Integration, Contagion and Turmoils; Evidence from Emerging markets

Purpose – Based on weekly data from 2012 to 2024, this paper aims to evaluate empirically ‎the integration and contagion properties of some emerging stock markets from North Africa ‎including Morocco, Tunisia and Egypt, and to deepen the understanding of the linkage ‎between them during stable and turmoil periods (Covid 19, Ukrainian war and Gazza war).‎ Design/methodology/approach – Besides traditional Granger causality (GC) test (Granger, ‎‎1969), the (Shi, Hurn, & Phillips, 2020)’ time-varying (TV) GC test, the (Song & Taamouti, ‎‎2020)’ quantiles GC test, and the (Breitung-Candelon, 2006)’ frequency domain (FD) GC ‎tests are used for the contagion (diversification) check between market volatility (returns). ‎Then, the returns DCC- GARCH specifications are used for the integration investigations. ‎Then, based on the returns DCC dynamic regressions, the contagion analysis between ‎considered markets that are related to the unexpected events is done.‎ Findings – As the results from the standard GC, all considered tests reveal that in mean, ‎Tunisian returns R_T and Egyptian R_E are predictable by Moroccan R_M. Only Tunisian ‎and Egyptian return can play then the role of diversifier. Results from these causality tests ‎detect some contagion in variance between markets, which was denied from dynamic DDC ‎regression regressions in returns. From dynamic DCC-GARCH model, our empirical results ‎show a weak integration between returns. ‎ Originality/value – Via the dynamic DCC ARCH and the DCC quantile regression, the time ‎varying GC, the quantile GC, and the spectral GC tests, this paper provides a deeper ‎understanding of North African marginal stock market behavior and linkage.‎