Analysis of Volatility Spillover in African Stock Markets: Evidence from Nigeria, Ghana, and South Africa

Authors

  • Peter Ali Department of Financial Management Technology, FUTO – Nigeria
  • Samuel M Nzotta Department of Financial Management Technology, FUTO – Nigeria
  • A.B.C Akujuobi Department of Financial Management Technology, FUTO – Nigeria
  • C.E. Nwaimo Department of Financial Management Technology, FUTO – Nigeria

DOI:

https://doi.org/10.26905/afr.v5i1.7547

Keywords:

Africa stock markets, GARCH-BEKK model, volatility spillover, Nigeria, Ghana South Africa.

Abstract

The purpose of this paper was to analyze stock market return volatility spillover between in Sub-Sahara markets using Nigeria, Ghana and South Africa monthly data from January 2000 to December 2017. Preliminary analyses from descriptive statistics show that show mean monthly returns are positive for all the stock markets. Skewness coefficients show that the stock returns and interest rates distribution of all Sub-Sahara Africa stock markets are negatively skewed but inflation rate is positively skewed for Nigeria and South Africa, and flat for Ghana. Excess kurtoses are positive for all the stock markets and macroeconomic indicators, and Jarque-Bera statistics indicate the stock markets’ series and macroeconomic indicators are not normally distributed. The Unit roots tests results indicate that all the stock markets and macroeconomic indicators are first difference stationary. The results of multivariate BEKK-GARCH (1,1) model show evidence of volatility spillover in Sub-Sahara Africa stock markets. We therefore recommend amongst others that stock market authorities should formulate and implement policies that would mitigate any negative effect of stock return volatility on the wealth of retail investors so as to sustain investors’ confidence in the African stock markets. This will eliminate the destabilising impact on the investors’ confidence on the markets.

References

Akuffo, B., Ampaw, E.M. & Lartey, S. (2014). Conditional heteroscedasticity: GARCH model

with application to interest rate in Ghana (2003:01 – 2013:12). Mathematical Theory and

Modeling. 4(6), 32-46.

Botha, F. & King, D. (2014). Modelling stock return volatility dynamics in selected African

markets. Economic Modelling, 45, 50-73.

Chinzara, Z. (2010). Macroeconomic uncertainty and emerging market stock market volatility:

The case for South Africa. University of Rhodes Working Paper No. 187.

DeCarlo, L. T. (1997). On the meaning and use of kurtosis. Psychological Methods, 2, 292-307.

Emenike, K. O. (2010). Modelling stock returns volatility in Nigeria using GARCH models.

African Journal of Management and Administration, 3(1), 8-15.

Emenike, K. O. (2016). Volatility transmission between money and stock markets: Evidence

from a developing financial market. Journal of Economic and Financial Sciences, 9(1), 244-255.

Emenike, K.O. (2018). Exchange rate volatility in West African countries: Is there a shred

spillover. International journal of emerging markets 13(6), 1457-1474.

Emenike, K. O. (2020). Dynamic interdependence between crude oil prices and foreign exchange

market in Nigeria. Studies in Economics and Econometrics, 44(3).

Enders, W. (2004). Applied Econometric Time Series (2nd Ed.). Singapore: John Wiley & Sons

(ASIA) Pte Ltd.

Friedman, J. & Shachmurove, Y. (2005). European stock markets dynamics before and after

the introduction of the euro. Penn Institute for Economic Research PIER Working Paper

No. 05-028.

Ljung, G.M. & Box, G.E.P. (1978). On a measure of lack of fit in time series models.

Biometrika, 67, 279-303.

Makhwiting, M.R., Lesaoana, M. & Sigauke, C. (2012). Modelling volatility and financial

market risk of shares on the Johannesburg stock exchange. African Journal of Business

Management, 6(27), 8065-8070.

Nnachi, A. (2008). Financial linkages of the Nigerian stock market, Unpublished PhD Thesis

Submitted to the Department of Banking and Finance, University of Nigeria Nsukka.

Okpara, G. C. (2012). Volatility modelling and stock return relationship in Nigeria. Unpublished

Ph.D Thesis Presented to the School of Postgraduate Studies, Federal university of Technology Owerri.

Onwumere, J.U.J. (2005). Business and economic research methods, Lagos: Don Vinton Ltd.

Panda, A.K., Nanda, S. & Paital, R.R. (2019). An empirical analysis of stock market

interdependence and volatility spillover in the stock markets of Africa and Middle East region. African Journal of Economic and Management Studies, 10(3), 314-335.

Ramona B., Marian S. & Jatin T. (2014). Modeling and estimating long-term volatility of

R.P.G.U stock markets. Recent Advances in Energy, Environment and Financial Planning,

-280.

Senga, C. & Cassimon, D. (2019). Spillovers in sub-Saharan Africa’s sovereign Eurobond yields.

Emerging Markets Finance and Trade, 1-17.

Shafiq, K. E. (2000). Volatility transmission between foreign exchange and money markets

Bank of Canada Working Paper 2000-16, Financial Markets Department; August.

Varghese, G. (2018). Within and cross volatility contagion effects among stock, crude and

forex returns: Empirical evidence from five emerging economies. Theoretical Economics Letters, 8, 1475-1492. doi: 10.4236/tel.2018.88095.

Vivek, B, Malhotra, D.K. Philip, R., & Rahul, S. (2012). An empirical examination of volatility

spillover between the Indian and US swap markets. International Journal of Emerging

Markets, 7(3), 289 – 304.

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Published

2022-02-20

How to Cite

Ali, P., Nzotta, S. M., Akujuobi, A., & Nwaimo, C. (2022). Analysis of Volatility Spillover in African Stock Markets: Evidence from Nigeria, Ghana, and South Africa. AFRE (Accounting and Financial Review), 5(1), 64–71. https://doi.org/10.26905/afr.v5i1.7547

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Articles