The time-frequency connectedness among metal, energy and carbon markets pre and during COVID-19 outbreak

“…In addition, optimal hedging ratios increased substantially in most cases during the COVID-19 phase, leading to higher hedging costs during the crisis. e findings of Jiang and Chen [55] also indicate that overall connectedness has increased significantly since the COVID-19 outbreak, as compared to the preCOVID era. Jiang and Chen [58] confirmed that following the COVID-19 outbreak, overall connectivity has increased.…”

Section: Background Literaturementioning

confidence: 88%

“…irdly, different from prior papers that employed merely the worldwide pandemic cases [3,24,43,44], our econometric investigation covers both new cases of COVID-19 pandemic globally and in Europe. As well, contrary to prior papers that used the price of WTI crude oil [1-4, 7, 8, 24-26, 29, 33, 35, 39, 43, 45-56], Brent crude oil [4,7,8,15,24,26,36,37,43,44,46,47,49,51,52,[54][55][56], Dubai crude oil [4,8], NYMEX's oil [26,55,57], or carbon futures [14], the current study covers the daily returns of the Physical Electricity Index, Amsterdam Power Exchange Electricity Netherlands Average All Hours and, London Natural Gas Index United Kingdom Pence Per 100000 British ermal Units. Not least, different from prior papers focused on time-frequency connectedness [32,42,55,56,58], our quantitative framework covers several techniques such as GARCH estimation, autoregressive distributed lag (ARDL) models, as well as vector autoregressive (VAR) models.…”

Section: Introductionmentioning

confidence: 89%

“…As well, contrary to prior papers that used the price of WTI crude oil [1-4, 7, 8, 24-26, 29, 33, 35, 39, 43, 45-56], Brent crude oil [4,7,8,15,24,26,36,37,43,44,46,47,49,51,52,[54][55][56], Dubai crude oil [4,8], NYMEX's oil [26,55,57], or carbon futures [14], the current study covers the daily returns of the Physical Electricity Index, Amsterdam Power Exchange Electricity Netherlands Average All Hours and, London Natural Gas Index United Kingdom Pence Per 100000 British ermal Units. Not least, different from prior papers focused on time-frequency connectedness [32,42,55,56,58], our quantitative framework covers several techniques such as GARCH estimation, autoregressive distributed lag (ARDL) models, as well as vector autoregressive (VAR) models. Aside from empirical contributions, our findings have practical implications for policymakers throughout the unprecedented phase of insecurity triggered by the COVID-19 pandemic.…”

Section: Introductionmentioning

confidence: 89%

See 1 more Smart Citation

How Energy Sector Reacted to COVID‐19 Pandemic? Empirical Evidence from an Emerging Market Economy

Armeanu

Joldeș

Gherghina

2022

Discrete Dynamics in Nature and Society

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The European Union is facing the highest natural gas prices in 15 years, owing largely to an upward trend in electricity prices, which is also on an uphill curve. However, the rise in electricity and natural gas prices is a widespread phenomenon that is being felt not only in Europe but also globally, as economic activity resumes and energy consumption returns to prepandemic levels. Consequently, this paper investigates how COVID-19 influenced the Romanian energy market. To accomplish our goal, we used daily data for variables and market indices that characterize COVID-19 and the energy market from July 1 to December 21, 2021. The results of the GARCH (1, 1) model estimation show that the major performer in Romania’s energy allocation and supply market had the highest conditional variance. In addition, the ARDL model was chosen because of the variable integration mix (order 0 and 1), as well as the VAR and the Granger causality framework. The empirical results of ARDL models provide the first conclusion of the analysis, indicating that the number of short-term connections was greater than long-term connections, which is also explained by the presence of short episodes of high volatility recorded in the investigated time interval. Another conclusion drawn from this study is that COVID-19 cases registered in Europe and around the world have made a significant contribution to explaining the evolution of the energy market, owing to the large number of cases registered in these regions and the level of contagion transmitted from these markets to the energy market. Furthermore, based on the Granger causality test results, only one-way causal relationships were identified from the variables that capture the evolution of the COVID-9 pandemic to the yields of Romanian energy companies. The novelty of this article is the examination of the impact of COVID-19 on the energy market throughout the fourth wave of coronavirus using the GARCH framework, the ARDL model, which allows for the capture of both short- and long-term reactions, the variance decomposition, and the Granger causality test. Because of the ongoing changes in the pandemic’s evolution, additional research on this topic is undoubtedly on the horizon in the near future.

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“…Further, Li et al (2021) finds that the COVID-19 outbreak changed the original structure of the industry-related network, directly influencing the consumption and supply of metal and chemical commodities in China. As mentioned above, movements in the prices of these commodities could still interact with each other in the COVID-19 epidemic to shake up China's commodity markets ( Jiang and Chen, 2022 ).…”

Section: Literature Reviewmentioning

confidence: 99%