We investigate the multi-scale information transmission between two implied volatilities in the energy markets (crude oil volatility and volatility in the energy market) and energy commodities returns (global energy commodity, brent, heating oil, natural gas and petroleum). The Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) based Rényi transfer entropy approach is employed to accomplish the research objective. The study’s outcome underscores that information flow between implied volatilities and energy commodities is negative with significance being scale-dependent. Especially, significant negative information flow is found at specific intrinsic mode functions (IMFs) such as IMF1, and from IMFs 6-9 suggesting short-, upper medium and long-term energy markets dynamics. Comparatively, we find profound negative information flow with the crude oil implied volatility than the volatility in the entire energy market implying the former’s strong hedging benefits. Investors and policymakers should have knowledge about the dynamics of implied volatilities, particularly, the crude oil implied volatility when designing strategies for the energy commodities markets.

We rely on daily changes in implied volatility indices for the US stock market (VIX), developed markets excluding the US (VXEFA), stock markets in Brazil (VXEWZ), Russia (RVI), India (NIFVIX), China (VXFXI), and the overall emerging market volatility index (VXEEM) to examine the degree of information flows among the markets in the coronavirus pandemic. The study also employs the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to decompose the data into intrinsic mode functions (IMFs). Subsequently, we cluster the IMFs based on their level of frequencies into short-, medium-, and long-term horizons. The analysis draws on the concept of Rényi transfer entropy (RTE) to enable an assessment of linear as well as non-linear and tail-dependence in the markets. The study reports significant information flows from BRIC volatility indices to the overall emerging market volatility index in the short-and medium-terms and vice versa. We also document a mixture of bi-directional and uni-directional flow of high risk information and low risk information emanating from emerging equity markets and from the developed markets. We find that the transmission of high risk information is largely dominated by the developed markets (VIX and VXEFA). In the midst of high degree of contagion, our findings reveal that investors can find minimal benefits by shielding against adverse shocks from the developed markets with a combination of stocks from India and other equities in the emerging markets in the short-term, within 1–15 days. For as low as 1–5 days, the empirical evidence indicates that a portfolio consisting of stocks from Russia and Brazil also offer immunity to shocks from the VXEFA. Our study makes an important empirical contribution to the study of market integration and contagion among emerging markets and developed markets in crisis periods.

No abstract

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.

This paper investigates the leverage effect of local realised exchange rate volatility and implied volatilities in energy market on exchange rate returns in BRICS for the period May 7, 2012 to March 31, 2022, using the quantile regression technique. This paper reveals that oil implied volatility shocks (OVX changes) have a significant negative impact on Russian-U.S. Dollar exchange rate returns in all quantiles. When it comes to the Indian rupee and Chinese RMB returns/Dollar, the adverse effects of OVX are most apparent in both normal and booming market conditions. Although South Africa's currency rate returns are affected by both slump- and bust-market situations, Brazil also tends to be in higher quantiles. The implied volatility indices in the energy market have a substantial and considerable negative impact on the BRICS currencies, with the exception of China, where the effect is only noticeable in the upper extreme quantiles. The policy implications and suggestions are discussed.