Quantile connectedness between African stock markets, Twitter sentiment index, implied volatilities, financial condition index and economic uncertainty

Abstract

Purpose This study aims to examine the quantile-based time-frequency spillovers between African stock prices and global uncertainty indicators. Design/methodology/approach The study applies the quantile vector autoregressive connectedness framework to daily data (2012–2023) for nine African stock markets and global indicators – VIX, OVX, EPU, FCI and Twitter sentiment. This method captures time–frequency spillovers across quantiles, revealing short- and long-term directional shock transmission under varying market conditions. Findings The study finds medium-term overall spillovers, stronger in the short-term and during turbulent periods. Financial Conditions Index, VIX, and Egypt, Kenya and Mauritius markets act as net transmitters, while Twitter sentiment and other markets are net receivers. Uganda shows strong unidirectional spillover to Kenya. Research limitations/implications The study extends literature on emerging-market contagion, highlighting tail-specific and horizon-dependent spillovers. Practical implications Findings help investors optimize portfolios by identifying key transmitters – FCI, VIX and select African markets – for strategic hedging. Originality/value This study is the first to integrate African stock markets with global uncertainty, volatility and social-media sentiment using a quantile time–frequency connectedness framework. By capturing tail-specific and horizon-dependent spillovers, it provides a nuanced understanding of dynamic risk transmission, offering fresh insights for investors, regulators and policymakers.