From forests to faucets to fuel: Investigating the domino effect of extreme risk in timber, water, and energy markets

This study explores the interdependence between timber, water, and energy markets and investigates the potential domino effect of extreme risk across these markets. Specifically, using CAViaR-TVP-VAR, we examine the role of water and timber investments as safe-havens and hedges for traditional energy markets, before and after the COVID-19 pandemic. Our results indicate that water and timber markets can serve as reliable safe-haven options for energy investors. Moreover, our findings suggest a weak link between natural gas and its counterparts, underscoring the need for energy portfolios to diversify. This study provides valuable insights for investors seeking to navigate extreme risk.

Connectedness among major cryptocurrencies in standard times and during the COVID-19 outbreak

The cryptocurrency markets are perceived as being dominated by Bitcoin leading the overall system dynamics. Although the previous empirical evidence points towards strong connections among selected cryptocurrencies or, from the other side, weak dependence between Bitcoin and traditional financial assets, a focused study on the dynamics of return and volatility connectedness among a wider range of cryptocurrencies is lacking, and more so, one directed towards the very first actual critical period of the global economy coinciding with relevant crypto-markets. Using data for the 10 most capitalized cryptocurrencies between 1st October 2017 and 5th January 2021, we examine how cryptocurrencies interact and whether they have a clear leader, with a special focus on differences with respect to investment horizons and how the relationship structure evolves in time. We uncover a structural change in the connectedness evolving in 2020 as the market restructures in reaction to the unprecedented monetary injections as a counter to the COVID-19-induced economic standstill. The structural change is shown not only for cryptocurrencies considered separately but also when we jointly examine them with traditional assets.

Volatility spillovers during normal and high volatility states and their driving factors: A cross‐country and cross‐asset analysis

Understanding the transmission of volatility across markets is essential for managing risk and financial stability, especially under crisis periods during which an extreme event occurring in one market is easily transmitted to another market. To gain such an understanding and enrich the related literature, we examine in this article the system of volatility spillovers across various equity markets and asset classes using a quantile-based approach, allowing us to capture spillovers under normal and high volatility states. The sample period is 16 March 2011-10 November 2020 and the employed dataset comprises 12 implied volatility indices representing a forward-looking measure of uncertainty of global equities, strategic commodities and the US Treasury bond market. The results show that the identity of transmitters and receivers of volatility shocks differ between normal and high volatility states. The US stock market is at the centre of volatility spillovers in the normal volatility state. European and Chinese stock markets and strategic commodities (e.g. crude oil and gold) become major volatility transmitters in the high volatility state, after acting as volatility receivers during normal periods. Furthermore, we study the drivers of implied volatility spillovers using regression models and find that US Default spread contributes to the total volatility spillover index in both volatility states, whereas TED spread plays a significant role in the normal volatility state. As for the role of short rate and risk aversion, it is significant in the high volatility state. These findings matter to the decision-making process of risk managers and policymakers.

Does financial stress wreak havoc on banking, insurance, oil, and gold markets? New empirics from the extended joint connectedness of TVP-VAR model

This study explores the dynamic and time-varying connectedness between the US stocks, financial sector, oil and gold markets, broad market volatilities, and financial stress. We examine if the traditional association between financial stress and its important factors and strategic commodities such as oil and gold has changed during the last decade, especially after the COVID-19. We use daily data set from July 2011 to June 2021, and employ the extended joint connectedness approach of Balcilar et al. (2021), which has several advantages over traditional connectedness models. Our findings show that traditional determinants of US financial stress are dynamic and change in response to the monetary injections in late 2019 more as compared with the COVID-19. In spite of the importance of COVID-19, our analysis points towards the enhanced significance of US monetary injections in driving joint connectedness between financial stress and its prominent factors and strategic commodities. Further, gold and oil show diversification potential in a portfolio of US stocks, financial sector and broad market volatilities. Therefore, important policy and investor implications are discussed for financial stability and portfolio choices.

Quantifying the asymmetric spillovers in sustainable investments

Owing to the growing importance of socially responsible investments in the wake of climate change mitigation goals, we estimate the asymmetric time- and frequency-spillovers between global sustainable investments. Additionally, we examine the influence of global risk factors such as US and UK economic policy uncertainties, stock market volatility, US treasury market volatility and infectious diseases related market volatility on the short- and long-run connectedness in these investments. To this end, we use daily returns and volatilities of 14 country-level Dow Jones Sustainability indices from January 2005 to March 2021. By employing the asymmetric versions of Diebold & Yilmaz (2012, 2014) and Barunik & Krehlik (2018) time-frequency connectedness, our study addresses both good and bad contagion among sustainable investments is unexplored in the recent literature. The results reveal significant time-frequency asymmetries in return spillovers across different regions in the short- and long-run. Germany, France, Netherlands, and the UK are the primary transmitters of returns and volatility shocks. We find more intra-regional connectedness among the Asian countries as opposed to inter-regional connectedness. Negative returns propagate more intensely than positive ones, and this contagion is considerably boosted during crises, including the COVID19. The VIX and COVID19 remain influential for financial contagion in the long run. The impact of MOVE is positive in the short-run while negative in the long-run, which shows an overreaction of connectedness to the US treasury market volatility in the short-run. Economic policy uncertainties in the US and the UK increase spillovers more intensely in the short-run. These results are robust to using volatility spillovers, the choice of rolling window and various forecast horizons. Our findings are distinctly important for socially responsible investors as we point out international portfolio diversification opportunities among sustainable investments. Understanding the dynamics of connectedness in sustainable investments can potentially boost financing in this market through portfolio choices and contribute to the climate change mitigation agenda of United Nations.

Climate indicators and COVID-19 recovery: A case of Wuhan during the lockdown.

The world needs to get out of the COVID-19 pandemic smoothly through a thorough socio-economic recovery. The first and the foremost step forward in this direction is the health recovery of the people infected. Our empirical study addresses this neglected point in the recent research on COVID-19 and specifically aims at exploring the impact of the environment on health recovery from COVID-19. The sample data are taken during the lockdown period in Wuhan, i.e., from 23rd January 2020 to 8th April 2020. The recently developed econometric technique of Quantile-on-Quantile regression, proposed by Shin and Zhu (2016) is employed to capture the asymmetric association between environmental factors (TEMP, HUM, PM2.5, PM10, CO, SO2, NO2, and O3) and the number of recovered patients from COVID-19. We observe significant heterogeneity in the association among variables across various quantiles. The findings suggest that TEMP, PM2.5, PM10, CO, NO2, and O3 are negatively related to the COVID-19 recovery, while HUM and SO2 show a positive association at most quantiles. The study recommends that maintaining a safe and comfortable environment for the patients may increase the chances of recovery from COVID-19. The success story of Wuhan, the initial epicenter of the novel coronavirus in China, can serve as an important case study for other countries to bring the outbreak under control. The current study could be conducive for the policymakers of those countries where the COVID-19 pandemic is still unrestrained.

On the indirect environmental outcomes of COVID-19: short-term revival with futuristic long-term implications.

The aim of this study is to identify and highlight the positive and negative indirect environmental impacts of COVID-19, with a particular focus on the most affected economies (USA, China, Spain, and Italy). In this respect, the empirical and theoretical dimensions of the contents of those impacts are analyzed. Research findings reveal a significant relationship between contingency actions and positive indirect impacts such as air quality improvements, clean beaches, and the decline in environmental noise. Besides, negative indirect impacts also exist, such as the rise in waste level and curtailment in recycling, further threatening the physical spaces (land and water), besides air. It is expected that global businesses will revive in the near future (though slowly), but the reduction in greenhouse gas emissions during this short time span is not a sustainable way of environmental mitigation. Thus, long-term mitigation policies should be strengthened to cope with the undesirable deterioration of the environment. Research findings provide an up-to-date glimpse of the pandemic from the perspectives of current and future indirect environmental impacts and the post-pandemic situation. Finally, it is suggested to invent and prepare action plans to induce a sustainable economic and environmental future in the post-pandemic world scenario.

Asymmetric nexus between COVID-19 outbreak in the world and cryptocurrency market

In the wake of recent pandemic of COVID-19, we explore its unprecedented impact on the cryptocurrencies' market. Specifically, we check how the changing intensity of the COVID-19 represented by the daily addition in new infections worldwide affects the daily returns of the top 10 cryptocurrencies according to the market capitalization. The results from Quantile-on-Quantile Regression (QQR) approach reveal that the changing intensity levels of the COVID-19 affect the Bearish and the Bullish market scenarios of cryptocurrencies differently (asymmetric impact). Additionally, there are differences between these currencies in their responses to the changing levels of this pandemic's intensity. Most of the currencies absorbed the small shocks of COVID-19 by registering positive gains but failed to resist against the huge changes except Bitcoin, ADA, CRO, and up to some extent Ethereum also. Our results reveal new and asymmetric dynamics of this emerging asset class against an extremely stressful and unpredictable event (COVID-19). Moreover, these results are robust to the use of alternative proxy (COVID-19 deaths) for pandemic intensity. Our findings help to improve investors and policymakers' understanding of the cryptocurrencies' market dynamics, especially in the times of extremely stressful and unseen events.

Effects of climatological parameters on the outbreak spread of COVID-19 in highly affected regions of Spain.

The coronavirus (COVID-19) pandemic is infecting the human population, killing people, and destroying livelihoods. This research sought to explore the associations of daily average temperature (AT) and air quality (PM2.5) with the daily new cases of COVID-19 in the top four regions of Spain (Castilla y Leon, Castilla-La Mancha, Catalonia, and Madrid). To this end, the authors employ Pearson correlation, Spearman correlation, and robust panel regressions to quantify the overall co-movement between temperature, air quality, and daily cases of COVID-19 from 29 February to 17 July 2020. Overall empirical results show that temperature may not be a determinant to induce COVID-19 spread in Spain, while the rising temperature may reduce the virus transmission. However, the correlation and regression findings illustrate that air quality may speed up the transmission rate of COVID-19. Our findings are contrary to the earlier studies, which show a significant impact of temperature in raising the COVID-19 spread. The conclusions of this work can serve as an input to mitigate the rapid spread of COVID-19 in Spain and reform policies accordingly.

Co-variance nexus between COVID-19 mortality, humidity, and air quality index in Wuhan, China: New insights from partial and multiple wavelet coherence.

The worldwide outbreak of COVID-19 disease has caused immense damage to our health and economic and social life. This research article helps to determine the impact of climate on the lethality of this disease. Air quality index and average humidity are selected from the family of climate variables, to determine its impact on the daily new cases of COVID-19-related deaths in Wuhan, China. We have used wavelet analysis (wavelet transform coherence (WTC), partial (PWC), and multiple wavelet coherence (MWC), due to its advantages over traditional time series methods, to study the co-movement nexus between our selected data series. Findings suggest a notable coherence between air quality index, humidity, and mortality in Wuhan during a recent outbreak. Humidity is negatively related to the COVID-19-related deaths, and bad air quality leads to an increase in this mortality. These findings are important for policymakers to save precious human lives by better understanding the interaction of the environment with the COVID-19 disease.

Correlation between environmental pollution indicators and COVID-19 pandemic: A brief study in Californian context.

In December 2019, the novel coronavirus COVID-19 outbreak was first detected in Wuhan Hubei province, China. The April 24, 2020, the Centers for Disease Control and Preventions (CDC) has confirmed more than 39,000 cases, including >1800 deaths. California's Governor Gavin Newsom ordered mandatory stay at home after World Health Organization (WHO) declared COVID-19 as a global pandemic in early March. We have evaluated the correlation between environmental pollution determinants and the COVID-19 outbreak in California by using the secondary published data from the Centers for Disease Control and the Environmental Pollution Agency (EPA). We employed Spearman and Kendall correlation tests to analyze the association of PM 2.5, PM 10, SO2, NO2, Pb, VOC, and CO with COVID-19 cases in California. Our findings indicate that environmental pollutants such as PM10, PM2.5, SO2, NO2, and CO have a significant correlation with the COVID-19 epidemic in California. Overall, our study is a useful supplement to encourage regulatory bodies to promote changes in environmental policies as pollution source control can reduce the harmful effects of environmental pollutants.

Asymmetric nexus between temperature and COVID-19 in the top ten affected provinces of China: A current application of quantile-on-quantile approach.

The present study examines the asymmetrical effect of temperature on COVID-19 (Coronavirus Disease) from 22 January 2020 to 31 March 2020 in the 10 most affected provinces in China. This study used the Sim & Zhou' quantile-on-quantile (QQ) approach to analyze how the temperature quantities affect the different quantiles of COVID-19. Daily COVID-19 and, temperature data collected from the official websites of the Chinese National Health Commission and Weather Underground Company (WUC) respectively. Empirical results have shown that the relationship between temperature and COVID-19 is mostly positive for Hubei, Hunan, and Anhui, while mostly negative for Zhejiang and Shandong provinces. The remaining five provinces Guangdong, Henan, Jiangxi, Jiangsu, and Heilongjiang are showing the mixed trends. These differences among the provinces can be explained by the differences in the number of COVID-19 cases, temperature, and the province's overall hospital facilitations. The study concludes that maintaining a safe and comfortable atmosphere for patients while COVID-19 is being treated may be rational.

The nexus between COVID-19, temperature and exchange rate in Wuhan city: New findings from partial and multiple wavelet coherence.

This study attempts to document the nexus between weather, COVID-19 outbreak in Wuhan and the Chinese economy. We used daily average temperature (hourly data), daily new confirmed cases of COVID-19 in Wuhan, and RMB (Chinese currency) exchange rate to represent the weather, COVID-19 outbreak and the Chinese economy, respectively. The methodology of Wavelet Transform Coherence (WTC), Partial Wavelet Coherence (PWC) and Multiple Wavelet Coherence (MWC) is employed to analyze the daily data collected from 21st January 2020 to 31st March 2020. The results have revealed a significant coherence between the series at different time-frequency combinations. The overall results suggest the insignificance of an increase in temperature to contain or slow down the new COVID-19 infections. The RMB exchange rate and the COVID-19 showed an out phase coherence at specific time-frequency spots suggesting a negative but limited impact of the COVID-19 outbreak in Wuhan on the Chinese export economy. Our results are contrary to many earlier studies which suggest a significant role of temperature in slowing down the COVID-19 spread. These results can have important policy implications for the containment of COVID-19 spread and macro-economic management with respect to changes in the weather.