Search

The challenges of the world economy and their societies, after the outbreak of the COVID-19 pandemic have led policy-makers to seek for effective solutions. This paper examines the oil price volatility response to the COVID-19 pandemic and stock market volatility using daily data. A general econometric panel model is applied to investigate the relationship between COVID-19 infection and death announcements with oil price volatility. The paper uses data from six geographical zones, Europe, Africa, Asia, North America, South America, and Oceania for the period 21 January 2020 until 13 May 2021 and the empirical findings show that COVID-19 deaths affected oil volatility significantly. This conclusion is confirmed by a second stage analysis applied separately for each geographical area. The only geographical area where the existence of correlation is not confirmed between the rate of increase in deaths and the volatility of the price of crude oil is Asia. The conclusions of this study clearly suggest that COVID-19 is a new risk component on top of economic and market uncertainty that affects oil prices and volatility. Overall, our results are useful for policy-makers, especially in the case of a new wave of infection and deaths in the future. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, uncertainty has increased in many areas of both business supply and demand, notably oil demand and pricing have become even more unpredictable than before. Thus, for companies that buy large quantities of oil, effective oil price risk management is crucial for business success. Nevertheless, businesses' risk appetite, specifically willingness to accept more risk to achieve desired business benefits, varies significantly. The aim of this paper is to deepen the analysis of the effectiveness of employing artificial neural networks (ANNs) in hedging against oil price changes by searching for buy signals for European WTI (West Texas Intermediate) crude oil call options, while taking into account the level of risk appetite. The number of generated buy signals decreases with increasing risk appetite, and thus the amount of capital necessary to buy options decreases. However, the results show that fewer buy signals do not necessarily translate into lower returns generated by networks in a given class. Thus, higher levels of return on the purchase of call options may be obtained. The conducted analyses clearly proved that ANNs can be a useful tool in the process of managing WTI crude oil price change risk. Using the analyzed network parameters, up to 29.9% of the theoretical maximum possible profit from buying options every day was obtained in the test set. Furthermore, all proposed networks generated some profit for the test set. The values of all indicators used in the analyses confirm that the ANNs can be effective regardless of the level of risk appetite, so in this respect they may be described as a universal decision support tool. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic storm has struck the world economies and energy markets with extreme strength. The goal of our study is to assess how the pandemic has influenced oil and gas prices, using energy market reactions in the United States and Japan. To investigate the impact of the COVID-19 cases on the crude oil and natural gas markets, we applied the Auto-Regressive Distributive Lag (ARDL) approach to the number of the US and Japanese COVID-19 cases and energy prices. Our study period is from 21 January 2020 to 2 June 2020, and uses the latest data available at the time of model calibration and captures the so-called "first pandemic wave". In the US, the COVID-19 pandemic had a statistically negative impact on the crude oil price while it positively affected the gas price. In Japan, this negative impact was only apparent in the crude oil market with a two-day lag. Possible explanations of the results may include differences in pandemic development in the US and Japan, and the diverse roles both countries have in energy markets. [ABSTRACT FROM AUTHOR]