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The study aims to shed new lights on the lead-lag relationships between the financial sector (RFSI) and economic growth (GDP) in the midst of global economic policy uncertainty (GEPU) shocks for BRICS economies. Hence, the bivariate, partial, and wavelet multiple correlations techniques are employed. From the bivariate analysis, we document positive bi-directional causality between the RFSI and economic growth over the sample period. The partial wavelet reveals that GEPU shocks distort the significance and directional comovements between the RFSI and GDP. Moreover, the outcome from the wavelet multiple cross correlations (WMCC) indicates that the RFSI is a first mover at most time scales for the BRICS economies. This is followed by GEPU which either leads or lags for most scales, especially for South Africa. The impact of GEPU on RFSI and GDP is worst for South Africa in about four cases in the medium-, and long-terms. This signifies that South Africa’s financial markets and economic growth are vulnerable to GEPU. However, the impetus for GEPU to drive the comovements between the financial sector and economic activity was less pronounced in the pre-COVID analysis conducted with the WMCC. The study supports both the supply-leading and demand-following hypotheses. Our findings also underscore the need for policymakers, investors and academics alike to incessantly observe the dynamics between finance and growth across time and periodicity while considering adverse shocks from global economic policy uncertainty in tandem.

Owing to the adverse impact of the COVID-19 pandemic on world economies, it is expected that information flows between commodities and uncertainties have been transformed. Accordingly, the resulting twisted risk among commodities and related uncertainties is presumed to rise during stressed market conditions. Therefore, investors feel pressured to find safe haven investments during the pandemic. For this reason, we model a mixture of asymmetric and non-linear bi-directional causality between global commodities and uncertainties at different frequencies through the information flow theory. Consequently, we utilise the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and the Rényi effective transfer entropy techniques to establish the dynamic flow of information. The intrinsic mode functions (IMFs) from the CEEMDAN are carefully extracted into multi-frequencies through cluster analysis to reconstruct the series into high, medium, and low frequencies in addition to the residue. We utilise daily data from December 31st, 2019, to March 31st, 2021, to provide insights into the COVID-19 pandemic. The correlation coefficients and variances demonstrate that the high frequency (IMFs 1–4) which measures the short-term dynamics is the dominant frequency, suggesting short-lived market fluctuations relative to real economic growth for institutional investors. Moreover, outcomes from the multi-frequency entropy indicate a negative bi-directional causality of information flow between global commodities and uncertainties, especially in the long term. Generally, the findings present pertinent inferences for portfolio diversification, policy decisions, and risk management schemes for global commodities and markets volatilities. We, therefore, advocate that market volatilities act as effective hedges for global commodities, and they clearly act as balancing assets rather than substitutes in the long-term dynamics of the COVID-19 pandemic. Investors who delayed in investing within financial markets of commodities and market volatilities are likely to minimise their portfolio risks.

This paper revisited the crude oil – stock market nexus to examine how the oil implied volatility index (a forward-looking and more accurate measure for uncertainty in oil prices) affects stock returns in major Africa's oil-importing (South Africa, Kenya, Mauritius, and Botswana) and oil-exporting (Nigeria, Egypt, Tunisia, and Morocco) countries during the COVID-19 pandemic. Quantile regression is employed to examine the heterogeneous relationship at different market conditions. The study documents evidence to support a negative relationship between the oil implied volatility shocks and stock returns in the selected stock markets, especially in downturns. Findings from this study also reveal that the oil implied volatility shocks can asymmetrically influence Africa's stocks. Specifically, our empirical evidence reveals that positive shocks in the oil implied volatility index play a key role in most of Africa's stock markets in market downturns while negative shocks play a moderate role during benign market conditions in some of Africa's stock markets during the pandemic. More importantly, our findings divulge that investors can find an invaluable shelter with a portfolio of the selected African stocks and oil market securities in the time of the pandemic. The policy implications are further discussed.

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