Hedging oil price risk with gold during COVID-19 pandemic

The nexus between remittance, exchange rate and economic growth of E7 economies: Frequency domain analysis

This study investigates the nexus between economic growth (GDP), trade openness, remittances, exchange rate, and agricultural output in E7 (Russia, Indonesia, Mexico, China, India, Brazil, and Turkey) economies, covering the data from 1990 to 2020. In the first step, we adopted the Dumitrescu and Hurlin time domain Granger causality test, which shows that economic growth (GDP) and agriculture do not have any causal relationship, not even at 3-lags. However, uni-directional causality exists between agriculture and economic growth at the first level difference. In the second step, we used Granger causality analysis in the frequency domain, presented by Croux and Reusens, showing a bivariate correlation among economic growth, trade, remittance, and agricultural output. The panel Granger causality outcome indicated that the causality between variables with various frequencies differs. Policymakers in these economies may consider these pragmatic results to formulate valuable and appropriate short-, medium-, and long-term economic strategies.

COVID-19 and risk spillovers of China's major financial markets: Evidence from time-varying variance decomposition and wavelet coherence analysis

COVID-19 has influenced financial markets drastically; however, this influence has received little attention, particularly in China. This study investigates risk spillovers across China's financial and shipping markets through dynamic spillover measures based on time-varying parameter vector autoregression and generalized forecast error variance decompositions. Stock, fund, and futures markets are identified as major risk senders, whereas other markets are identified as major risk receivers. Surprisingly, bonds, gold, and shipping are safe havens that facilitate portfolio optimization. Furthermore, using wavelet coherence analysis, we find that the coherence between dynamic total spillover and COVID-19 varies across time and frequency domains.

Do oil, gold and metallic price volatilities prove gold as a safe haven during COVID-19 pandemic? Novel evidence from COVID-19 data

The spreading COVID-19 outbreak has wreaked havoc on the world's financial system that raises an urgent need for the re-evaluation of the gold as safe haven for their money because of the unprecedented challenges faced by markets during this period. Therefore, the current study investigates whether different asset class volatility indices affect desirability of gold as a safe-haven commodity during COVID-19 pandemic. Long run and the short run relationship of gold prices with gold price volatility, oil price volatility, silver price volatility and COVID-19 (measured by the number of deaths due to COVID) has been analyzed in the current study by applying ARDL Bound testing cointegration and non linear ARDL approach on daily time series data ranging from January 2020 to Dec 2021. Findings of the study suggest that in the long run, oil price volatility and gold price volatility positively affect the gold prices, whereas the effect of silver price volatility on gold prices is negative in the long run. However in the short run, all the three indices negatively impact the gold prices. In contrast, the impact of COVID-19 is positive both in the short run and in the long run that proves the validity of gold as safe haven asset in the time of the deadly pandemic. The findings of this study have significant implications and offer investors with some indications to hedge their investments by considering the gold's ability of safe haven during this era of pandemic.

Do non-pharmaceutical policies in response to COVID-19 affect stock performance? Evidence from Malaysia stock market return and volatility

This paper examines the impact of non-pharmaceutical intervention by government on stock market return as well as volatility. Using daily Malaysian equity data from January 28, 2020 to May 31, 2022, the regression analysis with bootstrapping technique reveals that the government's response in combating the deadly virus through Stringency index has shown a positive direct effect on both stock market returns and volatility, and indirect negative effect on stock market returns. The study revealed that international travel restriction and cancelling public events are the major contributors to the growth of volatility when estimated for Malaysia stock market index. On the one hand, heterogenous impact is expected from the perspective of different sectors when the individual social distancing measures were taken into account in determining stock return and volatility. Apart from that, the robustness check for the main findings remains intact in majority of the regression models after incorporating daily COVID-19 death rate, log (daily vaccination) and day-of-the-week effect as additional control variable in alternative.

Gold price and exchange rate in pre and during Covid-19 period in India: Modelling dependence using copulas

This study examines the dynamic relationship between the gold price and the exchange rate in pre- and during Covid-19 pandemic in India. We consider the periods of about equal length for both the pre- and during Covid-19 by considering the data from January 1, 2019 till February 28, 2021. The descriptive analysis shows a significant increase in the dynamics of gold price and exchange rate after mid-March 2020. The results derived from the ARDL approach show a positive and significant relationship between the gold price and exchange rate both in the long and short run. We have selected the best fitted bivariate copula to study the joint distribution of the gold price and the exchange rate. Using the copula model, we examine the relationship between the gold price and exchange rate in a bivariate framework. We have studied the dependence between them including the tail dependencies using the fitted copula. Our findings reveal that the gold price and exchange rate are significantly correlated for the entire study period, and it also reveals that there is no tail dependence. However, the mutual association between the variables is not confirmed in the considered Covid-19 period.

Can gold and bitcoin hedge against the COVID-19 related news sentiment risk? New evidence from a NARDL approach

The COVID-19 pandemic has led to extensive news coverage, causing investor sentiment to swing, which has further increased financial market price volatility. There is an increasing need to find a hedge against sentiment risk. This paper examines the hedge capabilities of gold and Bitcoin against COVID-19-related news sentiment (CNS) risk under a nonlinear autoregressive distributed lag (NARDL) model. Our empirical results reveal that there is an obvious asymmetric effect from the CNS on gold prices in the short run and that the decrease in the COVID-19-related news index would have a greater impact on gold prices than when it increases. The impact of CNS on Bitcoin prices is asymmetric in the long and short term, especially in the long term. In addition, we conclude that gold is a hedge against CNS risk in the long term, and the hedging effect of Bitcoin is mainly reflected in the short-term.

Impact of the COVID-19 pandemic on return and risk transmission between oil and precious metals: Evidence from DCC-GARCH model

It is frequently discussed in the literature that the correlation between low-correlation assets under ordinary market conditions may increase during crisis periods. To contribute to the ongoing debates, this paper empirically examines risk transmission between oil and precious metal markets induced by the COVID-19 pandemic using the DCC-GARCH model. The findings reveal evidence of a significant risk transmission between oil prices and precious metal prices, particularly during the onset of the COVID-19 pandemic. The findings point out that the negative relationship between oil and all precious metals returns in the pre-COVID-19 period has changed with the effect of the pandemic. In this process, it is revealed that the negative relationship between oil and gold has strengthened, but the negative relationship between oil and silver has weakened. In addition, the correlations between oil and platinum and palladium turn positive. The empirical findings imply that investors and portfolio managers seeking portfolio diversification and hedging opportunities in a high-risk environment such as the COVID-19 pandemic should consider gold and silver assets for investment.

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.

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.

COVID-19 pandemic and financial innovations

This study is motivated around the COVID-19 pandemic as a source of rising financial market risks. Hence, we investigate whether pandemic-induced risks can be hedged by alternative investment in financial innovations captured in exchange traded funds (ETFs). We explore the hedging effectiveness of sectoral ETFs along with a battery of robustness measures. Following the predictability analyses, we find that financial innovations captured in ETFs can effectively hedge both pandemic-induced and financially engineered market risks especially after controlling for the role of oil price in the predictive model. Our model provides better in-sample and out-of-sample forecasting accuracy and economic gains than the benchmark model and this is more pronounced for the COVID-19 pandemic period.

Volatility in metallic resources prices in COVID-19 and financial Crises-2008: Evidence from global market

The prevalence of uncertainty is evident in natural resources and financial markets almost every period. However, the global financial crisis and the recent Covid-19 pandemic is considered the most distressful event that disturbs the global economic and financial performance. In such crises, natural resource (mineral) prices also fluctuate as a result of demand and supply shocks. Identifying volatility in metallic resource prices is now the time's need, which consequently leads to implementing appropriate policies for recovery of the global markets. In this sense, the current study analyzed these two period from August 21, 2007, to December 31, 2009 (global financial crisis) and from January 01, 2019, to September 17, 2021 (Covid-19 pandemic). The empirical results obtained via threshold generalized autoregressive conditional heteroscedasticity (TGARCH) and exponential autoregressive conditional heteroscedasticity (EGARCH) model asserted that volatility exists in metallic resource prices in both the crises periods. Concerning the global financial cristhe metallic resource prices were more volatile in 2008, while such priwere are highly volatile during the Covid-19 pandemic peak year (2020). Additionally, volatility in metallic resources is found higher in the Covid-19 pandemic, relative to global financial crisis. Based on the empirical results, this study suggests the appropriate policy measures that could help tackle the issue of metallic resource price volatility.

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 effects of COVID-19 on the interrelationship among oil prices, stock prices and exchange rates in selected oil exporting economies

This paper re-examines the performances of stock prices, oil prices and exchange rates in twelve oil exporting countries amidst the ravaging consequences of the ongoing worldwide coronavirus pandemic. Consequently, the study adopted a panel Vector Autoregressive (pVAR) model which applied data from the pre- and post-COVID-19 periods. Contrary to the pre-COVID-19 pandemic period, the pVAR Granger causality test indicates that the stock market can as well affect the exchange rate market, though positively. Furthermore, the Impulse response functions (IRFs) shows that a shock to crude oil prices provokes a negative response by exchange rates in the post-COVID-19 pandemic era only. The Forecast Error Variance Decomposition (FEVD) estimates that such innovations to crude oil prices account for the varying fluctuations in exchange rates and stock returns at different periods, but is neither influenced by the stock market activities nor the exchange rate market in the post-COVID-19 pandemic era. This suggests that before COVID-19, the different markets in the selected oil producing economies were only affected by their market fundamentals and dynamics only, but this changed with the plummeting oil prices in the COVID-19 pandemic era. The development of vaccines and the immediate vaccination of the world people will ease the lockdowns and increase the demand for crude oil by the high oil importing countries. With the improved earnings from this, and the associated appreciation of the local currencies against the US dollars, the capital market activities of these net oil exporting countries improve. Policy makers and investors should consider the dynamics in the oil market while making decisions.

Revisiting the safe haven role of Gold across time and frequencies during the COVID-19 pandemic

This research empirically evaluates the potential diversification benefits of Gold during the COVID-19 pandemic period, when including it in equity-based asset allocation strategies. This study proposes minimum VaR portfolios, with monthly rebalance and different wavelet scales (short-run, mid-run and long-run), doing both an in-sample and out-of-sample analysis. We find much more unstable weights as the frequency of the decomposition becomes lower, and strong evidence of the outperformance of the mid-run decompositions over the rest of active management strategies and the passive management of buy and hold the variety of single equity indices. Thus, we may shed some light on the role of Gold as a safe haven when properly filtering aggregated data.

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.

Economic Growth, Exchange Rate and Remittance Nexus: Evidence from Africa

This paper examined the nexus between economic growth and exchange rate, remittances, trade, and agricultural output based on data sourced from 1980 to 2018 for 10 selected African economies. We employed both the Dumitrescu and Hurlin time-domain Granger causality test and the Croux and Reusens frequency domain Granger causality test. Results from the time-domain test suggests that causality only exists between economic growth and both exchange rate and trade, with no significant relationship between economic growth and both remittances and agricultural output. When we employed frequency domain model in our analysis, the results suggested that there is a bi-directional temporary and permanent causality between economic growth and exchange rate, trade, agriculture, and remittances. Our results suggest the validity of both the J-Curve and Marshall–Lerner hypotheses in the studied economies. Our study offers some relevant policy implications.

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.

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 COVID-19 Outbreak and Risk–Return Spillovers between Main and SME Stock Markets in the MENA Region

This study investigates return and asymmetric volatility spillovers and dynamic correlations between the main and small and medium-sized enterprise (SME) stock markets in Saudi Arabia and Egypt for the periods before and during the COVID-19 pandemic. Return and volatility spillovers are modelled using a VAR-asymmetric BEKK–GARCH (1,1) model, while a VAR-asymmetric DCC–GARCH (1,1) model is employed to model the dynamic conditional correlations between these markets, which are then used to determine and explore portfolio design and hedging implications. The results show that while bidirectional return spillovers between the main and SME stock markets are limited to Saudi Arabia, shock and volatility spillovers have different characteristics and dynamics in both main–SME market pairs. In addition, the dynamic correlations between the main and SME markets are mostly positive and have notably increased during the COVID-19 pandemic, particularly in Saudi Arabia, suggesting that adding SME stocks to a main stock portfolio enhances its risk-adjusted return, especially during tranquil market phases. One practical implication of our results is that the development of SME stock markets can indirectly contribute to economic development via the main market channel and provide an avenue for portfolio diversification and risk management.

The links between gold, oil prices and Islamic stock markets in a regime switching environment

This paper investigates the linkages between gold, oil prices and Islamic stock market for the turbulent period 1996–2020 which covers the recent COVID-19 pandemic crisis. The paper applies standard VAR and Markov switching VAR models. Empirical results can be summarized as follows: (i) There are some significant relationships between the considered markets. (ii) The sign of the links varies significantly according to markets and regimes. (iii) There is a significant and positive link between oil and Islamic stock markets namely during turbulent periods suggesting the financialization of the crude oil market. (iv) The negative or the absence of relationships between gold market and both oil and Islamic stock markets indicate that gold can act as a hedge and safe haven during extreme market conditions. These findings have several practical implications for risk-management and portfolio diversification strategies.

Contagion and portfolio management in times of COVID-19

This paper aims to investigate the COVID-19 pandemic impacts on the interconnectedness between the Chinese stock market and major financial and commodity markets-gold, silver, Bitcoin, WTI, S&P 500, and Euro STOXX 50-and analyze the portfolio design implications. Using daily data from 2018 to 2021, we first apply the wavelet power spectrum (WPS) to visualize volatility shifts. In contrast to previous research, we empirically identify the precise COVID-19 outbreak dates for each market using the Perron (1997) breakpoint test. Finally, we employ the bivariate DCC-GARCH model to analyze the connectedness between markets. The findings reveal that the COVID-19 pandemic caused volatility shifts of different intensities for all of the studied markets. Moreover, each return series exhibits one break date, which is specific to each market and corresponds to a distinct COVID-19-related event. Correlations, hedge ratios, and optimal portfolio weights changed significantly after the COVID-19 outbreak. There is evidence of contagion effects between the Chinese stock market and S&P 500, Euro STOXX 50, gold, and silver. Interestingly, the latter two assets lost their safe haven property with SSE. However, WTI and Bitcoin act as safe havens against SSE risks.

Chinese jigsaw: Solving the equity market response to the COVID-19 crisis: Do alternative asset provide effective hedging performance?

Against COVID-19 risks, this paper examines the hedging performance of alternative assets including some financial assets and commodities futures for the Chinese stock market in a multi-scale setting. Dynamic conditional correlations and optimal hedge ratios of the Shanghai stock exchange with Bitcoin, Dow Jones Industrial Average, Gold, WTI, Bonds and VIX returns are estimated before and during the pandemic crisis. In the short-term, the use of wavelet decomposition shows that Bitcoin provides the best hedge to the Shanghai stock market. In the long-term, commodities dominate. Whereas WTI offers the highest hedging effectiveness, Gold ranks second by a slight margin. These results allow investors to choose the highest returns and protecting tail risk during the current sanitary crisis. Our findings suggest particularly more pronounced economic benefit of diversification including alternative financial assets while commodities futures serve as good hedge assets especially during unpredictable crisis like the current sanitary crisis relating to the covid-19.

Deep learning-based exchange rate prediction during the COVID-19 pandemic

This study proposes an ensemble deep learning approach that integrates Bagging Ridge (BR) regression with Bi-directional Long Short-Term Memory (Bi-LSTM) neural networks used as base regressors to become a Bi-LSTM BR approach. Bi-LSTM BR was used to predict the exchange rates of 21 currencies against the USD during the pre-COVID-19 and COVID-19 periods. To demonstrate the effectiveness of our proposed model, we compared the prediction performance with several more traditional machine learning algorithms, such as the regression tree, support vector regression, and random forest regression, and deep learning-based algorithms such as LSTM and Bi-LSTM. Our proposed ensemble deep learning approach outperformed the compared models in forecasting exchange rates in terms of prediction error. However, the performance of the model significantly varied during non-COVID-19 and COVID-19 periods across currencies, indicating the essential role of prediction models in periods of highly volatile foreign currency markets. By providing an improved prediction performance and identifying the most seriously affected currencies, this study is beneficial for foreign exchange traders and other stakeholders in that it offers opportunities for potential trading profitability and for reducing the impact of increased currency risk during the pandemic.

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.

Socio-economic and corporate factors and COVID-19 pandemic: a wake-up call

The novel coronavirus 2019 (COVID-19) emerges from the Chinese city Wuhan and its spread to the rest of the world, primarily affected economies and their businesses, leading to a global depression. The explanatory and cross-sectional regression approach assesses the impact of COVID-19 cases on healthcare expenditures, logistics performance index, carbon damages, and corporate social responsibility in a panel of 77 countries. The results show that COVID-19 cases substantially increase healthcare expenditures and decrease corporate social responsibility. On the other hand, an increase in the coronavirus testing capacity brings positive change in reducing healthcare expenditures, increased logistics activities, and corporate social responsibility. The cost of carbon emissions increases when corporate activities begin to resume. The economic affluence supports logistics activities and improves healthcare infrastructure. It linked to international cooperation and their assistance to supply healthcare logistics traded equipment through mutual trade agreements. The greater need to enhance global trade and healthcare logistics supply helps minimize the sensitive coronavirus cases that are likely to provide a safe and healthy environment for living.

COVID-19 and the Energy Price Volatility

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.

Market Openness and Its Relationship to Connecting Markets Due to COVID-19

In this research, statistical models were formulated to study the effect of the health crisis arising from COVID-19 in economic markets. Economic markets experience economic crises irrespective of effects corresponding to financial contagion. This investigation was based on a mixed linear regression model that contains both fixed and random effects for the estimation of parameters and a mixed linear regression model corresponding to the generalisation of a linear model using the incorporation of random deviations and used data on the evolution of the international trade of a group of 42 countries, in order to quantify the effect that COVID-19 has had on their trade relationships and considering the average state of trade relationships before the global pandemic was declared and its subsequent effects. To measure, quantify and model the effect of COVID-19 on trade relationships, three main indicators were used: imports, exports and the sum of imports and exports, using six model specifications for the variation in foreign trade as response variables. The results suggest that trade openness, measured through the trade variable, should be modelled with a mixed model, while imports and exports can be modelled with an ordinary linear regression model. The trade relationship between countries with greater economic openness (using imports and exports as a trade variable) has a higher correlation with the country’s health index and its effect on the financial market through its main trading index; the same is true for country risk. However, regarding the association with OECD membership, the relations are only with imports.

Gold and US sectoral stocks during COVID-19 pandemic

In this study, we examine the hedging relationship between gold and US sectoral stocks during the COVID-19 pandemic. We employ a multivariate volatility framework, which accounts for salient features of the series in the computation of optimal weights and optimal hedging ratios. We find evidence of hedging effectiveness between gold and sectoral stocks, albeit with lower performance, during the pandemic. Overall, including gold in a stock portfolio could provide a valuable asset class that can improve the risk-adjusted performance of stocks during the COVID-19 pandemic. In addition, we find that the estimated portfolio weights and hedge ratios are sensitive to structural breaks, and ignoring the breaks can lead to overestimation of the hedging effectiveness of gold for US sectoral stocks. Since the analysis involves sectoral stock data, we believe that any investor in the US stock market that seeks to maximize risk-adjusted returns is likely to find the results useful when making investment decisions during the pandemic.

The role of coronavirus news in the volatility forecasting of crude oil futures markets: Evidence from China

Based on the high-frequency heterogeneous autoregressive (HAR) model, this paper investigates whether coronavirus news (in China and globally) contains incremental information to predict the volatility of China's crude oil, and studies which types of coronavirus news can better forecast China's crude oil volatility. Considering the information overlap among various coronavirus news items and making full use of the information in various coronavirus news items, this paper uses two prevailing shrinkage methods, lasso and elastic nets, to select coronavirus news items and then uses the HAR model to predict China's crude oil volatility. The results show that (i) coronavirus news can be utilized to significantly predict China's crude oil volatility for both in-sample and out-of-sample analyses; (ii) the Panic Index (PI) and the Country Sentiment Index (CSI) have a greater impact on China's crude oil volatility. Additionally, China's Fake News Index (FNI) have a significant impact on China's crude oil volatility forecast; and (iii) global coronavirus news provides more incremental information than China's coronavirus news for predicting the volatility of China's crude oil market, which indicates that global coronavirus news is also a key factor to consider when predicting the market volatility of China's crude oil.

Contagion in Global Stock Markets during the COVID-19 Crisis

The impact of the coronavirus disease (COVID-19) outbreak on global stock markets is investigated by analyzing the impact of the COVID-19 pandemic on the stock markets of 15 countries selected from Asia, Europe, Latin America, and North America. Using extremal dependence tests of contagion, it is found that contagion effects are widespread to global equity markets in four regions. Latin America and North America are highly exposed to contagion risks, followed by Europe, with Asia being least vulnerable. Based on the time window of the crisis severity index, it is found that Latin America is most likely to be affected. The results confirm that for countries with more severe epidemics, there are stronger contagion effects. Therefore, for the governing authorities of various countries, if they want to prevent the contagion of financial crises during the pandemic, strong and timely epidemic prevention measures are very necessary.

Spatial financial contagion during the COVID-19 outbreak: Local correlation approach

The purpose of this paper is to examine the effect of spatial proximity on financial contagion during the COVID-19 outbreak. We use the daily stock index series of Asian, American, and European countries from January 1, 2014 to January 30, 2021. Two groups of countries are considered: the first includes China and geographically close countries, namely Taiwan, Hong Kong, Singapore, India, Australia, Indonesia, Malaysia, South Korea, Singapore, Vietnam and Russia. The second group includes countries that are geographically distant from China: the United States, Brazil, Mexico, Argentina, Italy, France and Germany. Using local correlation measurement and polynomial regressions, we show that the spatial contagion effect exists between China and geographically distant countries. However, this effect is absent for geographically close countries (Taiwan, Vietnam and Hong Kong).

These findings have strong implications for investors and present guidance for regulators and policymakers in understanding the true impact of the COVID-19 on financial markets.

Assessing the hedging potential of gold and other precious metals against uncertainty due to epidemics and pandemics

We assess the hedging capabilities of four prominent precious metals namely gold, palladium, platinum and silver against market risks due to epidemics and pandemics. The research objective is informed by the COVID-19 pandemic which amplifies health risks with attendant concerns for financial markets. We utilize the health-related uncertainty index developed by Baker et al. (Equity market volatility: infectious disease tracker [INFECTDISEMVTRACK], 2020) which measures uncertainty in the financial markets due to infectious diseases including the COVID-19 pandemic and construct a predictive model that accommodates the salient features of both the predictand and predictor series. Our results support the safe haven property only for gold before and during the COVID-19 pandemic. We push the analysis further for in-sample and out-of-sample forecast evaluation and find that accounting for uncertainty due to infectious diseases improves the forecast of the four precious metals relative to the benchmark model (historical average). We highlight for investors that the gold market remains the safest market among the precious metals particularly during the COVID-19 pandemic.

Empirical Examination on the Drivers of the U.S. Equity Returns in the During the COVID-19 Crisis

This study investigates the drivers of the Standard & Poor's (S&P) 500 equity returns during the COVID-19 crisis era. The paper considers various determinants of the equity returns from December 31, 2019, to February 19, 2021. It is observed that the United States Dollar (USD) and the volatility indices (VIX) negatively affect the S&P 500 equity returns. However, the newspaper-based infectious disease "equity market volatility tracker" is positively associated with the stock market returns. These results are robust to consider both the ordinary least squares (OLS) and the least angle regression (LARS) estimators.

COVID-19 pandemic and the crude oil market risk: hedging options with non-energy financial innovations

This study examines the hedging effectiveness of financial innovations against crude oil investment risks, both before and during the COVID-19 pandemic. We focus on the non-energy exchange traded funds (ETFs) as proxies for financial innovations given the potential positive correlation between energy variants and crude oil proxies. We employ a multivariate volatility modeling framework that accounts for important statistical features of the non-energy ETFs and oil price series in the computation of optimal weights and optimal hedging ratios. Results show evidence of hedging effectiveness for the financial innovations against oil market risks, with higher hedging performance observed during the pandemic. Overall, we show that sectoral financial innovations provide resilient investment options. Therefore, we propose that including the ETFs in an investment portfolio containing oil could improve risk-adjusted returns, especially in similar financial crisis as witnessed during the pandemic. In essence, our results are useful for investors in the global oil market seeking to maximize risk-adjusted returns when making investment decisions. Moreover, by exploring the role of structural breaks in the multivariate volatility framework, our attempts at establishing robustness for the results reveal that ignoring the same may lead to wrong conclusions about the hedging effectiveness.

Examining the Asymmetric Impact of COVID-19 Pandemic and Global Financial Crisis on Dow Jones and Oil Price Shock

COVID-19 has significantly affected the financial and commodity markets. The purpose of this investigation is to understand the impact of the COVID-19 crisis on Dow Jones and West Texas Intermediate (WTI) oil returns in relation to other crises using the Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model. The results indicate that COVID-19 and the accompanying lockdown have adversely impacted both yields and that the impact on oil prices is more significant than on the Dow Jones index. The variance and squared residuals of oil prices and the Dow Jones reached their highest historical levels during the COVID-19 outbreak, even higher than during the global financial crisis, and especially the VaR of both markets reached their historical peak points during the COVID-19 era. The variance of WTI during COVID-19 is higher than that of DJI, as was also the case during the financial crisis. These findings confirm that COVID-19 has negatively impacted investors’ ability to determine optimal portfolios and thus the sustainability of financial and energy markets more than the global financial crisis of 2007–2009. We, therefore, suggest that policy changes are needed to maintain financial sustainability and help investors deal with future financial and other crises.

The Progression of COVID-19 and the Government Response in China

The ongoing pandemic of COVID-19 (Coronavirus Infectious Disease-2019) was first reported at the end of 2019 in Wuhan, China. On 30 January 2020, the WHO declared a Public Health Emergency for the novel coronavirus. On 11 March 2020, the WHO officially declared the COVID-19 outbreak as a pandemic. Due to the differences in population distribution, economic structure, degree of damage and other factors, the affected countries have introduced policies tailored to local conditions as a response to the pandemic, leading to different economic and social impacts. Considering the highly heterogeneous spreading of COVID-19 across regions, this paper takes a specific country (China) as a case study of the spread of the disease and national intervention models for the COVID-19 pandemic. The research period of this article is from 17 December to 26 April 2020, because this time period basically covered the important time nodes of the epidemic in China from animal-to-human transmission, limited human-to-human transmission, epidemic to gradual control. This study is useful for comparing the effectiveness of different interventions at various stages of epidemic development within the same country and can also promote the comparison of the epidemic response interventions of different countries. Based on the conclusions of the model simulation, this article evaluates the dual impact of the epidemic on people's wellbeing and the economy.

Hedging against risks associated with travel and tourism stocks during COVID‐19 pandemic: The role of gold

The global lockdowns including movement restrictions during COVID‐19 pandemic impacted the hospitality business negatively and by extension the trading of related stocks such as travel & tourism stocks. Owing to the long standing hedging potential of gold, we examine whether this potential can be extended to the travel & tourism stocks in order to hedge against the associated risks caused by the current pandemic. Using daily data from January 2016 to July 2020 and constructing optimal portfolio strategies, we find that gold serves as a very strong hedge and safe haven for travel & tourism stocks, most especially in the pandemic period. This conclusion validates the inclusion of gold in the diversified portfolio of travel & tourism stocks in order to improve the risk‐adjusted return performance for investors in the sector particularly during COVID‐19 pandemic.