# Co-movement between stock markets in advanced economies and Africa in times of uncertainty: A time-frequency domain approach

## TL;DR

This study explores how stock markets in advanced economies and African countries move together during uncertain times, including the impact of the pandemic.

## Contribution

The study introduces a bivariate wavelet approach to analyze co-movement, addressing gaps in pandemic-related market interdependence.

## Key findings

- Co-movement between advanced and African stock markets reflects interdependence rather than contagion.
- African stock markets are becoming less resilient to global market fluctuations during crises.
- The bivariate wavelet approach effectively captures non-linear and non-stationary market behaviors.

## Abstract

This study examined the co-movement between New York and Shanghai stock markets, and twelve African stock markets, before, during, and after the COVID-19 pandemic. Daily composite indices from January 2016 to March 2023 were used for the study. The study employed the continuous complex Morlet wavelet transform which is best for time-frequency domain in terms of magnitude, direction, and lead-lag in localised linearity, and stationarity. The results revealed notable co-movements between the two advanced markets and some African stock markets. However, considerable number of co-movements between the two advanced markets and most African stock markets were not significant. Furthermore, the study found that the nature of co-movement between advanced and African markets reflects interdependence more than contagion. The results further indicate that, the long-held assertion that African stock markets are resilient to fluctuations in advanced markets during periods of global turbulences if gradually fading away. This study addresses a critical gap in the literature concerning the influence of pandemics on co-movement of markets with a specific focus on co-movement between stock markets in advanced economies and those in Africa. In addition, it departs from previous studies by employing a bivariate wavelet approach which effectively handles non-linearity, non-stationarity, structural breaks and time localization. We recommend that policymakers incorporate both time and frequency characteristics of markets into market regulations and strategies. Investors should employ risk minimisation strategy through the creation of international portfolios between global and emerging African markets to enhance their reward from investments in stocks, albeit with due caution.