Purpose

The paper examines the impact of COVID-19 on the network structure of the Ghana Stock Exchange (GSE) market.

Design/methodology/approach

The study utilises the minimum spanning tree (MST) and network measures, including normalised tree length, average shortest path length, node degree, and node strength, to analyse the GSE structure across three periods: pre-COVID-19 (January–December 2019), COVID-19 (January–December 2020) and post-COVID-19 (January–December 2021).

Findings

The study reveals a contraction of the MST, reduced normalised tree length and average shortest path length during COVID-19 compared to pre-COVID-19. The GSE market network structure underwent significant changes during COVID-19, with the MST expanding and normalised tree length increasing post-COVID-19. Node degree and strength analyses identified ICT stock as the central node pre-COVID-19, while financial stock assumed this role during and after COVID-19. These findings underscore the profound impact of the COVID-19 pandemic on the structure and dynamics of the GSE market network.

Research limitations/implications

The study used correlation to measure the linear relationships between stocks without accounting for nonlinear associations. It focused exclusively on the GSE market. Despite this limitation, the empirical findings and robustness tests reveal the significant impact of COVID-19 on the GSE market’s network structure. These results highlight the dynamic nature of the GSE market’s network topology.

Practical implications

This paper highlights the dynamic nature of the GSE market network structure, providing valuable insights for investors and market participants to navigate similar crises in the future. Additionally, GSE regulators can leverage these findings to identify stocks that may pose risks during extreme market events.

Originality/value

This study is the first in Ghana to examine the effects of extreme events, such as COVID-19, on the network structure of the GSE market.