From Sectoral Insights to Stock-Level Networks: Unveiling the Casablanca Stock Exchange Micro-Structure

Abstract

This paper investigates the dynamics within the Casablanca Stock Exchange topology during crisis and non-crisis periods using daily historical log-returns of sectoral indices spanning the period from January 4, 1993, to September 9, 2021. The study applies Agglomerative Hierarchical Clustering to the Dynamic Time Warping distance matrix across ten sub-periods encompassing major financial crises, from the Subprime Mortgage Crisis to the European Debt Crisis and the COVID-19 pandemic. The resulting clustering outcomes are aggregated into a network representation to reveal the cumulative interconnections among sectoral indices. The findings indicate the interconnections among the Casablanca Stock Exchange sectoral indices appear to be trend-dependent, with the O\&G sector emerging as a central hub within the network. Extending this analysis to a finer level, the study examines the dynamics of stocks composing the MASI index. Daily historical log-returns of stocks are collected for MASI constituents over the period from January 2, 2013, to October 27, 2022. Using a Granger causality–based topological approach, the study investigates the evolving interdependencies among stocks, providing deeper insights into the microstructure of the Casablanca Stock Exchange at the stock level.