Purpose: Despite the growing recognition of the complex interplay between macroeconomic shock indexes and stock market dynamics, there is a significant research gap concerning their interconnectedness and return spillovers in the context of the African stock market. This leaves much to be desired, given that the financial market in Africa is arguably one of the most preferred destinations for hedge and portfolio diversification (Alagidede, 2008; Anyikwa and Le Roux, 2020). Further, like other financial markets across the globe, the increased capital flow, coupled with declining information asymmetry in Africa, has deepened intra and inter-sectoral integration within and across national borders. This has, thus, increased the susceptibility of financial markets in Africa to spillover of shocks from other sectors and jurisdictions. Additionally, while previous studies have investigated these factors individually (Asafo-Adjei et al., 2020), with much emphasis on developed markets, an all-encompassing examination of spillovers and the connectedness between the aforementioned macroeconomic shock indexes and stock market returns remains largely unexplored. This study happens to be the first to consider the impact of each of the indexes on stock returns in Africa, with evidence spanning from May 2007 to April 2023, covering notable global crisis episodes such as the Global Financial Crisis (GFC), the COVID-19 pandemic and the Russia–Ukraine war.Design/methodology/approach: This study employs the novel quantile vector autoregression (QVAR) model, making it the first of its kind in literature. By applying the QVAR, the study captures the potential nonlinear and asymmetric relationship between stock returns and the factors of interest across different quantiles, i.e. bearish, normal and bullish market conditions. Thus, the approach allows for a more accurate and nuanced examination of the tail dependence and extreme events, providing insights into the behaviour of the variables under extreme events.Findings: The study revealed that connectedness and spillovers intensified under bearish and bullish market conditions. It was also observed that, among the macroeconomic shock indicators, FSI exerted the highest influence on stock returns in Africa in both bullish and normal market conditions. Across the various market regimes, the Egyptian Exchange (EGX) and the Nairobi Stock Exchange (NSE) were net receiver of shocks.Originality/value: This study happens to be the first to consider the impact of each of the indexes on stock returns in Africa, with evidence spanning from May 2007 to April 2023, covering notable global crisis episodes such as the GFC, the COVID-19 pandemic and the Russia–Ukraine war. On the methodology front, this study employs the novel QVAR model, making it one of the few studies in recent literature to apply the said method.

Purpose: This study seeks to examine the relationship between macroeconomic shock indicators, namely geopolitical risk (GPR), global economic policy uncertainty (GEPU) and financial stress (FS), and returns as well as volatilities on seven carefully selected stock markets in Africa. Specifically, the study intends to unravel the co-movement and interdependence between the respective macroeconomic shock indicators and each of the stock markets under consideration across time and frequency.Design/methodology/approach: This study employed wavelet coherence approach to examine the strength and stability of the relationships across different time scales and frequency components, thereby providing valuable insights into specific periods and frequency ranges where the relationships are particularly pronounced.Findings: The study found that GEPU, Financial Stress (FS) and GPR failed to induce significant influence on African stock market returns in the short term (0–4 months band), but tend to intensify in the long-term band (after 6th month). On the contrary, stock market volatilities exhibited strong coherence and interdependence with GEPU, FSI and GPR in the short-term band.Originality/value: This study happens to be the first of its kind to comprehensively consider how the aforementioned macro-economic shock indicators impact stock markets returns and volatilities over time and frequency. Further, none of the earlier studies has attempted to examine the relationship between macro-economic shocks, stock returns and volatilities in different crisis periods. This study is the first of its kind in to employ data spanning from May 2007 to April 2023, thereby covering notable crisis periods such as global financial crisis (GFC) and the COVID-19 pandemic episodes.

Purpose: This study seeks to: (1) examine the extent of interconnectedness prevailing between the cryptocurrency market, the stock market and the precious metals market. (2) Conduct thorough assessment of hedge and safe-haven qualities of broad range of precious metals and cryptocurrencies against returns on the African stock market. Design/methodology/approach: This study applied two novel approaches that is Cross-quantilogram, an advanced statistical technique used to examine the relationship between quantiles of response variable and the quantiles of predictor variables, and TVP-VAR, a technique that captures the dynamic connectedness of variables under consideration. Findings: It was found that the three markets are highly interconnected, particularly among assets under the respective financial markets. It was further revealed that the Johannesburg Stock Exchange (JSE) was the most resilient stock market, whereas Bitcoin, BNB, Silver (XAG) and Platinum (XPT) also exhibited notable resistance to shocks. Finally, the study found that cryptocurrencies and precious metals portrayed varying hedge and safe haven qualities under the various stock markets. Practical implications: The high interdependency between the African stock market, cryptocurrencies and precious metals suggests that none of the markets is immune to shocks form the other market. The finding that cryptocurrencies and precious metals exhibit some degree of safe-haven and hedge potentials, albeit limited in certain stock markets, provides investors with alternative investment options during market downturns. Since most African stock markets, except the JSE, are net receivers of shocks, investors in these markets should exercise caution during periods of global financial uncertainty. Originality/value: To the best of our knowledge, this study is the first to explore the dynamic interconnectedness between seven carefully selected African stock markets, three distinct cryptocurrencies and four precious metals, while also assessing the hedge and safe-haven potential of the cryptocurrencies and precious metals against stock market returns. Additionally, the study stands out in recent literature by employing two novel approaches: the TVP-VAR model, which captures the dynamic connectedness among variables, and the Cross-Quantilogram, an advanced statistical method that analyzes the relationship between the quantiles of the response and predictor variables, all within a single study.

This study sought to ascertain a machine learning algorithm capable of predicting crises in the African stock market with the highest accuracy. Seven different machine-learning algorithms were employed on historical stock prices of the eight stock markets, three main sentiment indicators, and the exchange rate of the respective countries’ currencies against the US dollar, each spanning from 1 May 2007 to 1 April 2023. It was revealed that extreme gradient boosting (XGBoost) emerged as the most effective way of predicting crises. Historical stock prices and exchange rates were found to be the most important features, exerting strong influences on stock market crises. Regarding the sentiment front, investors’ perceptions of possible volatility on the S&P 500 (Chicago Board Options Exchange (CBOE) VIX) and the Daily News Sentiment Index were identified as influential predictors. The study advances an understanding of market sentiment and emphasizes the importance of employing advanced computational techniques for risk management and market stability.

This study seeks to investigate the spillover effects between uncertainty indexes and returns on African stock markets; explore the time-varying nature of these interactions using TVP-VAR and QVAR techniques; and assess the resilience of individual stock markets to shocks, with particular attention to Energy Policy Uncertainty (EPU), Climate Policy Uncertainty (CPU), and Geopolitical Risks (GPRs) indexes. Accordingly, we employed two novel techniques, namely QVAR and TVP-VAR connectedness approaches to ascertain interdependencies under the bearish, bullish, and normal market regimes. The results for the QVAR approach revealed a total connectedness index (TCI) of 89.5%, suggesting substantial co-movement across markets during bearish market regime. Total connectedness index increased marginally to 89.7% under the bullish regime, reflecting an adaptive shift in shock propagation. Results from the TVP-VAR technique show a TCI of 71.97%, an indication of a reduced market interconnectedness amidst normal market regimes. We observe that CPU, EPU, and GPRs displayed heterogeneous spillover effects, with EPU and GPRs presenting pressing risks for majority of the markets. Additionally, the markets exhibited varying degrees of resilience under the various regimes, providing valuable insights for investors and policymakers on the nuances of the African stock market and shocks across various market regimes.