perceived economic vagaries, as well proffer commensurate palliative or solution to the public or investors. This will help to avert escalation of such information as bad news which increases volatility.

keywords:

Stock returns, Asymmetry effect, Magnitude effect, EGARCH, African Countries JEL Classification: C32, C58, G14, G41

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References:

Adewale, A. O., Olufemi, A. P., & Oseko, M. S. (2016). Modelling volatility persistence and
asymmetry with structural break: Evidence from the Nigerian stock market. Journal of
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Aguda, N. A. (2016). A test of asymmetric volatility in the Nigerian stock exchange. International
Journal of Economics, Finance and Management Sciences, 4(5), 263-268.

Bala, D. A. & Asemota, J. O. (2013). Exchange rates volatility in Nigeria: Application of GARCH
models with exogenous break. CBN Journal of Applied Statistics, 4(1), 89-116.

Banumathy, K., & Azhagaiah, R. (2015). Modelling stock market volatility: Evidence from India.
Managing Global Transitions, 13(1), 27-42.

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