This paper investigates volatility spillovers between the global crude oil market and the stock markets of the global oil stock markets (Russian, Canada, China, Kuwait, and the USA) pre and after the COVID-19 pandemic. We use wavelet Granger causality methods to study the volatility spillovers between global oil stock markets, mainly from January 1, 2019, to March 31, 2021. Our Results (1) shows that WTI and Brent oil prices had a negative mean return before COVID-19 but a positive mean return during the pandemic spread. Other Results (2) find the positive, significantly lowest, and highest frequency during the COVID-19 outbreak for all selected countries. The results also show that the link between oil WTI & Brent prices and stock markets return in the lowest (33-66 days) and highest frequency range (4-16) before the Covid-19 epidemic, especially in the first quarter of 2020. Before the COVID-19 period, the Russian oil stock market is seriously prejudiced with oil prices on a modest scale, but not after the pandemic's start. This study also perceives direction opposite between the COVID-19 period. The Canadian and United States America oil and stock markets influence the lowest scale in the previous COVID-19 sample for the U.S. market. Moreover, this paper exposed that oil marketing highest oil futures in their portfolios than stock shares for all times. We found that oil price shocks had a more significant impact on the stock markets of the United States and Canada than on the stock markets of other countries.

For humankind to sustain a livable atmosphere on the planet, many countries have committed to achieving carbon neutralization. Countries mainly reduce carbon emissions by regulations through a carbon tax or by establishing a carbon market using economic stimuli. In this paper, we use the least absolute shrinkage and selection operator (LASSO) method to select the key determinants of a carbon market and then use the Markov switching vector autoregression (MSVAR) model to study the market’s driving factors and analyze its time-varying characteristics. The results show that there are perceptible time-varying characteristics and notable differences among markets. During COVID-19, energy factors had a long-term shock on the carbon market, economic factors had a short-term shock on the carbon market, and the economic recession has led to fluctuations in the carbon market. In addition, through MSVAR, the results show that the energy market has a negative effect on the carbon market, and the stock market has a positive effect on the carbon market. In periods of low volatility, compared with the natural gas market and coal market, the oil market has a stronger shock on the carbon market. In periods of high volatility, the coal market has a stronger shock on the carbon market. In terms of emission reduction, countries around the world would be wise to change their energy consumption structure, reduce coal use, and shift to a cleaner energy consumption structure.

The financial system development has got considerable attention due to its association with the environment of the country. To address the apprehension of the researchers about the effect of the determinants of the financial system on the environmental quality of high-income developed countries, we analyze the data of twenty developed countries with sound and strong financial systems for the period 2001 to 2018. We consider both banking development and stock market development as the main key determinants of the financial system. We employ numerous modern-day penal data estimation techniques, namely Dynamic Penal GMM in both linear and non-linear form, Common Correlated Effect Mean Group (CCEMG), and Dynamic Fixed Effect for capturing the issues of heterogeneity, endogeneity, and cross-sectional dependence. Our results show that banking development substantiates the environmental quality in high-income developed countries. The positive gesture of the banking development on environmental quality could be the reason for the established environmentally friendly policies in the developed part of the world. Hence, we conclude that banking development in high-income developed countries significantly reduces the emissions of dangerous gases, which resultantly enhances the environmental quality. The study reveals an insignificant and tenuous impact of the market development on the environmental quality that might be due to the adoption of cleaner technologies by firms in the developed world that are environmentally friendly. The results of our long-term estimations also predict the significant effect of banking development and an insignificant effect of the market development on environmental quality. In addition, our results also demonstrate an inverted U-shaped relationship of the determinants of the financial system and environmental quality. More institutional and legal initiatives must be made for a more robust banking and stock market development framework by the policy makers with a view to substantiating the quality of the environment to a more sustainable level in the developed world.

In recent years, the frequent occurrence of smog in Chinese cities has prompted great changes in the policy environment faced by enterprises. In this study, we address the question whether the decision-making behavior of enterprises will be affected by smog. This paper studied the 2010–2018 data of 218 listed Chinese polluting companies to investigate the impact of smog on corporate social responsibility (CSR). The subjects of this study were all listed on China’s A-share market on either the Shenzhen or Shanghai Stock Exchange. The empirical results indicate the following: (1) the more serious the smog, the more likely enterprises are to perform CSR; (2) smog exerts a higher impact on the social responsibility of enterprises that receive more media attention. Further research determined that media attention, whether positive, negative, or neutral, plays the same role in moderating the relationship between smog and CSR; and (3) compared to private enterprises, the function of smog in promoting the CSR fulfillment of state-owned enterprises (SOEs) is more obvious. Based on the reality of Chinese polluting industries, this research combined smog and media attention in the exploration of CSR, which not only enriches CSR research but also provides positive guidance for the sustainable development of polluting enterprises.

The objective of this analysis is to examine the impact of international trade and technological innovation over the 1990–2018 period on the G7 economy’s consumption-based carbon emissions. The report explores international trade by separately considering imports and exports. The results indicate that the data cross-sections are dependent and that the panel has slope heterogeneity. The results of the co-integration study indicate that imports, exports of technological innovation, GDP, and demand-related carbon emissions are co-integrated with systemic splits (2001 mild recession, 2008 financial crises, and 2011 decline of stock market, and 2014 export decline). The cross sectionally augmented autoregressive distributive lag model results show that technological innovation and exports have a negative effect on the use of carbon. Meanwhile, imports and GDP are positive associated with carbon emissions based on consumption. The analysis of the robustness test also verifies these impacts. The results of this research study show that policymakers and regulators can encourage technological innovation to reduce carbon pollution and improve the sustainability of the environment.

Energy stocks have become an essential segment of the investment portfolios of both households and institutional investors. This study investigates the dynamic aspect of evolving weak-form efficiency in six energy stock markets: those of the United States (US), Canada, China, Australia, India, and Saudi Arabia. The generalized autoregressive conditionally heteroskedastic in the mean GARCH-M(1,1) method is applied, alongside the state-space time-varying approaches with the Kalman filter estimation, to detect the evolving efficiency for periods ending in November 2019. The empirical results reveal that the studied markets undergo various extents of time-varying efficiency, containing periods of efficiency enhancement as well as periods of deviation from efficiency. Meanwhile, the 2007–2009 global financial crisis and the 2015 changes in the energy sector—in addition to other contemporaneous crises—have a profound influence on the timeline of market efficiency evolution. Overall, all of the markets gradually became more efficient, apart from India’s energy market as a result of the current energy crisis in India. Amid the energy markets explored in this study, the US energy market was found to be the most efficient.

The interaction between oil and stock market returns is one of the most important relationships that have a significant influence on the economy of any country all over the world. Therefore, this paper investigates the impact of crude oil prices on the Chinese stock market and selected industries by using the VAR-DCC-GARCH model over the period from December 26, 2001, to April 30, 2019. The empirical results show that the impact of Brent crude oil prices on the Shanghai Composite Index and selected industries is significant. However, there are some variations in these relationships and the degree of influence on each differs during different sample periods. Brent crude oil prices exert substantial influence on some specific industries, like mining, chemical, nonferrous metals, and steel. Whereas, the volatility spillover effect of Brent crude oil prices is stronger within the mining, chemical, steel, nonferrous metal, building materials, building decoration, electrical equipment, electrical equipment, textile and garment, light manufacturing, public utility, and transportation industries than within other industries. When oil prices change abruptly, the risk of spillover impacts of oil prices on stock markets will also increase. In conclusion, the impact of Brent crude oil prices on the Chinese stock market is generally positive. Furthermore, the subsequent volatility of Chinese stock market prices will, in turn, influence the volatility spillover of Brent crude oil prices on the indexes. The result is an ongoing back and forth of changes in price volatilities.

Economic policy uncertainty generally tends to induce a pessimistic view of future market behaviour. Furthermore, instabilities in global oil prices have serious implications for the economies of oil exporters and importers, due to their over-dependence on crude oil for revenue and production activities, respectively, and thereby on stock market indices. Against limited empirical evidence, this study examines the spillover effects from global economic policy uncertainty (GEPU) and oil price volatility to the volatility of the stock market indices of oil exporters and importers in both developed and emerging economies. The results show that the spillover effect from GEPU to oil exporters is relatively smaller than to oil importers, for both developed and emerging countries. Conversely, the volatility spillovers from oil prices to oil exporters are relatively larger than to oil importers, for both developed and emerging countries. Specifically, the volatility spillovers from oil prices to oil exporters (importers) in emerging countries are relatively stronger compared to oil exporters (importers) in developed countries. The findings indicate that the volatility of the stock markets of emerging countries is more sensitive to global factors such as GEPU and oil price volatility, and that oil exporters and importers in emerging economies are more sensitive to oil price volatility than oil exporters and importers in developed economies, which is in line with previous studies.

The relationship between financial development and energy consumption is the most frequently research field in finance and economy. The main objective of performing this study is to answer that is there a relationship between financial development and renewable energy consumption in emerging countries? In many studies carried out in literature, the empirical findings were pointing to the existence of thiss relationship. To examine the relationship between financial development and renewable energy consumption, a total of 20 emerging countries were obtained from annual frequency data between 1990 and 2015. The system GMM estimation was used as the method of study. As a result of the analysis performed, it indicates that financial development does not impact renewable energy consumption in emerging countries when financial development is measured using both banking and stock market variables. Additionally, it can be said that the financial development increases renewable energy consumption if it is measured by only stock market capitalization.

We analyze the dynamic correlation between the carbon price and the stock returns of green energy companies and calculate the hedging effect of the carbon price on stock returns in green energy sectors. The results show that the coefficients of the carbon price change with time and are vulnerable to extreme events like the COVID-19. The quantile-on-quantile (QQ) model results reveal a dynamic effect from the carbon price to the stock returns of green energy sectors. The quantile coherency (QC) approach results show that investors can benefit more in the short term with high-frequency trading to hedge between carbon trading and the green energy stock market. What is more, the hedging effects are heterogenetic and investors should adjust their hedging strategies in different quantiles.