Exploring the Time-varying Connectedness and Contagion Effects among Exchange Rates of BRICS, Energy Commodities, and Volatilities

This paper investigates the total and net directional connectedness of the energy market and currency market amid volatilities (local and international) of BRICS for the period May 7, 2012 to March 31, 2022. The Time-varying parameter Vector Autoregression (TVP-VAR) connectedness approach is specifically employed. We reveal that the average value of the total connectedness index (TCI) is 46.91%, for the specific network of energy commodities, currency rates, and volatilities. Also, from the averaged dynamic connectedness, the global energy commodity index demonstrated the most transmitter of shocks. Conversely, BRICS currency markets (except for Brazilian Rubble) and most implied energy volatilities and realised exchange rate volatilities were net receivers of shocks. Moreover, the total connectivity indices were seen to vary significantly during the study sample period with strong susceptibility to crisis periods, especially, the COVID-19 pandemic. We advocate that most volatilities were consistent net transmitters across time as indicated by the net directional connectedness. The findings imply that in a network of energy commodities, exchange rate, and volatilities, risk minimisation is elated to boost investors' confidence across time.

Oil tail-risk forecasts: from financial crisis to COVID-19

The coronavirus outbreak has caused unprecedented volatility in oil prices. This paper extends previous studies on oil Value-at-Risk (VaR) by providing extra insights into Expected Shortfall (ES) forecasting over the last decade, including several oil crises. We introduce a conditional volatility model combined with the Cornish-Fisher expansion for ES forecasting. In comparison to the widely used volatility models and innovation distributions, this approach is superior for predicting the ES of long positions but overestimates VaR for short positions. Overall, the volatility model addressing leverage effects with skewed t innovation produces the most accurate joint VaR and ES forecasting. Moreover, the magnitude of ES relative to VaR varies across models and time, implying that ES should be used in conjunction with VaR to inform timely risk management decisions. The results would be of interest to the regulatory authorities, energy companies, and financial institutions for oil tail-risk forecasting.

Return and volatility spillovers between energy and BRIC markets: Evidence from quantile connectedness

Using the quantile connectedness approach for the median, lower, and upper quantiles, we examine the return and volatility connectedness between energy and BRIC markets from January 1, 2000, to July 9, 2021. We find that uncertain economic activity and intense periods characterize energy and BRIC market returns and volatility connectedness. A parallel return and volatility connectedness structure for upper and lower quantiles against the average quantile revealed different results. Time-varying features are substantiated between energy and BRIC markets;significant distress events, such as the Global Financial Crisis, European Debt Crisis, Shale Oil Revolution, and COVID-19 pandemic, intensified spillovers. We highlight diversification avenues for energy and BRIC markets given the periods of financial turmoil, with investors’ concerns widely addressed by opt-in investment opportunities with lower risk and greater diversification. Our study has beneficial implications for policymakers, regulators, investors, and financial market constituents to redevelop their existing strategies to avoid financial losses.

Evidence from the nonlinear autoregressive distributed lag model on the asymmetric influence of the first wave of the COVID-19 pandemic on energy markets

The COVID-19 pandemic remained a global risk factor and integrated into various means in the functioning of companies, economies and financial markets. Therefore, this paper investigates how COVID-19 influences the energy market in the main financial markets (China, France, Germany, Italy, Spain and the United States), using time series from February 28, 2020, to November 3, 2020. The goal of this research is to investigate the asymmetric impact of COVID-19 from leading financial markets on energy commodities. In this regard, the non-linear auto-regressive distributed lag (NARDL) framework is employed to capture the long-run asymmetric reactions. The econometric design allows to explore the long-term asymmetric reactions of dependent variables through positive and negative partial sum decompositions of changes in the explanatory variables. The quantitative results show a significant long-run asymmetric interdependence between the number of new SARS-CoV-2 incidence and mortality and the daily percent change in close price of future contracts pertaining to Brent oil, crude oil WTI, carbon emissions, gasoline RBOB, heating oil, Chukyo kerosene, and natural gas. Furthermore, no asymmetry is found in the case of ethanol and fuel oil futures. The novelty of this article is the study of the impact of COVID-19 on the energy sector during the first two waves of COVID-19 by applying the NARDL model that allows to capture long-term asymmetric reactions. Certainly, further research on this topic is necessary due to the permanent shifts in the pandemic, as well as the availability of longer data periods on COVID-19.

Energy Commodity Price Response to COVID-19: Impact of Epidemic Status, Government Policy, and Stock Market Volatility

The outbreak of the COVID-19 pandemic has hit the global financial markets, including energy commodities. The aim of the paper is to examine the reaction of the energy commodity market to the COVID-19 pandemic, particularly the epidemic status, the stringency of the government anti-COVID-19 policy, and the stock market volatility. We use daily data on the S&P GSCI Energy index, the number of new confirmed COVID-19 global cases, the self-developed Global Stringency Index, and the VIX index. The research covers the period from January 2 to September 30, 2020, i.e. the first phase of the COVID-19 pandemic. Based on a structural vector autoregressive model we observe a significant and negative energy commodity market’s reaction to the changes in the stock market volatility. Moreover, the results imply that the increase in the Global Stringency Index leads to the decline in the S&P GSCI Energy index but the reaction is significant only on the third day after the shock. We reveal no significant impact of global epidemic status on energy commodity prices.

Does COVID-19 open a Pandora's box of changing the connectedness in energy commodities?

With the rapid spread of coronavirus, the global financial markets have been undergoing tremendous changes, which bring investors more risks in the short term. Against such background, this study concentrates on the far-reaching energy commodities, aiming to explore the impact of COVID-19 on cross-market linkages. To capture the dynamic nature of interdependence, we applied the TVP-VAR based connectedness index method and individually focused on the total, net, and pairwise connectedness. The empirical results show that there is a dramatic rise in the total connectedness in energy markets following the outbreak of COVID-19, but this change only lasted about two months and then fell back to the prior level. Further analyzing the net spillover conditions, we find that the connectedness structure has also displayed some temporary changes. At last, the spillover networks indicate that there are only three pairwise connectedness relations have changed in direction before and after the outbreak of COVID-19. We also try to discuss the underlying COVID-19 shock propagation mechanism, and the results suggest the significant mediation effect of the financial panic risk. In general, our study offers several urgent and prominent implications to understand the financial impact of COVID-19.