Interdependence among West African stock markets: A dimension of regional financial integration

Abstract

Understanding the nature of interdependence between international stock markets is vital for portfolio diversification, risk management and market regulation. This paper examines the nature of interdependence among West African stock markets using correlation analysis, the Granger causality test and a multivariate BEKK‐GARCH (1,1) model. The results show evidence of a weak relationship among West African stock markets. The results also show absence of causal dependence between the Côte d'Ivoire BRVM (Bourse Régionale des Valeurs Mobilières), and the Ghana stock market, but evince feedback relationship between the Côte d'Ivoire BRVM and the Nigeria stock market as well as between the Ghana and Nigeria stock markets. The results further reveal no evidence of volatility spillover between the Côte d'Ivoire BRVM and the Ghana stock market, but show evidence of unidirectional volatility spillover from the Nigeria stock market to the Côte d'Ivoire BRVM as well as bidirectional volatility spillover between the Nigerian and Ghanaian stock markets. Overall, the findings reveal existence of weak interdependence among West African stock markets, and that West African financial markets are interdependent through the Nigerian market. These findings are relevant to stock market stabilisation and investment policy in West Africa.

On the Dynamic Changes in the Global Stock Markets’ Network during the Russia–Ukraine War

“…These nodes are identified as the most vulnerable ones compared to China, Kazakhstan, and Czechia; there were few or no changes for Nigeria, which exhibited stable behavior among all nodes. The possible explanation for the stable behavior of this node can be associated with the Nigerian stock market's low level of integration with the rest of the world, despite its anchoring position in West African stock markets, as reported by Emenike (2021). The same conclusion about the linkage between Nigerian and developed stock markets was also documented by Oluseun Olayungbo et al (2023), who concluded on the availability of diversification and hedging opportunities.…”

“…To attain this objective, 55 indices pertaining to different countries were employed to construct 22 financial networks, which were These nodes are identified as the most vulnerable ones compared to China, Kazakhstan, and Czechia; there were few or no changes for Nigeria, which exhibited stable behavior among all nodes. The possible explanation for the stable behavior of this node can be associated with the Nigerian stock market's low level of integration with the rest of the world, despite its anchoring position in West African stock markets, as reported by Emenike (2021). The same conclusion about the linkage between Nigerian and developed stock markets was also documented by Oluseun Olayungbo et al (2023), who concluded on the availability of diversification and hedging opportunities.…”

How does sovereign bond volatility interact between African countries?

“…Following Emenike (2021), Wald test was computed to evaluate consistency of estimates from BEKK-GARCH-(1,1) model. The null hypotheses of the Wald test for regional pairs of Africa countries sovereign bonds are: A I,J 5 B I,J 5 0, indicates that absence of volatility interaction from sovereign bond of country I to sovereign bond of country J. conversely, A J,I 5 B J,I 5 0, suggests that there is no volatility interaction sovereign bond of country J to sovereign bond of I.…”

“…Statistical significance of the diagonal elements a11,t (a22,t) would suggest that the current conditional variance of h11,t (h22,t) is correlated with its own past squared errors, whereas significance of the lagged variance b11,t (b22,t) indicate that the current conditional variance of h11,t (h22,t) is affected by its own past conditional variance. Similarly, the statistical significance of the off-diagonal coefficients a12,t and b12,t will indicate evidence of shock and volatility interaction effects from the sovereign bond volatility of country i to the sovereign bond volatility in country j , whereas the statistical significance of the off-diagonal coefficients a21,t and b21,t will show evidence of sovereign bond volatility interaction effects from country j to country i (…”

Stock market integration in Africa: Further evidence from an information‐theoretic framework

“…Differing and sometimes innovative approaches have been used to untangle and determine dependencies among African stock exchanges. While some studies use traditional VAR‐based and Pearson correlation analyses, recent studies counter the inadequacies of these traditional methods by using, among other methods, the BEKK‐GARCH model (Emenike, 2021); Toda and Yamamoto Granger causality (Obadiaru et al, 2020); wavelet multiple correlation (WMC) and wavelet multiple cross‐correlation (Boako & Alagidede, 2017; Tweneboah et al, 2019); and copulas (Mensah & Alagidede, 2017). Most of these studies conclude that African stock exchanges are weakly integrated and are largely segmented from developed exchanges.…”