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.

The high energy consumption of cryptocurrency transactions has raised concerns about the environment and sustainability among green investors and regulatory authorities. The current study examines the connectedness among clean energy, Bitcoin, the stock market, and crude oil empirically. The time-varying parameter vector autoregression (TVP-VAR) is used to estimate the dynamics of connectedness in a daily dataset spanning the period November 11, 2013 to September 30, 2021. We find that the clean energy and traditional stock markets transmit shocks to Bitcoin and oil in terms of return, and they receive shocks in terms of volatility from Bitcoin and oil. Additionally, Bitcoin and other financial markets are only tenuously linked during non-crisis periods. Nonetheless, their connection strengthens substantially during times of crisis, such as the great cryptocurrency crash of 2018 and the COVID-19 pandemic of 2020. We believe that these findings can help explain how clean energy and cryptocurrency markets are linked during times of crisis.

This research for the first time examines the influence of the financial development, stock market, globalization, institutional quality, economic growth, electricity, and renewable energy consumption on carbon dioxide emission from 1985 to 2018 in thirty-six (OECD) countries. Cointegrations exist in the used variables based on the examined findings of the Kao, Westerlund, and Pedroni cointegration. Findings of the pooled mean group (PMG) indicate that renewable energy consumption, globalization, and institutional quality assist to reduce the carbon dioxide emission that improve the environment while financial development, stock market, electricity consumption, and economic growth cause to increase the carbon dioxide emission in OECD countries both in the long and in the short run. To reduce carbon dioxide emission, important policy implications are suggested for OECD countries.

This study aims to enrich our understanding of the valuation consequence of climate risk in financial markets. The primary focus of our study is on the stock price reaction to firms’ climate-risk-related information. We employ transcripts of Chinese listed firms’ performance briefings to capture the climate risk at the firm level. Using a sample of Chinese listed firms between 2009 and 2021, we find that greater corporate climate risks lead to negative market reactions over a short time window, consistent with the market quickly comprehending corporate climate risks. This result holds for a series of robustness checks. We further find that the negative impact of corporate climate risk on the stock price reaction operates through the increased market trading activities, greater investor attention, and reduced positive media coverage. Finally, we demonstrate that industry carbon emission, local abnormal temperature, state ownership, institutional shareholding, and dividend payout are important moderators that shape the association of the corporate climate risk and the adverse market reaction. Our evidence suggests that disclosures of climate-related information can help the stock market to price climate risk more efficiently.

Low-carbon transformation has become a key priority in China, as demonstrated in the implementation of the Carbon Peak, Carbon Neutralization policy, leading to increasing concern of environmental performance at the corporate level. This paper measures the carbon emission of 1,089 Chinese companies through the EIO-LCA-based approach. Then we examine the impacts of international crude oil price fluctuations and the corporate development level on carbon emissions of individual companies. Our results indicate that an increase in international crude oil price uncertainty could inhibit the company’s carbon emission. In parallel, we find that there might exist an environmental Kuznets curve (EKC) inverted U-shaped correlation between the company’s development level and its environmental performance. However, some exceptions to corporate carbon performance may emerge, resulting from specific corporate characteristics such as the state-owned nature and whether the firm is listed on the stock exchange. Our results could help companies optimize their internal carbon emission structure during the low-carbon transition process and contribute to effective policy regulations towards the target of carbon reduction.

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.

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 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.

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 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.