Impact of COVID-19 outbreak on asymmetric multifractality of gold and oil prices

Influence of environmental technologies and income on the environment in OECD member countries transitioning to low carbon societies

This paper focuses on examining the effects of per capita environmental technology development on the load capacity factor (LCF) within the context of OECD member countries during the period spanning 1990 to 2021. To investigate these relationships, we employ the AMG estimator and FM-LS estimator. Additionally, we explore the validity of the load capacity curve for these countries and estimate the inflection points in the income per capita-environmental sustainability relationship. Our findings lead us to the conclusion that there is no significant impact of environmental technologies on environmental sustainability. Furthermore, we observe a negative influence on the development of environmental technologies, which can be attributed to the negative externalities associated with their implementation and the lack of societal adoption. Moreover, our estimations reveal an inflection point at $45,251.90 in terms of GDP per capita, beyond which the sustainability condition of the studied countries improves.

Evaluating the Safe-Haven Abilities of Bitcoin and Gold for Crude Oil Market: Evidence During the COVID-19 Pandemic

The COVID-19 pandemic poses a serious threat to investors in the crude oil market. Furthermore, investors have an increasing need to find a safe haven in their investment portfolios when facing unprecedented risks in crude oil markets during the COVID-19 pandemic. According to a review of the literature, there are contradictory findings on which investment is the safer haven for the oil market. Therefore, this paper aims to evaluate whether bitcoin is a safer haven for the crude oil market than the commonly used gold during the COVID-19 pandemic. Three spillover measurements based on the time, and frequency domains, and a network framework are employed to quantify the return spillover effects among bitcoin, gold and three major crude oil futures markets. We divide the sample into two periods, pre-COVID-19 and post-COVID-19. The results show that bitcoin has a weak safe-haven effect on the crude oil market only over a short period, while gold maintains a good safe-haven ability for crude oil futures across various time horizons (frequencies), both before and after the outbreak of the COVID-19 pandemic. The findings of this study have important implications for policy-makers, crude oil producers and global investors. In particularly, investors cannot ignore the importance of bitcoin and gold in selecting more profitable portfolio policies when searching for safe-haven assets.

The impact of containment measures and monetary and fiscal responses on US financial markets during the COVID-19 pandemic

This paper analyses the effects of containment measures and monetary and fiscal responses on US financial markets during the Covid-19 pandemic. More specifically, it applies fractional integration methods to analyse their impact on the daily S&P500, the US Treasury Bond Index (USTB), the S&P Green Bond Index (GREEN) and the Dow Jones (DJ) Islamic World Market Index (ISLAM) over the period 1/01/2020-10/03/2021. The results suggest that all four indices are highly persistent and exhibit orders of integration close to 1. A small degree of mean reversion is observed only for the S&P500 under the assumption of white noise errors and USTB with autocorrelated errors; therefore, market efficiency appears to hold in most cases. The mortality rate, surprisingly, seems to have affected stock and bond prices positively with autocorrelated errors. As for the policy responses, both the containment and fiscal measures had a rather limited impact, whilst there were significant announcement effects which lifted markets, especially in the case of monetary announcements. There is also evidence of a significant, positive response to changes in the effective Federal funds rate, which suggests that the financial industry, mainly benefiting from interest rises, plays a dominant role.

Connectedness of COVID vaccination with economic policy uncertainty, oil, bonds, and sectoral equity markets: evidence from the US

We examine the connectedness of the COVID vaccination with the economic policy uncertainty, oil, bonds, and sectoral equity markets in the US within time and frequency domain. The wavelet-based findings show the positive impact of COVID vaccination on the oil and sector indices over various frequency scales and periods. The vaccination is evidenced to lead the oil and sectoral equity markets. More specifically, we document strong connectedness of vaccinations with communication services, financials, health care, industrials, information technology (IT) and real estate equity sectors. However, weak interactions exist within the vaccination-IT-services and vaccination-utilities pairs. Moreover, the effect of vaccination on the Treasury bond index is negative, whereas the economic policy uncertainty shows an interchanging lead and lag relation with vaccination. It is further observed that the interrelation between vaccination and the corporate bond index is insignificant. Overall, the impact of vaccination on the sectoral equity markets and economic policy uncertainty is higher than on oil and corporate bond prices. The study offers several important implications for investors, government regulators, and policymakers.

Did weekly economic index and volatility index impact US food sales during the first year of the pandemic?

We explore the impacts of economic and financial dislocations caused by COVID-19 pandemic shocks on food sales in the United States from January 2020 to January 2021. We use the US weekly economic index (WEI) to measure economic dislocations and the Chicago Board Options Exchange volatility index (VIX) to capture the broader stock market dislocations. We validate the NARDL model by testing a battery of models using the autoregressive distributed lags (ARDL) methodology (ARDL, NARDL, and QARDL specifications). Our study postulates that an increase in WEI has a significant negative long-term effect on food sales, whereas a decrease in WEI has no statistically significant (long-run) effect. Thus, policy responses that ignore asymmetric effects and hidden cointegration may fail to promote food security during pandemics.

Assessing stock market contagion and complex dynamic risk spillovers during COVID-19 pandemic

A very important area where COVID-19 has seriously disrupted is the global financial markets, where stock markets have experienced great turmoil. To shed light on the nature of this turmoil and to characterize nonlinear dynamics in inter-market risk transmission, we formally test the existence of inter-stock market contagion, identify the main channel once the presence of contagion has been established, and assess the upside and downside risk spillovers dynamically focusing on complexity during pre-COVID-19 and post-COVID-19 periods. Applying multiple measures including time-varying conditional value-at-risk based on copula theory, and sample entropy methods, considering a sample covering seven countries (USA, UK, France, Germany, Japan, Brazil, China) during the period from 4 January 2019 to 30 December 2020, we show that contagion is widely present among analysed stock markets with only a few exceptions and that "portfolio rebalancing" as opposed to "wealth constraint" occurs more as the main channel of transmission. All market pairings exhibit significant bilateral upside and downside spillovers after the outbreak of COVID-19. A significant shift in complexity of risk spillover dynamics is evident for most recipient countries following the shock of COVID-19, among which all but China display a downward shift. The findings of this paper could help regulators, politicians, and portfolio risk managers amid the uncertainty created by the COVID-19 pandemic.

Comparing asymmetric price efficiency in regional ESG markets before and during COVID-19

The ever-emerging environmental, social, and governance (ESG) concerns have received significant attention of policymakers, governments, regulation bodies, and investors. Considering the markets volatilities due to economic and financial uncertainties that can drive the informational price inefficiencies across the markets, this study compares the asymmetric price efficiency of regional ESG markets by using an asymmetric multifractal detrended fluctuation analysis before and during COVID-19 crisis. We then examine whether global factors influence the asymmetric efficiency of regional ESG markets. Our findings reveal that COVID-19 outbreak reduced the efficiency of regional ESG markets, except for Europe, which sustained its efficiency even during the pandemic. Moreover, global factors drive the efficiency of regional ESG markets significantly before and during COVID-19. A major implication of our findings stems from the fact that a contagion reduces the efficiency of the markets while stable economic conditions make those markets informationally efficient.

COVID-19 and China commodity price jump behavior: An information spillover and wavelet coherency analysis

Jumps in commodity prices can make asset risk management challenging. This study explores the influence feature of the COVID-19 epidemic on China's commodity price jumps, using 5-min intraday high-frequency futures data of three China's commodity markets (energy, chemical, and metal) from January 23, 2020 to June 10, 2022. We find that firstly the information spillover from the COVID-19 spread situation to China's energy price jumps is relatively weak, and the COVID-19 epidemic shows the most substantial jump information spillover pattern to China's chemical price. The information spillover pattern is time-varying across the COVID-19 spread situation phase. Secondly, there are co-movement patterns between China's commodity price and China/global COVID-19 confirmed cases. This co-movement feature mainly occurs at the medium- or long-run time scales, and varies across commodities. Thirdly, the demand elasticity for China's commodities and its dependence on imports and exports are the main factors influencing the sensitivity of its price jumps to the COVID-19 outbreak.

Green stocks, crypto asset, crude oil and COVID19 pandemic: Application of rolling window multiple correlation

The COVID-19 pandemic disrupted almost all spares of global social, psychological, and economic life. The emergence of various variants and corresponding variations in daily infection asymmetrically influenced economic indicators. This study extends the existing literature by exploring the hedging potential of crude oil, carbon efficiency index of green firms, and bitcoin during this pandemic. This objective is realized by employing the recently advanced rolling window multiple correlation of Polanco-Martínez (2020). This approach is based on the new p-value corrected method, which has advantages over other correlation methods. The sample observations are based on daily data from 1/22/2020 to 12/20/2021. In the bivariate case, we find a significant positive correlation between COVID-19 and CEI, while a negative impact is observed between COVID-19 and WTI. Similarly, we observe a significant and nonlinear association between COVID-19 and BTC. However, our findings show positive and significant correlations among variables in the multivariate case. The overall findings show that CEI and BTC can be safe havens for investors during this worse pandemic. The study's robust findings can be used to derive important policy implications worldwide during the COVID-19 pandemic.

Does COVID-19 pandemic event alter the dependence structure breaks between crude oil and stock markets in Europe and America

This article attempts to investigate the influence of novel coronavirus (COVID-19) pandemic on the dependence structure break between crude oil and stock markets in Europe and America using ARMA-GARCH and R-vine copula methods. The empirical results demonstrate that international crude oil and European (American) stock markets have significant asymmetric and symmetric dependence structure, rapid outbreak of COVID-19 pandemic triggers their dependence structure break. The results of Kendall correlation confirms that COVID-19 pandemic amplifies the dependence risks between European Brent crude oil and France (German and Spain) stock markets and reduces the dependence risk between Brent crude oil and UK (Italy) stock markets after February 20, 2020. The COVID-19 pandemic may amplify the dependence risk between West Texas Intermediate (WTI) crude oil and Canada stock markets after March 23, 2020, it first quickly reduces the dependence risks between WTI crude oil and US (Brazil and Mexico) stock markets after March 23, 2020 and then enlarges their dependence risks after June 30, 2020. European and American crude oil and stock markets have induced different ranges of their dependence risks in different time scales and their dependence structure breaks have good robustness.

Pricing efficiency and asymmetric multifractality of major asset classes before and during COVID-19 crisis

We examine the impact of COVID-19 pandemic crisis on the pricing efficiency and asymmetric multifractality of major asset classes (S&P500, US Treasury bond, US dollar index, Bitcoin, Brent oil, and gold) within a dynamic framework. Applying permutation entropy on intraday data that covers between April 30, 2019 and May 13, 2020, we show that efficiency of all sample asset classes is deteriorated with the outbreak, and in most cases this deterioration is significant. Results are found to be robust under different analysis schemes. Brent oil is the highest efficient market before and during crisis. The degree of efficiency is heterogeneous among all markets. The analysis by an asymmetric multifractal detrended fluctuation analysis (A-MF-DFA) approach shows evidence of asymmetric multifractality in all markets which rise with the scales. The inefficiency is higher during downward trends before the pandemic crisis as well as during COVID-19 except for gold and Bitcoin. Moreover, the pandemic intensifies the inefficiency of all markets except Bitcoin. Findings reveal increased opportunities for price predictions and abnormal returns gains during the COVID-19 outbreak.

The role of cryptocurrencies in predicting oil prices pre and during COVID-19 pandemic using machine learning

This study aims to explore the role of cryptocurrencies and the US dollar in predicting oil prices pre and during COVID-19 pandemic. The study uses three neural network models (i.e., Support vector machines, Multilayer Perceptron Neural Networks and Generalized regression neural networks (GRNN)) over the period from January 1, 2018, to July 5, 2021. Our results are threefold. First, our results indicate Bitcoin is the most influential in predicting oil prices during the bear and bull oil market before COVID-19 and during the downtrend during COVID-19. Second, COVID-19 variables became the most influential during the uptrend, especially the number of death cases. Third, our results also suggest that the most accurate model to predict the price of oil under the conditions of uncertainty that prevailed in the world during the bear and bull prices in the wake of COVID-19 is GRNN. Though the best prediction model under normal conditions before COVID-19 during an uptrend is SVM and during a downtrend is GRNN. Our results provide crucial evidence for investors, academics and policymakers, especially during global uncertainties.

Coronavirus pandemic impact on bank performance

This study examines the effects of the coronavirus (COVID-19) epidemic on the performance of the banking sector. Our sample consists of 1,575 banks in 85 countries from 2020Q1 to 2021Q4. The findings demonstrate that the COVID-19 outbreak has significantly decreased bank performance. Moreover, the adverse impact of COVID-19 on the bank's performance depends on the bank's and country-specific aspects. The adverse effect of the COVID-19 outbreak on bank performance is higher in smaller, undercapitalized, and less diversified banks. At the same time, a better institutional environment and financial development have significantly increased the strength and resilience of banks. The results are quite robust to using the alternative bank performance measures and estimation techniques. These findings provide practical implications for regulators and policymakers in the face of unprecedented uncertainty caused by COVID-19 epidemics.

COVID-19 impact on multifractality of energy prices: Asymmetric multifractality analysis

This article assesses the asymmetric multifractality of the energy prices in the different periods during the coronavirus pandemic (COVID-19) through asymmetric multifractality detrended fluctuation analysis. The higher (lower) multifractality shows a rapid rise (fall), which has different consequences for the energy prices. The findings explore strong multifractality in the downward movements for crude oil, heating oil, diesel, gasoline, propane and kerosene oil returns. The upside multifractality for coal and natural gas returns are bigger than the downside in both periods. Furthermore, the access asymmetry is more pronounced during the COVID-19, implying increased market inefficiency. The outcomes explore if energy prices are inefficient during the pandemic. A special attention is required in order to observe such unexpected fluctuations in the price dynamic and guidelines are vital. The level of efficiency can be improved by a greater transference in information while the government must play its role in regulations. Such aspects can increase stability and decrease the expected risks and price movements.

Global pandemic crisis and risk contagion in GCC stock markets

This study investigates how the COVID-19 outbreak has shaped the volatility spillover between oil and Gulf Cooperation Council (GCC) stock markets. Contagion analysis is conducted by implementing a vector error correction (VECM) asymmetric BEKK model, wherein both cointegration and asymmetric features are considered. Financial market uncertainty caused by the recent health crisis is captured using Baker et al.'s (2020) newly developed infectious disease tracker. Our results indicate a significant discrepancy in the GCC group, as shock and volatility linkages between oil and equities are more apparent for some countries but not for others. The estimated VECM-asymmetric BEKK model reveals cross-market asymmetric spillover effects only in Kuwait, Qatar, and Saudi Arabia. We report that the global pandemic has strongly affected crude oil market volatility, while the GCC region seems to be less affected by the emergence of the new infectious disease. Our findings underscore the diversification opportunities offered by Gulf equity markets to international investors.

How does the COVID-19 outbreak affect the causality between gold and the stock market? New evidence from the extreme Granger causality test

The causal relationship between gold and stocks has been widely studied, while their causality and the long- and short-run characteristic of this relationship have not been examined under different shocks. The purpose of this paper is to fill this gap. Meanwhile, considering the impact of the COVID-19 outbreak on gold and stock markets, we also aim to investigate whether the relationship changes after this epidemic. With invoking the time- and frequency-domain extreme Granger causality tests, we find that a significant causality between gold and stock usually comes from extreme shocks, displaying as the long-term causality running from gold shocks to stock shocks while the fickle impact of stock shocks on gold shocks. Besides, empirical results suggest that the causality between gold and stock shocks is greatly promoted after this epidemic. The present study is useful for investors and policymakers, as it has reference significance when dealing with subsequent extreme shocks or events.

Comparing the asymmetric efficiency of dirty and clean energy markets pre and during COVID-19

In the backdrop of the recent COVID-19 pandemic, the study examines the comparative asymmetric efficiency of dirty and clean energy markets pre and during the COVID-19 pandemic. For this purpose, we utilize an asymmetric multifractality detrended fluctuation analysis (A-MF-DFA). The study's findings uncover the presence of asymmetric multifractality in clean and dirty energy markets. In addition, multifractality in the energy markets is sensitive to trends, time horizon and major events. More importantly, the results suggest superior efficiency of clean-energy markets compared to conventional energies. We confirm the time-varying nature of market efficiency in the energy markets, and during the recent COVID-19 outbreak, market inefficiencies in the clean and dirty energy markets soared. In this way, the study holds meaningful insights for policymakers, energy policy practitioners, investors, and financial market participants to choose between clean (dirty) investments based on their asymmetric efficiency (inefficiency).

Public attention, oil and gold markets during the COVID-19: Evidence from time-frequency analysis

This paper uses time-frequency analysis, including wavelet analysis and time-frequency domain causality, to evaluate the relationship between public attention to the COVID-19 pandemic, crude oil, and gold markets in the G7 countries over time and frequency. Empirical findings show that WTI oil lead gold returns during the COVID-19 outbreak, and vice versa when Omicron spread. The relationship between public attention to the COVID-19 and WTI oil/gold markets appears to be heterogeneous for G7 countries. European public attention caused by the COVID-19 outbreak has a strong impact on gold returns at the 32-64 day frequency, while public attention generated by Omicron has a significant effect on WTI oil returns at 4-128 day frequency. The public in the US and Canada is more concerned about the global stock and WTI oil markets slump than the COVID-19 pandemic. The Italian public seems to be the most sensitive to the EU's economic support plan. The heterogeneity of the public attention-oil/gold nexus in the G7 implies that portfolio diversification across markets and investment horizons may be extremely beneficial.

The relationship between global stock and precious metals under Covid-19 and happiness perspectives

In this paper, we examine the relationship between global stock markets, as respectively represented by the FTSE All-World Series and the MSCI Emerging Markets indexes, and the S&P GSCI Precious Metals index from 01 September 1999 to 03 May 2021. We employ the conditional correlation multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) to investigate this stock-precious metals nexus in terms of return and volatility spillovers. The study assesses impacts of the Covid-19 pandemic on the stock-precious metals nexus and further examine this relationship by supplementing the Twitter's Daily Happiness Sentiment index to the methodological framework for the period from 01 January 2020 to 03 May 2021. We find that precious metals positively influence stock markets before the Covid-19 outbreak and firmly play a valuable role due to their hedge and safe haven characteristics. In contrast, the bivariate GARCH framework does not provide statistically significant evidence on the stock-precious metals nexus during the Covid-19 pandemic. Meanwhile, the tri-variate GARCH approach with stock markets, precious metals, and happiness sentiment indexes reveals sufficiently complicated interactions between these return series. Prominently, past change in the happiness index negatively affects the stock returns but positively drives the performance of precious metals. These findings indirectly demonstrate the stock-precious metals nexus under impacts of the Covid-19 pandemic and reflect the demand of precious metals during crisis periods. Accordingly, we suggest a reasonable method of adjusting the proxies when no interaction effect is significantly found during unprecedented outbreaks.

Does COVID-19 pandemic cause natural resources commodity prices volatility? Empirical evidence from China

COVID-19 pandemic caused havoc around the globe in both economic and non-economic sectors. This paper, unlike previous studies, evaluates the role of COVID-19 on the volatility in natural resources. The volatility of natural resources commodity prices has been the center of discussion, especially during the pandemic. Unlike previous studies, this study aims to evaluate the role of the pandemic, i.e., Covid-19 and its possible impact on volatility in natural resources commodity prices for China. China has been the center of this epidemic disease and is considered one of the major economies affected by the Covid-19; therefore, it is better to conduct this study for China. This study uses data from January 2020 till September 2021 to capture the peak time of Covid-19. Moreover, this study employs the novel wavelet power spectrum and wavelet coherence approach to better capture volatility within commodity prices volatility and Covid-19 and evaluate the association between both variables. The empirical results reveal that only natural resources commodity prices are volatile and only short. While Covid-19 positive cases and Covid-19 deaths are not vulnerable during the study period. Moreover, the wavelet coherence conforms that both Covid-19 positive cases and Covid-19 deaths significantly cause volatility in natural resources commodity prices. Although, volatility is found at different periods; still, volatility is observed only in the short-run. The study also provides relevant policy implications to ensure a relevant and timely solution for the existing issue. Moreover, future research guidelines and the study's limitations are also provided.

COVID-19 Shock and the Time-Varying Volatility Spillovers Among the Energy and Precious Metals Markets: Evidence From A DCC-GARCH-CONNECTEDNESS Approach

The outbreak of the COVID-19 epidemic intensified the volatility of commodity markets (the energy and precious metals markets), which created a significant negative impact on the volatility spillovers among these markets. It may also have triggered a new volatility risk contagion. In this paper, we introduce the DCC-GARCH-CONNECTEDNESS approach to explore the volatility spillover level and multi-level spillover structure characteristics among the commodity markets before and during the COVID-19 epidemic in order to clarify the new volatility risk contagion patterns across the markets. The results implied several conclusions. (i) The COVID-19 epidemic has significantly improved the total volatility spillover level of the energy and precious metals markets and has enhanced the risk connectivity among the markets. (ii) The COVID-19 epidemic has amplified the volatility of the crude oil market, making it the main volatility spillover market, namely the source of volatility risk contagion. (iii) The COVID-19 epidemic outbreak enhanced the external risk absorption capacity of the natural gas and silver markets, and the absorption level of the external volatility spillover improved significantly. Furthermore, the risk absorption capacity of the gold market weakened, while the gold market has remained the endpoint of external volatility risk during the epidemic and has acted as a risk stabilizer. (iv) The volatility spillover among markets has clear time-varying characteristics and a positive connectedness with the severity of the COVID-19 epidemic. As the severity of the COVID-19 epidemic increases, the volatility risk connectivity among the markets rapidly increases.

A singular value decomposition entropy approach to assess the impact of Covid-19 on the informational efficiency of the WTI crude oil market

This work investigates the impact of the Covid-19 outbreak on crude oil market efficiency. The approach is based on the singular value decomposition (SVD) entropy. Iso-distributional surrogate data test was used to contrast the results against random patterns, and phase randomization based on Fourier transform was used to assess nonlinearities. The analysis considered the WTI market and focused on the Covid-19 pandemic period January 2020-November 2021 and contrasted with the long preceding period from January 2000 to date. It was found that the crude oil market was informationally efficient most of the time with small sporadic deviations from efficiency in the pre-Covid-19 years. The Covid-19 period exhibited the largest deviations from efficiency, mainly in the first months of the outbreak, accompanied by a marked reduction of nonlinear components. The analysis was conducted for different scales, and the results showed that the deviations from efficiency were more pronounced for quarterly scales. For the sake of comparison, the analysis was also carried out on the trading volume dynamics and the results showed that the market activity is not fully random. The dynamics of the trading volume exhibited significant deviations from the randomness behavior when the crude oil market was efficient, and a behavior that was consistent with nonlinear patterns. The opposite behavior was noted for stages when the crude oil market showed strong deviations from efficiency. Overall, the findings of this study suggest an increasing opportunity for crude oil price predictions and abnormal returns during the Covid-19 pandemic.

Corporate investment and government policy during the COVID-19 crisis

We investigate the impact of the US government response to the COVID-19 pandemic, including stringent social measures and economic support packages, on corporate investment. The empirical results show that despite the overall decreased investment due to the economic impact of the pandemic, the government response to COVID-19 and economic supports have a positive effect on corporate investment after subtracting the impact of the pandemic on firm-level investment. We find that the impact of economic support packages on corporate investment is stronger than that of health containment policies. Further analyses show that the effect is weak in firms with higher levels of political risk and investment irreversibility, while being more pronounced in firms with higher technology intensity. Our findings provide fresh insights into the firms’ reaction to the government policies during the pandemic and suggest that both social measures and economic support are vital to restoring corporate investment as well as the economic recovery process.

Are effects of COVID-19 pandemic on financial markets permanent or temporary? Evidence from gold, oil and stock markets

The purpose of this study is to examine the effect of COVID-19 pandemic on gold, oil, conventional and Islamic stock markets. Two variables as the number of new COVID-19 cases and Infectious Disease Equity Market Volatility (IDEMV) Index developed by Baker, Bloom, Davis and Kost (2019) are used in order to discuss the effect of COVID-19 pandemic. Other variables used in the research are oil prices, gold prices and S&P Dow Jones Index values for conventional and Islamic stock markets. The data set used in the study is the daily data set between 31st December 2019 and 5th May 2020 for all variables. Time and frequency domain causality test is used in the study. According to the study results, there is a permanent causality in long term between stock markets, gold and oil prices and the number of COVID-19 cases. There is also a permanent causality in long term between IDEMV and gold and oil prices. However, in short term, there is a temporary causality between gold and oil prices and the number of COVID-19 cases. These results are highly important especially for policy performers and portfolio managers to determine the portfolio strategies.

Tracking safe haven properties of cryptocurrencies during the COVID-19 pandemic: A smooth transition approach

The study aims to examine the hedge and safe-haven properties of three heavyweight cryptocurrencies-Bitcoin, Ripple, and Ethereum-against the stock, commodity, and foreign exchange markets. The study sample covers the period of August 2011 to September 2020 and therefore includes the current coronavirus disease-2019 (COVID-19) crisis. Using a logistic smooth transition regression model (LSTR2), the study findings indicate the ability of monitored cryptocurrencies to act as safe-haven assets, but such behavior differs across markets. Interestingly, during the pandemic period, Ethereum provides the strongest safe haven function for the commodity market. According to our findings, we are mindful of that the COVID-19 outbreak provides an exciting opportunity to advance our knowledge of the prominence of new coins such as Ethereum that are gradually gaining supremacy in the cryptocurrency market to the detriment of traditional cryptocurrencies like Bitcoin.

Co-movements in sector price indexes during the COVID-19 crisis: Evidence from the US

This paper is an examination of co-movements between sector indexes in the United States prior to and during the COVID-19 period. Using daily data between January 2013 and July 2020, this study is the first to examine sectoral cointegration, as well as how contagion occurs from one healthcare sector to others. We find that only five sectors reacted to the shock to the healthcare sector. Our findings can assist policymakers in appropriately responding to the current crisis and tackling potential pandemics in the future. Our findings are also valuable for stockholders in terms of predicting price changes and improving portfolio diversification.

Why Was There More Household Stock Market Participation During the COVID-19 Pandemic?

Although the nation was experiencing an economic downturn due to the COVID-19 pandemic outbreak, we nonetheless observed an increase in household equity share value relative to both domestic market capitalization and retail investors' trading volume. In this paper, we aim to interpret the reasons underlying this seemingly unexpected phenomenon. We investigate portfolio choices with stocks, bonds, and life annuities under an inverse S-shaped probability distortion function. The results indicate that people invest more heavily in risky assets and buy more annuities when reducing their savings in risk-free accounts, which is indeed consistent with the reality.

Oil and Gas Markets and COVID-19: A Critical Rumination on Drivers, Triggers, and Volatility

The paper endeavours to explore and analyse some critical issues in the oil and gas market that cropped up around the spread of COVID-19 and tries to identify the key drivers and triggers pertaining therewith. The spread of the first wave that began in March 2020 is crucial because of the global economic downturn that ensued due to lockdown and imposed restrictions coupled with a protracted oil price war that began between Saudi Arabia and Russia. The paper tries to address some key research questions to understand the triggers and drivers around the pandemic. These are: (1) whether the behaviour of OPEC or its key players around the pandemic could be considered uniquely different; (2) what could the triggers be for the increased volatilities that cropped up in both physical and financial markets during the pandemic; (3) what was really different about the oil market crisis around the pandemic that transformed it to an unprecedented storage crisis; (4) what really went wrong with the much-hyped U.S. shale boom during the pandemic that led to the bankruptcy of several oil and gas companies, followed by huge job losses. The paper relies on a structured review of relevant secondary literature to address these exploratory questions and builds upon a retrospective rumination on the world oil market from 1960 to 2020. This is complemented by an analysis of supporting data and evidence obtained from various sources. Considering the intertwining of oil and financial markets around the pandemic, the lessons and findings from the paper would not only be highly relevant for policymakers and stakeholders in the oil and gas sector but would be equally relevant for those in the financial markets.

Causal inference for the impact of economic policy on financial and labour markets amid the COVID-19 pandemic

The COVID-19 pandemic has turned the world upside down since the beginning of 2020, leaving most nations worldwide in both health crises and economic recession. Governments have been continually responding with multiple support policies to help people and businesses overcoming the current situation, from “Containment”, “Health” to “Economic” policies, and from local and national supports to international aids. Although the pandemic damage is still not under control, it is essential to have an early investigation to analyze whether these measures have taken effects on the early economic recovery in each nation, and which kinds of measures have made bigger impacts on reducing such negative downturn. Therefore, we conducted a time series based causal inference analysis to measure the effectiveness of these policies, specifically focusing on the “Economic support” policy on the financial markets for 80 countries and on the United States and Australia labour markets. Our results identified initial positive causal relationships between these policies and the market, providing a perspective for policymakers and other stakeholders.

Does oil impact gold during COVID-19 and three other recent crises?

The ongoing COVID-19 pandemic has inspired an examination of the oil-gold prices nexus during four recent crises: the COVID-19 pandemic, the gold market crash, the European sovereign debt crisis, and the global financial crisis. Using daily data from May 2007-August 2021, we employ the nonlinear autoregressive distributed lag method to reveal five novel findings. First, this study contrasts with much of the literature, which infers that the relationship between oil and gold prices is strongly positive. Second, we find no oil and gold price relationship in the long term during all the crisis periods. Third, oil prices have substantially lost their power to predict gold prices in recent times and the oil-gold price linkage is not functional across all crisis periods. Fourth, in the short term, only negative Brent and negative West Texas Intermediate price changes cause positive gold price changes during the pandemic and gold market crash, respectively. Fifth, Brent prices have shown no link to gold prices before COVID-19. We argue that gold prices are less sensitive to oil prices than ever, and the uncertainty resulting from the COVID-19 crisis has attracted investors to gold. Our main findings hold under robustness analyses using fractional cointegration/integration models, lag length, and heteroskedasticity-consistent standard errors.

The Impact of COVID-19 on China's Capital Market and Major Industry Sectors

This paper studies the impact of COVID-19 on China's capital market and major industry sectors via an improved ICSS algorithm, a time series model with exogenous variables and nonparametric conditional probability estimation. Through the empirical analysis of the stock market, the bond market and different industry sectors, it is found that the pandemic has had no significant impact on the return of the stock and bond markets; however, it has increased market volatility. There are significant differences in the significance, direction and duration of the impact of the pandemic in different sectors. In addition, the impacts of COVID-19 have been gradual in some industries but rapid in others. Different industries show different sensitivities in their response to COVID-19. Based on the impact analysis, this paper proposes corresponding suggestions for investment strategies and macrocontrol decisions.

Responses of the International Bond Markets to COVID-19 Containment Measures

Using an international sample during the COVID-19 outbreak, our study gives evidence that COVID-19 containment measures impact volatility in the international bond markets in different ways. We found that the positive effect of increasing new COVID-19 vaccinations markedly mitigates bond market volatility, while non-pharmaceutical government interventions resembling bad news increase volatility in bond markets. Besides this, changes in total COVID-19 cases and total deaths have co-movement and a significant relationship with this volatility. Our results imply that the investors’ responses to the trigger of increased uncertainty seem to differ in a way that depends on bad or good news as a reflection of the possibility of pandemic control and the health of the economy. The mass vaccinations not only signal a lower probability of stringent government responses to the pandemic but also stabilize investors’ behavior and mitigate compliance fears to open a period of safe living with coronavirus. Our findings are still robust when using alternative measures of independent variables and different forecasting models of conditional volatility.

Practice-relevant model validation: distributional parameter risk analysis in financial model risk management

An objective of model validation within organisations is to provide guidance on model selection decisions that balance the operational effectiveness and structural complexity of competing models. We consider a practice-relevant model validation scenario where a financial quantitative analysis team seeks to decide between incumbent and alternative models on the basis of parameter risk. We devise a model risk management methodology that gives a meaningful distributional assessment of parameter risk in a setting where market calibration and historical estimation procedures must be jointly applied. Such a scenario is typically driven by data constraints that preclude market calibration only. We demonstrate our proposed methodology in a natural gas storage modelling context, where model usage is necessary to support profit and loss reporting, and to inform trading and hedging strategy. We leverage our distributional parameter risk approach to devise an accessible technique to support model selection decisions.

Information spillover effects from media coverage to the crude oil, gold, and Bitcoin markets during the COVID-19 pandemic: Evidence from the time and frequency domains

Many scholars have explored the COVID-19 impact on the crude oil, gold, and Bitcoin markets, whereas most have ignored the media coverage influence. This paper focuses on examining information spillover from epidemic-related news to the crude oil, gold, and Bitcoin markets with the time-frequency analysis method. The empirical results reveal that both the return and volatility spillovers from epidemic-related news to the crude oil, gold, and Bitcoin markets are stronger in the short term (less than 1 week). In the long term, only the media sentiment index notably impacts crude oil, gold, and Bitcoin market returns. The volatility spillover from media coverage to crude oil mainly occurs in the short term. Regarding the gold and Bitcoin markets, the long-term volatility spillovers are significant. An obvious risk contagion path is found. Media hype is the main risk transmitter and transmits vast shocks to these three markets, especially the Bitcoin market, which subsequently transmits these shocks to the gold market. Risk accumulates systemically in the gold and Bitcoin markets. These findings have crucial empirical implications for policymakers and investors when formulating related short- or long-term decisions during the pandemic.

COVID-19 media coverage and ESG leader indices

This study examines the dynamic connectedness between COVID-19 media coverage index (MCI) and ESG leader indices. Our findings provide evidence that MCI plays a role in facilitating the transmission of contagion to advanced and emerging equity markets during the pandemic. The connectedness between MCI and ESG leader indices is more pronounced around March and April 2020 at the peak of the pandemic. The US is a net receiver of shocks reaffirming that it was the most affected country during the pandemic. Our results provide implications for investors, portfolio managers, and policymakers in mitigating financial risks during the pandemic.

Do Commodities React More to Time-Varying Rare Disaster Risk? A Comparison of Commodity and Financial Assets

Using a rare disaster risk database from almost the last one hundred years, we examine the differences in the reaction of asset prices to rare disaster risk between commodity and financial assets. We first employ time-varying parameter VAR (TVP-VAR) models to investigate the role of rare disaster risk in the price dynamics of major asset markets. The results indicate that disaster risk generally has a more intense and persistent impact on crude oil and stock markets when compared to gold and bond markets. However, the role of rare disaster risk differs substantially between commodity and financial assets, as well as between the short and long term. Moreover, when using a nonparametric causality-in-quantiles method to detect causal relationships, we provide evidence of the nonlinear causality effect of rare disaster risks on asset volatilities, and not their returns, except for crude oil. In addition, we demonstrate that augmenting a diversified portfolio of stock or bonds with gold can significantly increase its risk-adjusted performance. The findings have important implications for investors as well as policymakers.

Examining the behaviour of energy prices to COVID-19 uncertainty: A quantile on quantile approach

The energy market is extremely vulnerable to the uncertainty caused by the pandemic and leads to global lockdowns and stagnant economic activity. This study is important because energy prices (EPs) experience a dramatic decline due to the pandemic, which has negative consequences for the global economy. We aim to analyze EPs behaviour to coronavirus (COVID-19) from 2020:01 to 2021:05. The finding shows that EPs are extremely vulnerable to the uncertainty produced by the pandemic in the short run. The COVID-19 has a negative effect on EPs in the medium to upper quantile, which suggests that higher uncertainty caused by the pandemic results in rapid decline. However, the impact of the COVID-19 is greater on the oil prices (OPs) as compared to the natural gas (NGP) and the heating oil price (HOP). Moreover, the finding reveals that COVID-19 impact on EPs are consistently negative across all the quantile. The degree of the impact increases when the relationship changes from short to long run. The pandemic has affected the energy price in the short run, which needs prudent policies to fully grasp the magnitude of the COVID-19 impact on energy prices.

COVID-19 Vaccination Effect on Stock Market and Death Rate in India

The COVID-19 epidemic has brought attention to the vulnerability of new illnesses, and immunization remains a viable option for resuming normal life. This paper examines the influence of COVID-19 vaccination on the death rate and the performance of stock market in India. For this study, COVID-19 vaccination and death rate data is gathered from the Ministry of Health and Family Welfare (MoHFW) portal, and the data for the stock index is taken from the Bombay Stock Exchange (BSE), India. In order to achieve a precise representation of feature significance and distribution, EDA (Exploratory Data Analysis) is utilized in this study. The impact of COVID-19 immunization on the mortality rate and stock market index is investigated using both statistical analysis and Machine Learning Regression-based models. The models are remarkably accurate in reproducing actual result. The empirical study suggests that vaccination has a strong positive impact on the stock market and reducing the death rate. Furthermore, the policies recommended by government and monetary authorities coupled with COVID-19 vaccine supported the stock market recovery in pandemic.

The persistence of precious metals and oil during the COVID-19 pandemic: evidence from a fractional integration and cointegration approach

In this paper, the behavior of precious metals and oil is examined using a fractionally integrated and cointegrated modeling approach. Using daily data from January 2015 to December 2020 and using both endogenous and exogenous structural breaks, we examine the behavior of the related series before and during the COVID-19 pandemic with the aim of investigating whether the degree of persistence has changed since the onset of COVID-19. We found that precious metals and oil exhibit long memory and are mean reverting regardless of the sample considered as the fractional parameter d < 0.5. However, when structural breaks are taken into consideration, an increase in persistence is found during the COVID-19 as compared to the period before it. In addition, the fractionally cointegrated vector autoregressive (FCVAR) model of Johansen and Nielsen (2010, 2012) is used to examine the existence of long-run relationship among precious metals and oil price. We find the integrated parameters at d < 0.5 for all samples except for the pre-COVID-19 sample. This highlights that the FCVAR is a better fit for the full sample and the COVID-19 and the COVID-19 pandemic period sub-samples, as the fractional parameter is d < 0.5 while the CVAR model is better fit for the pre-COVID-19 period where d> 0.5. Both cointegration techniques alongside the parameter stability tests lend support to the existence of a persistence and stable long-run relationships among the series irrespective of the sample period considered. Attendant policy recommendations for investors and policymakers are recommended.

The impact of the COVID-19 pandemic on the energy market – A comparative relationship between oil and coal

The COVID-19 epidemic has severely affected the world economy and energy markets. In order to alleviate the shock, stabilize the financial market, and promote economic recovery, the Fed announced an unlimited QE policy. In order to understand the impact of the policy on the energy market under the extreme events, the study selected WTI crude oil and coal prices from January 1, 2018 to May 7, 2021 as the research objects. Taking the two years before the epidemic, the epidemic stage was further divided into four small stages according to the three peaks of the epidemic in the US. The MF-DCCA model calculations show that coal and WTI crude oil have an interactive relationship. The risks between them are not just averaged and superimposed, but transmitted and interacted.The MF-DFA model calculation results show that due to the disorder of energy supply and demand under the epidemic, market efficiency in the first quarter of 2020 has dropped rapidly. However, market efficiency decoupled from the development of the epidemic in the second half of 2020. Especially after the announcement of the QE policy, market efficiency has improved significantly. However, under the excessive monetary policy, market efficiency declined in the first half of 2021. This shows that the policy has a certain effect on alleviating the impact of the epidemic on the energy market. But this improvement is not sustainable from the long term. As prices rise, inflation continues. In the future, the volatility and risk of the energy futures market will increase.

Stock market volatility and the COVID-19 reproductive number

The media has prominently featured the totemic reproductive number R in its COVID-19 coverage despite being an imperfect measure of the degree of infectivity of the virus. As such, it conveys information to the public regarding the state of the pandemic that affects market sentiment. We analyze how news about R affects the volatility in stock markets worldwide and find that when R is greater than one, which means the spread of the disease should soar, it has a positive and significant effect on volatility. Our results hold after controlling for government interventions and several robustness checks.

Sovereign Bond Market Shock Spillover Over Different Maturities: A Journey from Normal to Covid-19 Period

With application of Diebold and Yilmaz’s (Int J Forecast 28(1):57–66, 2012) spillover approach, we examine shock spillover in international sovereign bond yields over short, medium, and long term maturities for major eight economies. By scrutinizing the data from 1st January 2013 to 12th November 2020, we explored that irrespective of pre-covid-19 or covid-19 period, shock spillover in bond yields across markets are much stronger over long and medium maturities relative to short-term maturity. Moreover, shock spillover of bond yields has amplified manifold during Covid-19, irrespective of their maturities compared to pre-Covid-19 period. The magnitude of shock spillovers remains low with short-term maturity. Assessing the relationship between international sovereign bond markets (SBMs) contributes to our understanding and is also crucial to the investors (both domestic and foreign) in investing in SBMs.

COVID-19 Vaccinations and the Volatility of Energy Companies in International Markets

The COVID-19 pandemic has elevated both the risk and volatility of energy companies. Can mass vaccinations restore stability within this sector? To answer this question, we investigate stock market data from fifty-eight countries from January 2020 to April 2021. We document that vaccination programs assist in decreasing the volatility of energy stocks around the world. The drop in volatility is statistically and economically significant and robust to many considerations. The observed phenomenon survives a broad battery of control variables; it is also independent of the employed regression model or the volatility measurement approach. Moreover, the effect is not driven by the dynamics of the pandemic itself or the associated government interventions. Finally, we find the influence of vaccinations on energy stock volatility to be more pronounced in developed markets rather than in emerging ones. Our findings bear clear practical implications: policy makers around the world should consider the essential role of vaccinations in the energy sector.

Can Major Public Health Emergencies Affect Changes in International Oil Prices?

In order to deepen the understanding of the impact of major public health emergencies on the oil market and to enhance the risk response capability, this study analyzed the logical relationship between major public health emergencies and international oil price changes, identified the change points, and calculated the probability of abrupt changes to international oil prices. Based on monthly data during six major public health emergencies from 2009 to 2020, this study built a product partition model. The results show that only the influenza A (H1N1) and COVID-19 pandemics were significant reasons for abrupt changes in international oil prices. Furthermore, the wild poliovirus epidemic, the Ebola epidemic, the Zika epidemic, and the Ebola epidemic in the Democratic Republic of the Congo had limited effects. Overall, the outbreak of a Public Health Emergency of International Concern (PHEIC) in major global economies has a more pronounced impact on international oil prices.

Impact of COVID-19 on stock market efficiency: Evidence from developed countries

This study investigates the impact of the novel coronavirus (COVID-19) pandemic on stock market efficiency for six hard-hit developed countries, namely, the United States (US), Spain, the United Kingdom (UK), Italy, France, and Germany. Applying the wild bootstrap automatic variance ratio test on daily stock market data from July 29, 2019 to January 25, 2021, it is found that all stock markets used in this study deviate from market efficiency during some periods of the pandemic. Deviations from market efficiency are seen more in the stock markets of the US and UK during the COVID-19 outbreak than in other stock markets. These results are strengthened when a different econometric method, the automatic portmanteau test, is used. The findings of this study indicate an increasing chance for stock price predictions and abnormal returns during the COVID-19 pandemic.

Impact of COVID-19 outbreak on multi-scale asymmetric spillovers between food and oil prices

This paper analyzes the time-frequency spillover effects between food and crude oil markets, two particularly important commodity markets, under the impact of the pandemic. Using the BK frequency domain spillover index and the rolling window method, we explore the spillover effects between the food and crude oil markets under the influence of COVID-19, and compare the changes of spillover effects in each market before and during the pandemic. Based the network connectedness method and the Bayesian structural time series method, we further reveal the changes of the pairwise spillover effects between markets on different time scales. Our study shows that the food-oil market system has the strongest spillover effect in the short term, and the spillovers during the pandemic are significantly weaker than that under the financial crisis. In addition, the pandemic has significantly increased the impact of corn on the crude oil market, but reduced its spillovers on soybeans and rice. Finally, during the COVID-19 period, the wheat market is likely to receive more spillovers from other markets, particularly corn and soybeans. These findings are of great significance for market participants with different horizons to understand the spillover effects of food and oil markets under the impact of the pandemic and to avoid the risk transmission across markets or assets.

The historic oil price fluctuation during the Covid-19 pandemic: What are the causes?

On 20 April 2020, the West Texas Intermediate (WTI) crude oil price dropped to negative levels for the first time in history. This study examines the factors underlying the historic oil price fluctuation during the Covid-19 pandemic. The autoregressive distributed lag (ARDL) bounds testing approach incorporating a structural break is applied to the daily series from 17 January to 14 September 2020 to analyze long-run relationships and short-run dynamics. The results reveal that increases in Covid-19 pandemic cases, US economic policy uncertainty, and expected stock market volatility contributed to the fall in the WTI crude oil price, whereas the fall in the global stock markets appears to significantly reduce the fall. Furthermore, the Russia-Saudi Arabia oil price war and speculation on oil futures are shown to play a critical part in the collapse of the oil markets. The findings are consistent with our expectations. Although it is reasonable to assume that the solution to this oil crisis is a pick-up in global oil demand, which will occur only when the novel coronavirus is defeated, this study proposes policy recommendations to cope with the current oil price crash.

The effect of green energy, global environmental indexes, and stock markets in predicting oil price crashes: Evidence from explainable machine learning

This study aims to predict oil prices during the 2019 novel coronavirus (COVID-19) pandemic by looking into green energy resources, global environmental indexes (ESG), and stock markets. The study employs advanced machine learning, such as the LightGBM, CatBoost, XGBoost, Random Forest (RF), and neural network models. An accurate forecasting framework can effectively capture the trend of the changes in oil prices and reduce the impact of the COVID-19 pandemic on such prices. Additionally, a large dataset with different asset classes was used to investigate the crash period. The research also introduced SHapely Additive exPlanations (SHAP) values for model analysis and interpretability. The empirical results indicate the superiority of the RF and LightGBM over traditional models. Moreover, this new framework provides favorable explanations of the model performance using the efficient SHAP algorithm. It also highlights the core features of predicting oil prices. The study found that high values of GER and ESG lead to lower crude oil prices. Our results are crucial for investors and policymakers in promoting climate change mitigation and sustained economic prosperity through green energy resources.

How COVID-19 has affected stock market persistence? Evidence from the G7's

This paper examines how COVID-19 pandemic has affected volatility persistence in the G7's stock markets. Based on daily data we divided the whole sample into two sub-samples according to its breakpoints and found that they occurred right after the declaration of COVID-19 pandemic by the World Health Organization - WHO (2020). This approach allows us to assess the main differences between these two distinct phases. Thus, while the first sub-period is relatively calm, the second one, which coincides with the pandemic outbreak, shows higher levels of volatility. Considering this, we rely on GARCH-type models to assess the degree of persistence of volatility and to evaluate how it has evolved across sub-samples. Our results show that the FIGARCH(1,d,1) is the best model to describe the data and that the degree of persistence is very different from the first to the second sub-sample. Thus, while the pre-pandemic period exhibits lower levels of persistence it has greatly increased with the COVID-19 outbreak. In particular, S&P 500 and FTSE/MIB became the most persistent indices in contrast to NIKKEI 225 and FTSE 100, which were amongst the least persistent.

FX markets’ reactions to COVID-19: Are they different?

In this paper, we empirically investigate the impact of the COVID-19 pandemic on FX markets. We find important differences between COVID-19 and previous high-risk episodes: the Global Financial Crisis, the Swiss National Bank's removal of the Swiss franc/euro floor, and Brexit. Contrary to these episodes, the USD did not show any safe haven characteristics during the pandemic. Furthermore, the estimated volatility and non-parametric value-at-risk of three currency portfolios indicate that COVID-19 was not as risky as previous stressful events. We provide evidence that investors could minimize COVID-19 risk by investing in the Canadian dollar and the Japanese yen, and by reducing their exposure to European currencies.