Conditional dependence structure and risk spillovers between Bitcoin and fiat currencies

This paper investigates the extreme dependence and risk spillovers between Bitcoin and the currencies of the BRICS and G7 economies. We find time-varying dependence between Bitcoin and all currencies. Moreover, when analysing risk spillovers from Bitcoin to currencies, we find that Bitcoin exercises significant power over most currencies, with the South African rand and Brazilian real holding both the highest downside and upside risk before and during the COVID-19 pandemic period, respectively. When considering risk spillovers from currencies towards Bitcoin, the Japanese yen exhibits the highest downside spillovers. Importantly, we find asymmetric spillovers between extreme upward and downward movements. • We study dependencies between Bitcoin and the currencies of the BRICS and G7 economies. • We find time-varying dependence between Bitcoin and all of the fiat currencies. • Bitcoin exercises significant power over most of the considered currencies. • We find asymmetric spillovers between extreme upward and downward movements. [ FROM AUTHOR] Copyright of Emerging Markets Review is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Risk spillover network in the supply chain system during the COVID-19 crisis: Evidence from China.

The COVID-19 crisis seriously impacted the global economy and supply chain system. Unlike previous studies, this paper examines the risk spillover effects within the supply chain system rather than between financial and other specific industries. The hypotheses are proposed by developing and simulating an agent-based model; the copula-conditional value at risk model is employed to empirically validate these hypotheses in China during the COVID-19 crisis. The findings reveal that risks are transmitted and amplified from downstream, through midstream to upstream. Additionally, the financial industry amplifies the risk spillover from the midstream to the upstream and downstream. Moreover, the risk spillovers exhibit significant time-varying characteristics, and policy interventions can potentially mitigate the effect of such spillovers. This paper provides a theoretical basis and empirical evidence for risk spillover in supply chain systems and offers suggestions for industrial practitioners and regulators.

Do lower environmental, social, and governance (ESG) rated companies have higher systemic impact? Empirical evidence from Europe and the United States

In recent years, companies have increasingly been characterized by environmental, social, and governance (ESG) scores, and investors and academics have raised questions concerning financial performance and investment risks. Now, as the European Banking Authority has acknowledged that ESG risks can potentially impact the economic and financial system, the debate on systemic risk has gained traction. Understanding the relationship between ESG merit and systemic risk is of utmost importance for the stability of the economic and financial system, still, research is limited. Relying on real‐world European and United Stated data, we quantify systemic risk by means of QL‐CoVaR. Empirical analyses of the entire period from 2007 to 2021 show that companies with high ESG scores tend to exhibit low QL‐CoVaR values indicating a positive effect of ESG scores. Such evidence is confirmed by clustering the individual companies into ESG portfolios and focusing on COVID‐19. Additional insights using the individual pillars are also provided.

Diversification benefits of NFTs for conventional asset investors: Evidence from CoVaR with higher moments and optimal hedge ratios

This study investigates the risk and returns on one of the newest digital asset classes instruments, non-fungible tokens (NFTs), by accounting for tail dependence of higher-order moments and portfolio characteristics. We used a wide range of asset classes, encompassing equites, fixed income securities, and commodities, and document the desirable hedging and portfolio attributes of NFTs by employing Conditional Value-at-Risk (CoVaR) and ∆CoVaRs with various copula functions. We found that NFTs exhibit beneficial investment and hedging attributes under all market conditions, including the Covid-19 pandemic. Our findings have important implications for investors, risk managers, and regulators. © 2023 Elsevier B.V.

Explain systemic risk of commodity futures market by dynamic network

Since inflation of commodities is becoming more and more severe recently caused by many macro events, such as COVID-19 and Russian-Ukrainian conflict, systemic risk of commodity futures market is getting more attention from academic and industrial areas. Instead of using external factors to explain this risk as previous researches, we explain it by internal topology and structures of commodity futures market. This method helps us understand its key driving factors and their different impact to Chinese and international commodity futures markets. © 2023 Elsevier Inc.

Systemic risk contagion of green and Islamic markets with conventional markets.

Financial markets are exposed to extreme uncertain circumstances escalating their tail risk. Sustainable, religious, and conventional markets represent three different markets with various characteristics. Motivated with this, the current study measures the tail connectedness between sustainable, religious, and conventional investments by employing a neural network quantile regression approach from December 1, 2008 to May 10, 2021. The neural network recognized religious and conventional investments with maximum exposure to tail risk following the crisis periods reflecting strong diversification benefits of sustainable assets. The Systematic Network Risk Index spots Global Financial Crisis, European Debt Crisis, and COVID-19 pandemic as intensive events yielding high tail risk. The Systematic Fragility Index ranks the stock market in the pre-COVID period and Islamic stocks during the COVID sample as the most susceptible markets. Conversely, the Systematic Hazard Index nominates Islamic stocks as the chief risk contributor in the system. Given these, we portray various implications for policymakers, regulatory bodies, investors, financial market participants, and portfolio managers to diversify their risk using sustainable/green investments.

How Connected is Crude Oil to Stock Sectors Before and After the COVID-19 Outbreak? Evidence from a Novel Network Method

A novel network with Wavelet denoising-GARCHSK and Mixed CoVaR method is proposed to construct full-sample and dynamic networks for investigating the risk spillover effects across international crude oil and Chinese stock sectors before and after the COVID-19 outbreak. The empirical results denote that the total bidirectional oil-sector risk spillover effects increase rapidly after the COVID-19 outbreak. Interestingly, sectors shift from net risk receivers to net risk contributors in the oil-sector risk transfer effects during the pandemic period. Second, unlike the pre-COVID-19 period, Shanghai crude (SC) replaces Brent as the largest oil risk transmitter to stocks during the COVID-19 period. Third, there are notable sectoral features in the oil-sector risk spillovers, which differ across different periods. After the burst, Energy has an incredibly weak connection with crude oil, while the sectors, which oil products are input for, become close with crude oil. Far more surprising is that the petroleum-independent sectors have increasing closer risk transfer effects with crude, even becoming the largest risk contributors to oil, after that. Finally, the oil-sector relationships during the same period are time-varying but stable. This paper provides policymakers and investors with new method and insight into the oil-sector relationships. [ABSTRACT FROM AUTHOR] Copyright of Fluctuation & Noise Letters is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Debt default, financial risk transmission and governance from the perspective of supply chain network.

The stock risk spillovers of 31 associated enterprises of Evergrande supply chain in China were measured with DCC-GARCH and CoVaR model, and high, moderate and low risk overflow networks in four periods were constructed, finally the overall metrics and dynamic evolution of risk spillover network were explored. The results showed that: With COVID-19 under control in China, the risk spillover of Evergrande supply chain associated enterprises continues to diverge, with the quantity and scope of high risk declining and moderate and low risk rising; The infection scope of high risk spillover has narrowed, from indirect to direct infection; Evergrande subsidiaries play obvious bridge roles in moderate and low risk networks, have strong control over the risk spread; Commercial banks suffer and trigger more risk spillovers, a number of risk spillover groups with commercial banks as cores formed in high and moderate risk networks.

Systemic Risk Transmission from the United States to Asian Economies During the COVID-19 Period

The study investigates the systemic risk transmission from the US banking sector and the US market to the five most economically impacted Asian nations (Thailand, Malaysia, the Philippines, India, and Singapore) during the COVID-19 period of 2020. We consider the conditional value-at-risk (CoVaR) approach to estimate the systemic risk of the given economies at 5% quantile (for severe downturn risk) and 20% quantile (for moderate downturn risk). Our findings demonstrate a rise in systemic risk for these Asian countries in 2020, particularly in the first half of the year. The findings also provide evidence of the significant systemic risk transmission from the US banking sector and the US stock market to the majority of the given Asian economies at both quantiles. The study further highlights the significant contribution of the US financial market in increasing the systemic risk of the given Asian economies in 2020. We find similar results for systemic risk transmission from the UK, the European Union, and Japan to the given Asian economies. The findings have implications for market participants, risk managers, and regulators who are concerned with risk diversification and tracking the routes of risk shock transmission. JEL Codes: G10;G18;G20. © 2023 Institute of Financial Management and Research.

Stochastic ordering of systemic risk in commodity markets

The contribution of commodity risks to the systemic risk is assessed in this paper through a novel approach that relies on the stochastic property of concordance ordering of CoVaR. Considering the period that spans from 2005 to 2022 and the VIX as the proxy for the stability of the financial system, we build the stochastic ordering of systemic risk for 35 commodities belonging to four sectors: Agriculture, Energy, Industrial Metals, and Precious Metals. The estimates of the ΔCoVaR signal that contagion effects from commodity markets to the financial system have been stronger during the years 2017–2019. Backtests validate CoVaR as a more resilient risk measure than the VaR, especially during periods of market turmoils. The stochastic ordering of CoVaR shows that severe losses (downside risk) in commodity markets tend to exacerbate systemic financial distress more than gains (upside risk). Commodity risks arising from WTI and EUA are threatening triggers for systemic risk. In contrast, the financial system is less vulnerable to a broader range of scenarios arising from fluctuations in Gold prices. As top contributors to the systemic risk, among the sectors we find Energy and Precious Metals with respect to upside risk and downside risk. The Covid-19 crisis has deeply amplified the systemic influence arising from the downside risk of WTI, Gasoline, and Natural Gas UK and has confirmed the safe-haven role of Gold. © 2022 Elsevier B.V.

Breakup and default risks in the great lockdown

In this paper, we exploit CDS quotes for contracts denominated in different currencies and with different default clauses to estimate the risk of a breakup of the Eurozone and the propagation of breakup and default risks after the COVID-19 shock. Our main result is that the risk of a Eurozone breakup is significant although, quantitatively, it is not larger than in the period before the COVID-19 shock. In addition, we find that an increase in the redenomination risk in one country is associated with an increase in default premia and bond spreads in other Eurozone countries. Finally, we find that a sizeable fraction of the changes in the cost of insuring against redenomination and default reflects two additional factors: the first captures the insurance cost against a euro depreciation conditional on redenomination, while the second captures liquidity premia. © 2021 Elsevier B.V.

Do lower environmental, social, and governance (ESG) rated companies have higher systemic impact? Empirical evidence from Europe and the United States

In recent years, companies have increasingly been characterized by environmental, social, and governance (ESG) scores, and investors and academics have raised questions concerning financial performance and investment risks. Now, as the European Banking Authority has acknowledged that ESG risks can potentially impact the economic and financial system, the debate on systemic risk has gained traction. Understanding the relationship between ESG merit and systemic risk is of utmost importance for the stability of the economic and financial system, still, research is limited. Relying on real-world European and United Stated data, we quantify systemic risk by means of QL-CoVaR. Empirical analyses of the entire period from 2007 to 2021 show that companies with high ESG scores tend to exhibit low QL-CoVaR values indicating a positive effect of ESG scores. Such evidence is confirmed by clustering the individual companies into ESG portfolios and focusing on COVID-19. Additional insights using the individual pillars are also provided.

Stochastic ordering of systemic risk in commodity markets

The contribution of commodity risks to the systemic risk is assessed in this paper through a novel approach that relies on the stochastic property of concordance ordering of CoVaR. Considering the period that spans from 2005 to 2022 and the VIX as the proxy for the stability of the financial system, we build the stochastic ordering of systemic risk for 35 commodities belonging to four sectors: Agriculture, Energy, Industrial Metals, and Precious Metals. The estimates of the ΔCoVaR signal that contagion effects from commodity markets to the financial system have been stronger during the years 2017–2019. Backtests validate CoVaR as a more resilient risk measure than the VaR, especially during periods of market turmoils. The stochastic ordering of CoVaR shows that severe losses (downside risk) in commodity markets tend to exacerbate systemic financial distress more than gains (upside risk). Commodity risks arising from WTI and EUA are threatening triggers for systemic risk. In contrast, the financial system is less vulnerable to a broader range of scenarios arising from fluctuations in Gold prices. As top contributors to the systemic risk, among the sectors we find Energy and Precious Metals with respect to upside risk and downside risk. The Covid-19 crisis has deeply amplified the systemic influence arising from the downside risk of WTI, Gasoline, and Natural Gas UK and has confirmed the safe-haven role of Gold.

Analyzing the risk spillovers of international crude oil on China's corn and biofuel ethanol markets: A transition toward green economy and environmental sustainability

This study aims to analyze the risk spillover effects between the global crude oil market and the biofuel ethanol and corn markets in China, employing a DCC-GARCH-Copula-CoVaR model and basing the weekly price data from 2012 to 2021. The empirical results revealed that there were dynamic conditional correlations among international crude oil, China's biofuel ethanol, and corn markets. Following the COVID-19 outbreak, the CoVaR and Delta CoVaR changed, which caused a sharp increase in the mean values and volatility. Additionally, China's biofuel ethanol market is more vulnerable to the risk spillovers from the international crude oil market than China's corn market. However, China's markets do not appear to have obvious risk spillover effects on the global market. The implications of the results are discussed in financial market supervision, including the risk management and portfolio adjustment.

Banking systemic risk estimating of China's banking industry during the COVID-19 pandemic-based on complex network theory.

The spread of COVID-19 worldwide has led to significant fluctuations in the global financial market, and the banking industry has also been exposed to the dual impact of the real economy and the financial market. In this paper, Chinese bank networks in different COVID-19 periods were constructed using CoVaR model and least absolute shrinkage and selection operator (LASSO) regression, and the characteristics and risk changes of the proposed bank networks were analyzed based on complex network theory. Additionally, the index of complex network theory was combined with the non-performing loan ratio of banks to build a new index for evaluating and measuring the systemic risk of banks in different periods. It was found that the network density, clustering coefficient and average network strength of banking networks increased during the COVID-19 pandemic, while the level of inter-bank correlation, and the systemic risk of banking networks increased. It was suggested after using the new indicators that joint-stock commercial banks and rural commercial banks were the main risk spillovers in different periods, and the systemic risk of these banks had increased during COVID-19. Therefore, the supervision of joint-stock commercial and rural commercial banks should be strengthened to prevent the risks from spreading to these banks during the COVID-19 pandemic.

The impact of the COVID-19 pandemic on the global dynamic spillover of financial market risk.

The COVID-19 outbreak has greatly impacted the stability of the global financial markets. In the post-COVID-19 pandemic era, the risk contagion patterns of the global financial markets may change. This paper utilizes the conditional value-at-risk (ΔCoVaR) model to measure the risk level of the financial markets in various economies and uses the TVP-VAR-CONNECTEDNESS approach to construct a time-varying spillover index. Based on the dimensions of time and space, we explored the contagion path, contagion status, and contagion structure characteristics of global financial market risk before and during the COVID-19 pandemic. The results entail several conclusions. (i) The COVID-19 pandemic increased the spillover level of global financial market risk and the risk connectedness of financial markets in different countries. In addition, during the concentrated outbreak period of COVID-19, the risk spillover level in developing countries rose rapidly, while the financial risk spillover level in developed countries decreased significantly. (ii) The impact of the COVID-19 pandemic on the spillover of the global financial market risk is time-varying, and there is a strong correlation between the risk spillover level of the financial markets of the world and the severity of the COVID-19 pandemic. (iii) Due to the impact of the COVID-19 pandemic, Brazil, Canada, and Russia have become new risk spillover centers; in the post-COVID-19 pandemic era, China's spillover to developed countries has increased, and the financial influence of China has also gradually increased. In addition, the risk contagion capacity of financial markets among European countries is gradually converging. (iv) During the concentrated outbreak of the COVID-19 pandemic, the Americas were the main exporter of global financial market risk, while Europe played a role in risk absorption.

Spillovers and diversification benefits between oil futures and ASEAN stock markets

This study combines copula functions, wavelet decomposition and conditional VaR methods to examine spillovers and diversification benefits between oil futures and ASEAN stock markets (Indonesia, Philippines, Malaysia, Singapore, Vietnam and Thailand). The results show zero tail dependence between oil and stock returns at the short term. In contrast, we find a lower tail independence and an upper tail dependence at the long term. Our results highlight that oil futures serve as hedge assets at short term and a safe haven asset at the long term. Furthermore, we find significant and asymmetric risk spillovers from oil to ASEAN markets. The downside and upside spillovers are higher at the long term than short term and increase during the GFC, the recent oil crisis, and COVID-19 periods. Finally, we show that an equally weighted portfolio provides highest diversification benefits at both lower and medium tail distributions with the exception of Malaysian market. The diversification benefits of oil are sizeable for less coupling markets and fall during times of GFC and oil crisis.

Risk spillover analysis of China’s financial sectors based on a new GARCH copula quantile regression model

This study employs a new GARCH copula quantile regression model to estimate the conditional value at risk for systemic risk spillover analysis. To be specific, thirteen copula quantile regression models are derived to capture the asymmetry and nonlinearity of the tail dependence between financial returns. Using Chinese stock market data over the period from January 2007 to October 2020, this paper investigates the risk spillovers from the banking, securities, and insurance sectors to the entire financial system. The empirical results indicate that (i) three financial sectors contribute significantly to the financial system, and the insurance sector displays the largest risk spillover effects on the financial system, followed by the banking sector and subsequently the securities sector;(ii) the time-varying risk spillovers are much larger during the global financial crisis than during the periods of the banking liquidity crisis, the stock market crash and the COVID-19 pandemic. Our results provide important implications for supervisory authorities and portfolio managers who want to maintain the stability of China’s financial system and optimize investment portfolios.

Cryptocurrency Bubble on the Systemic Risk in Global Energy Companies

Financialization has brought new challenges to the international energy markets, making energy systemic risk a more complicated issue. One of the important fea-tures is the development of cryptocurrency, which has become a critical part of the global financial markets. As a consequence, the rise and fall of cryptocurrency can have nonnegligible impacts on the systemic risks in the international energy sec-tor. This paper empirically tests this hypothesis using the equity data of the top 100 energy companies from 2014 to 2021. Specifically, we explore the extreme shocks of cryptocurrency using multiple bubble tests, and then we test to what extent bubbles in cryptocurrency markets can affect systemic risk in the energy sector. Our empirical results show that the formation of cryptocurrency bubbles, especially when the bubbles burst, significantly increases systemic risks in the energy sector. This effect retains the same in the recent COVID-19 pandemic period. In addition, oil and gas companies play an essential channel in the risk spillover from crypto-currency markets to the international energy markets. © 2022 by the IAEE. All rights reserved.

Tail-risk spillovers from China to G7 stock market returns during the COVID-19 outbreak: A market and sectoral analysis.

This study uses a combination of copulas and CoVaR to investigate risk spillovers from China to G7 countries before and during the COVID-19 pandemic. Using daily data on stock and equity sectors for the period from January 1, 2013 to June 9, 2021, the main empirical results show that, before the COVID-19 pandemic, stock markets were positively related and systemic risk was comparable for all countries. However, during the COVID-19 outbreak, the level of dependence increased for all G7 countries and the upside-downside risk spillovers become on average higher for all stock markets, with the exception of Japan. Our results also provide evidence of higher market risk exposure to information from China for the technology and energy sectors. Moreover, we find an asymmetric risk spillover from China to the G7 stock markets, with higher intensity in downside risk spillovers before and during COVID-19 spread.