Abstract
This study employs segmented multifractal analysis to evaluate the efficiency of key financial markets in North Africa. The proposed method, an adapted version of Multifractal Detrended Fluctuation Analysis (MF-DFA), integrates a wavelet-based change-point detection to identify and separate the two most dynamically changing phases. Subsequent multifractal measurements are then conducted for each of these identified intervals. Focusing on three equity indices—the Egyptian Exchange Index (EGX30), Moroccan All Shares Index (MASI), and Tunisian Stock Index (Tunindex)–that collectively represent the North African financial and economic landscape, empirical results reveal significant asymmetric multifractality, especially notable in the two Maghreban indices. These findings prompt inquiries into the influence of major events on financial market efficiency. Segmented multifractal analysis introduces a novel approach to explore the dynamics and resilience of these sectors, contributing to a more profound understanding of their complex behaviors and responses to various stimuli.
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