Pandemic-driven financial contagion and investor behavior: Evidence from the COVID-19

This paper studies the pandemic-driven financial contagion during the COVID-19 period and the impact of investor behavior on it by constructing three types of direct behavior measurements based on Google search volumes. More specifically, using a sample of 26 major stock markets around the world during the COVID-19 pandemic, we construct a non-linear financial contagion network via a dynamic mixture copula-EVT (extreme value theory) model to quantitatively detect and measure the complex nature of pandemic-driven financial contagion. Furthermore, through constructing direct investor behavior measurements including investor attention, sentiment, and fear, we find investor behavior plays an important role in explaining pandemic-driven financial contagion. We also find that the impacts of investor behavior on the pandemic-driven financial contagion are heterogeneous under several different settings, including market conditions, market development levels, regional subsets, and contagion directions.     

Covid-19 pandemic and spillover effects in stock markets: A financial network approach

This paper examines the impact of the COVID-19 pandemic on 51 major stock markets, both emerging and developed. We isolated the countries susceptible to shock transmissions, and evaluated countries with immunity, during the lockdown. Specifically, using dependence dynamics and network analysis on a bivariate basis, we identify volatility and contagion risk among stock markets during the COVID-19 pandemic. The empirical findings add to the existing body of literature, given that previous work has not placed emphasis on network topologic metrics when it comes to financial networks, specifically during the COVID-19. The evidence shows instant financial contagion a result of the lockdown and the spread of the novel coronavirus. The methodological framework outlines important information for investors and policymakers on using financial networks to improve portfolio selection, by placing an emphasis on assets according to centrality.     

Financial contagion effects of major crises in African stock markets

This study examines financial contagion effects in African stock markets during major crises over the period 2005 to 2020. We investigate contagion effects in individual stock markets and from a regional perspective using dynamic conditional correlations during the global financial crisis, European debt crisis, Brexit, and COVID-19. The empirical evidence confirms contagion effects in some individual markets. However, significant evidence of contagion is found only during the global financial crisis from the regional perspective. Our findings suggest that the regional impacts of crises differ due to the nature of those crises. We also find financial contagion increases in the country-level risk, market capitalization and export to GDP and decreases in corruption.     

Financial contagion intensity during the COVID-19 outbreak: A copula approach

The sudden and rapid spread of the novel coronavirus (COVID-19) has had a severe impact on financial markets and economic activities all over the world. The purpose of this paper is to investigate the existence and intensity of financial contagion during the COVID-19 outbreak. We use daily series of stock indexes of 10 Asian countries (Taiwan, Hong Kong, Singapore, India, Indonesia, Malaysia, South Korea, Vietnam, Australia and China) and 4 American countries (the United-States, Brazil, Mexico, and Argentina) over the period starting from January 1st, 2014 to June 30th, 2021. Based on a copula approach, the results show that all studied markets are affected by the COVID-19 outbreak and the presence of financial contagion for all American and Asian countries. The results also show that contagion is more intense for American countries than Asian ones. These findings have practical implications, especially for investors, risk managers, and policy makers. The latter should continue to provide liquidity to the international market during this pandemic.     

Capture the contagion network of bitcoin – Evidence from pre and mid COVID-19

COVID-19 is the first global scale crisis since the inception of Bitcoin. We compare the contagion phenomenon of Bitcoin and other financial markets or assets pre and during the COVID-19 shock in both contemporaneous and non-contemporaneous manner. This paper uses the directed acyclic graph (DAG), spillover index, and network topology to provide strong evidence on the directional contagion outcomes of Bitcoin and other assets. The empirical results show that the contagion effect between Bitcoin and developed markets is strengthened during the COVID-19 crisis. Particularly, European market has a dominant role. Excluding Bitcoin’s own shocks, United State and European markets are the main contagion sources to Bitcoin. European market also works as a intermediary to deliver infectious from United State and market fear. The findings show that gold always has contagion effect with Bitcoin, while gold, US dollar and bond market are the contagion receivers of Bitcoin under the shock of COVID-19. The empirical results further proved the safe haven, hedge and diversifier potential of Bitcoin in economic stable time, but also shows that the sustainability of these properties is undermined during the market turmoil.     

Interconnected multilayer networks: Quantifying connectedness among global stock and foreign exchange markets

This paper proposes a novel interconnected multilayer network framework based on variance decomposition and block aggregation technique, which can be further served as a tool of linking and measuring cross-market and within-market contagion. We apply it to quantifying connectedness among global stock and foreign exchange (forex) markets, and demonstrate that measuring volatility spillovers of both stock and forex markets simultaneously could support a more comprehensive view for financial risk contagion. We find that (i) stock markets transmit the larger spillovers to forex markets, (ii) the French stock market is the largest risk transmitter in multilayer networks, while some Asian stock markets and most forex markets are net risk receivers, and (iii) interconnected multilayer networks could signal the financial instability during the global financial crisis and the COVID-19 crisis. Our work provides a new perspective and method for studying the cross-market risk contagion.     

Dynamic spillovers across oil,gold and stock markets in the presence of major public health emergencies

Extreme events have a systemic impact on global financial markets, leading to significant cross-market spillovers in the oil, gold, and stock markets and raising widespread concerns about market linkages and risk contagion. In this paper, with a focus on both return and volatility, a frontier spillover network analysis is used to examine the strength and scale characteristics of spillovers in the oil, gold and stock markets under major public health emergency shocks. In addition, the paper adopts a marginal spillover and network analysis to evaluate linkage relationships, risk sources and transmission paths in the oil, gold, and stock markets during such events. The results show that the return and volatility spillover effects generated across the oil, gold, and stock markets are significant, with return spillovers being more stable and volatility spillovers being highly sensitive to emergencies. Meanwhile, the COVID-19 pandemic has displayed the strongest return and volatility spillovers. The high intensity of the shocks during the COVID-19 period has changed the usual characteristics of the market, with the gold market becoming the risk receiver and the oil market becoming risk sources.     

Risk contagion of COVID-19 in Japanese firms: A network approach

The novel coronavirus disease (COVID-19) is one of the worst pandemics in human history. Our research objective is to assess the contagion effect on Japanese firms and to evaluate the Japanese government's COVID-19 measures during the period from April 7, 2020, to May 25, 2020. We propose a susceptible-infected-recovered-dead model for COVID-19 and derive COVID-19 parameters for Japan. Subsequently, we analyze the effect of COVID-19 on Japanese firms through correlation-based network and credit risk analyses. The main findings are that the Tokyo Stock Price Index moved in the opposite direction of COVID-19 parameters and COVID-19 parameters are almost the only risk factors that impact a firm's credit risk during the period. Finally, we find that the interconnection analysis between the COVID-19 infection network and the financial networks contribute to the existing pandemic risk management knowledge.     

Have the predictability of oil changed during the COVID-19 pandemic: Evidence from international stock markets

The COVID-19 has undoubtfully brought fierce shocks to the real economic activities, financial market and public lives. Under this special condition, this study explores whether the predictability of crude oil futures information has changed before and during the COVID-19 pandemic for 19 international stock markets. From an in-sample perspective, we find that the crude oil futures RV can significantly affect future stock volatility for each equity index except SSEC. Moreover, the out-of-sample results from statistic and economic perspective reveal that crude oil futures RV is a more efficient predictor during the COVID-19 pandemic compared with the pre-crisis period. Furthermore, we find that the predictability of crude oil futures information is stronger from March to May 2020, when the epidemic is seriously prevailing. The empirical results from alternative evaluation method, recursive window method, alternative realized measures, controlling VIX and the seasonal effect, asymmetric forecasting window and different testing windows are robust and consistent. Our findings could offer novel and significant policy and practical implications.     

Stock markets’ reaction to COVID-19: Cases or fatalities?

In this paper, we examine the stock markets’ response to the COVID-19 pandemic. Using daily COVID-19 confirmed cases and deaths and stock market returns data from 64 countries over the period January 22, 2020 to April 17, 2020, we find that stock markets responded negatively to the growth in COVID-19 confirmed cases. That is, stock market returns declined as the number of confirmed cases increased. We further find that stock markets reacted more proactively to the growth in number of confirmed cases as compared to the growth in number of deaths. Our analysis also suggests negative market reaction was strong during early days of confirmed cases and then between 40 and 60 days after the initial confirmed cases. Overall, our results suggest that stock markets quickly respond to COVID-19 pandemic and this response varies over time depending on the stage of outbreak.     

新冠肺炎疫情、金融市场震荡与金融危机

新型冠状病毒感染肺炎疫情在全球快速蔓延后,美国等国家金融市场出现大幅度震荡,历史罕见。金融市场震荡是疫情影响投资者信心,金融市场本身的风险需要释放,以及经济基本面悲观预期等因素共同作用的结果。目前来看,疫情对实体经济造成冲击,疫情应对情况也在很大程度上决定了金融市场震荡是否演化为全球金融危机,国外金融市场震荡对国内金融市场的传导需要审慎理性处理。     

Analysis of risk correlations among stock markets during the COVID-19 pandemic

The outbreak of the COVID-19 pandemic significantly negatively impacted the global economy and stock markets. This paper investigates the stock-market tail risks caused by the COVID-19 pandemic and how the pandemic affects the risk correlations among the stock markets worldwide. The conditional autoregressive value at risk (CAViaR) model is used to measure the tail risks of 28 selected stock markets. Furthermore, risk correlation networks are constructed to describe the risk correlations among stock markets during different periods. Through dynamic analysis of the risk correlations, the influence of the COVID-19 pandemic on stock markets worldwide is examined quantitatively. The results show the following: (i) The COVID-19 pandemic has caused significant tail risks in stock markets in most countries, while the stock markets of a few countries have been unaffected by the pandemic. (ii) The topology of risk correlation networks has become denser during the COVID-19 pandemic. The impact of the COVID-19 pandemic makes it easier for risk to transfer among stock markets. (iii) The increase in the closeness of the risk relationship between countries with lower economic correlation has become much higher than that between counties with higher economic correlation during the COVID-19 pandemic. For researchers and policy-makers, these findings reveal practical implications of the risk correlations among stock markets.     

全球股票市场间风险传染的测度、监管及预警

近年来,伴随金融一体化程度的加深,全球各股票市场间风险传染的动态复杂性加剧,其准确测度、高效监管及实时预警已成为优先事项。本研究选取全球21个代表性股票市场作为分析样本,首先基于广义向量自回归模型的滚动估计准确测度其间风险动态传染的高维网络序列,进一步借由矩阵值因子模型来稳健收缩上述序列,以探究其潜在动态核心结构,从而实现高效监管。最后,通过向量自回归模型的预测功能实现对全球股票市场间风险传染的实时预警。研究表明,全球股票市场间风险传染具有时变性,其监管与预警可通过少数与地理区域高度相关的风险区域间的动态传染关系及内部的市场构成来刻画。与此同时,我们发现中国内地等新兴市场的重要地位逐渐凸显。本文研究结论可为有效防范与化解金融风险提供有益参考。     

Impacts of COVID-19 outbreak,macroeconomic and financial stress factors on price spillovers among green bond

We examine the impacts of the COVID-19 pandemic and global risk factors on the upside and downside price spillovers of MSCI global, building, financial, industrial, and utility green bonds (GBs). Using copulas, CoVaR, and quantile regression approaches, we show symmetric tail dependence between MSCI global GB and both building and utility GBs. Moreover, the upper tail dependence between MSCI global GB and financial GB intensified during COVID-19. We find asymmetric risk spillovers from MSCI global GB to the remaining GBs. Finally, the COVID-19 spread, the Citi macro risk index, and the financial condition index contribute positively to the quantiles' risk spillovers. The spillover index method shows significant dynamic volatility spillovers from global GB to GB sectors that intensify during the pandemic outbreak, except for financial GB. The causality-in-mean and in-variance from COVID-19, Citi macro risk index, and US financial condition index to the downside and upside spillover effects are sensitive to quantiles     

The 2008 financial crisis: Stock market contagion and its determinants

In this paper, we investigate worldwide contagion and its determinants during the 2008 financial crisis. Utilizing an international sample of returns from 2003 to 2009, we consider both uni- and bi-directional contagion. After controlling for crisis-related volatility, we find strong evidence that cross-market linkages increase among many financial markets. In contrast to previous crises, contagion following the 2008 global financial crisis is not confined to emerging markets. The United States and other mature financial markets in the sample transmit and receive contagion. Country markets are less influenced by regions than they are by other country markets. We also construct variables that represent relative changes in economic variables before and during the crisis. We find that both economic fundamentals such as trade structure, interest rates, inflation rates, industrial production, and regional effects, and investors’ risk aversion contribute to international contagion.     

全球股票市场间风险传染的测度、监管及预警

近年来,伴随金融一体化程度的加深,全球各股票市场间风险传染的动态复杂性加剧,其准确测度、高效监管及实时预警已成为优先事项。本研究选取全球21个代表性股票市场作为分析样本,首先基于广义向量自回归模型的滚动估计准确测度其间风险动态传染的高维网络序列,进一步借由矩阵值因子模型来稳健收缩上述序列,以探究其潜在动态核心结构,从而实现高效监管。最后,通过向量自回归模型的预测功能实现对全球股票市场间风险传染的实时预警。研究表明,全球股票市场间风险传染具有时变性,其监管与预警可通过少数与地理区域高度相关的风险区域间的动态传染关系及内部的市场构成来刻画。与此同时,我们发现中国内地等新兴市场的重要地位逐渐凸显。本文研究结论可为有效防范与化解金融风险提供有益参考。     

Crude oil market and stock markets during the COVID-19 pandemic: Evidence from the US,Japan, and Germany

We analyzed the return and volatility spillover between the COVID-19 pandemic in 2020, the crude oil market, and the stock market by employing two empirical methods for connectedness: the time-domain approach developed by Diebold and Yilmaz (2012) and the method based on frequency dynamics developed by Barunik and Krehlik (2018). We find that the return spillover mainly occurs in the short term; however, the volatility spillover mainly occurs in the long term. From the moving window analysis results, the impact of COVID-19 created an unprecedented level of risk, such as plummeting oil prices and triggering the US stock market circuit breaker four times, which caused investors to suffer heavy losses in a short period. Furthermore, the impact of COVID-19 on the volatility of the oil and stock markets exceeds that caused by the 2008 global financial crisis, and continues to have an effect. The impact of the COVID-19 pandemic on financial markets is uncertain in both the short and long terms. Our research provides some urgent and prominent insights to help investors and policymakers avoid the risks in the crude oil and stock markets because of the COVID-19 pandemic and reestablish economic development policy strategies.     

Explaining stock markets' performance during the COVID-19 crisis: Could Google searches be a significant behavioral indicator?

The purpose of this study is to examine the impact of the pandemic on the performance of stock markets, focusing on the behavioral influence of the fear due to COVID-19. Using a data set of 10 developed countries during the period December 31, 2019, to September 30, 2020, we examine the impact of COVID-19 on the performance of the stock markets. We incorporate the impact of the COVID-19 pandemic using the following variables: (a) the number of new COVID-19 cases, which was widely used as the main explanatory variable for market performance in early financial studies, and (b) a Google Search index, which collects the number of Google searches related to COVID-19 and incorporates the health risk and the fear of COVID-19 (the higher the number of searches for Covid terms, the higher the index value, and the higher the fear index). We employ our input into an EGARCH(1,1,1) model, and the findings show that the Google Search index enables us to draw statistically significant information regarding the impact of the COVID-19 fear on the performance of the stock markets. On the other hand, the variable of the number of new COVID-19 cases does not have any statistically significant influence on the performance of the stock markets. Google searches could be a useful tool for supporters of behavioral finance, scholars, and practitioners.     

Time-frequency spillovers among carbon,fossil energy and clean energy markets: The effects of attention to climate change

We explore the time-frequency spillovers among carbon, fossil energy and clean energy markets, and consider the casual effects of climate change attention. The spillover effects among carbon, fossil energy and clean energy markets are time-varying. Carbon market is a net receiver of spillovers from the oil market and clean energy markets in the short term, but it becomes a net transmitter of spillovers to the coal and gas markets in the long term. Our marginal spillover effects analysis suggests that the COVID-19 pandemic has increased cross-market risk contagion in the long term and that carbon market bears larger input risks. Investors' attention to climate change has significant causal effects on the spillovers, and the causal impact of climate change attention on total spillover has significantly increased during the COVID-19 pandemic. Our findings provide important guidelines for investment in environmental protection and demonstrate the importance of formulating differentiated policies for environmental protection in different time horizons.     

The Eurozone banking sector in the time of COVID-19: Measuring volatility connectedness

This article investigates the volatility connectedness of the Eurozone banking system over the last 15 years (from 2005 to 2020). Applying the Diebold-Yilmaz Connectedness Index model to the daily stock return volatilities of 30 major Eurozone banks, we are able to measure the risk spillover effects and to capture the COVID-19 outbreak's impact on banking stability. The empirical findings show that the 30 banks are highly interconnected. Furthermore, we show the strong impact of the COVID-19 pandemic on the volatility dynamics, i.e., on the structure of the Eurozone banking system. Dynamically, we find that volatility connectedness increases during crises, reaching its maximum peak at the time of COVID-19. The analysis points out the critical role of volatility transmission played by large banks, highlighting the “too-big-to-fail” characteristic of this banking system. However, we find that small-medium banks are important actors of contagion, supporting the thesis that the Eurozone banking system is also “too-interconnected to fail.” Finally, we document the heterogeneity effect of the COVID-19 pandemic between Eurozone banking systems. This heterogeneity impact could be a future source of financial instability within the Eurozone.