ABSTRACT
We study the impact of COVID-19 on the pairwise dependence between three indices, the COVID-19 Media Coverage Index, MSCI World Semiconductor Index, and the MSCI World Energy Index, as well as investigate the respective volatility spillovers. We find intervals of weak, moderate, and strong coherence between the Media Coverage Index and returns and volatility of semiconductor and energy sector companies. Low coherence intervals indicate a diversification potential of investments in these sectors and in their volatility-based products during periods of systemic crises such as the financial turmoil induced by COVID-19. Our results provide evidence that after the escalation of the pandemic in early 2020, the energy sector cedes its leading role in terms of volatility to the semiconductor industry. We report on appealing hedging attributes related to the decoupling between the trends in the global semiconductor industry and the global energy sector accelerated by the COVID-19 triggered crisis.
ABSTRACT
We study the impact of COVID-19 on the pairwise dependence between three indices, the COVID-19 Media Coverage Index, MSCI World Semiconductor Index, and the MSCI World Energy Index, as well as investigate the respective volatility spillovers. We find intervals of weak, moderate, and strong coherence between the Media Coverage Index and returns and volatility of semiconductor and energy sector companies. Low coherence intervals indicate a diversification potential of investments in these sectors and in their volatility-based products during periods of systemic crises such as the financial turmoil induced by COVID-19. Our results provide evidence that after the escalation of the pandemic in early 2020, the energy sector cedes its leading role in terms of volatility to the semiconductor industry. We report on appealing hedging attributes related to the decoupling between the trends in the global semiconductor industry and the global energy sector accelerated by the COVID-19 triggered crisis.
ABSTRACT
This paper investigates the influence of oil demand, oil supply, and risk-driven shocks on the yield curve in the US between 1995 and 2020. The US term-structure shape is modeled by three structural factors, the level, slope, and curvature. Their empirical analysis is performed according to the Diebold-Li modified variant of the widely used Nelson-Siegel model. The technique of wavelet analysis allows investigating the interrelation of shocks in oil prices and the US yield curve along time and frequency domains, simultaneously. We report on low, medium, and high coherence zones, relative to the oil price movements and the changes in the three yield-curve factors. The low coherence intervals indicate the potential for the three latent factors to be used for creating diversification strategies capable of hedging adverse dynamics in the oil market, potentially workable through global crises. We document the variability of dynamic patterns observable for the US sovereign yield factors on per-type-of-shock basis, evidencing the potential role of the US sovereign debt investments for designing cross-asset hedge strategies for commodity and fixed-income markets.
ABSTRACT
We apply wavelet analyses to study how the Covid pandemic influenced the volatility of commodity prices, covering various classes of commodities. We document the intervals of low, medium, and high coherence between the coronavirus panic index and the moves of the commodity prices. The low coherence intervals indicate the diversification potential of commodity investments during a systemic pandemic such as Covid-19. We document differences in the observed patterns per commodity category and evidence their potential role for designing cross-assets hedge strategies based on investments in commodities.