Assessing the efficiency of African stock markets through multifractal cross-correlation insights

This paper investigates the informational efficiency and cross-correlations among the five largest African stock markets—Johannesburg, Casablanca, Botswana, Nigerian, and Egyptian—using Multifractal Detrended Cross-Correlation Analysis (MF-DCCA). Spanning the period from January 30, 2012, to August 8, 2024, with nearly 3,050 observations, the study explores the multifractal characteristics and complex interdependencies among these markets. Initial results from the Cross-Correlation Significance Test indicate statistically significant relationships across most index pairs. Further analysis using MF-DCCA components—Generalized Hurst exponents, Rényi exponents, and the Hölder Singularity Spectrum—reveals persistent long-range cross-correlations and strong multifractal behavior. The application of surrogate and shuffling procedures confirms that both long-memory effects and heavy-tailed distributions contribute to the observed multifractality. These findings suggest the presence of informational inefficiencies within and between African stock markets, as evidenced by deviations from random-walk behavior. The study provides new insights into market dynamics in emerging economies, with practical implications for investors, portfolio managers, and policymakers.