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.     

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.     

Tail risk contagion between international financial markets during COVID-19 pandemic

In this paper, we combine the time-varying financial network model and FARM-selection approach to analyze the tail risk contagion between international financial market during the COVID-19 epidemic. Since the tail risk acts as a global transmission channel, we use the sample of 19 international financial markets to explore the contagion of tail risk during the epidemic. We find that the COVID-19 epidemic increases the number of contagion channels in the international financial system. The clustering level of the financial system has a significant growth during the COVID-19 pandemic, and the number of risk drivers is also larger than risk takers. The key financial market of each international financial network is related to the epidemic country. We also consider the tail risk contagion in local financial markets and find that the COVID-19 pandemic has an important influence on the tail risk contagions in local network systems     

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.     

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.     

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.     

Return connectedness across asset classes around the COVID-19 outbreak

In this paper, we show evidence of a dramatic change in the structure and time-varying patterns of return connectedness across various assets (gold, crude oil, world equities, currencies, and bonds) around the COVID-19 outbreak. Using the TVP-VAR connectedness approach, the results show that the dynamic total connectedness across the five assets was moderate and quite stable until early 2020. After that, the total connectedness spikes and the structure of the network of connectedness alters, which concurs with the COVID-19 outbreak. The equity and USD indices are the primary transmitters of shocks before the outbreak, whereas the bond index becomes the main transmitters of shocks during the COVID-19 outbreak. However, the USD index is a net receiver of shocks to other assets during the outbreak period. Furthermore, using a recently developed newspaper-based index of uncertainty in financial markets due to infectious diseases to capture the recent impact of COVID-19, we find that connectedness is positively related to this index, and increases at higher levels (conditional quantiles) of connectedness. Overall, our results reflect the speedy disturbing effects of the COVID-19 outbreak, which matters to the formulations of policies seeking to achieve financial stability. The results also indicate a possibility to threaten investors’ portfolios and fade the benefits of diversification.     

Impact of COVID-19 on stock market efficiency: Evidence from developed countries

This study investigates the impact of the novel coronavirus (COVID-19) pandemic on stock market efficiency for six hard-hit developed countries, namely, the United States (US), Spain, the United Kingdom (UK), Italy, France, and Germany. Applying the wild bootstrap automatic variance ratio test on daily stock market data from July 29, 2019 to January 25, 2021, it is found that all stock markets used in this study deviate from market efficiency during some periods of the pandemic. Deviations from market efficiency are seen more in the stock markets of the US and UK during the COVID-19 outbreak than in other stock markets. These results are strengthened when a different econometric method, the automatic portmanteau test, is used. The findings of this study indicate an increasing chance for stock price predictions and abnormal returns during the COVID-19 pandemic.     

A multilateral approach to examining the comovements among major world equity markets

This study investigates the comovement in stock indices among major developed markets, where Morgan Stanley Capital International (MSCI) indices are employed for the purposes of the study. We employ a model that accommodates multilateral international impacts on equity index movements. The empirical results reveal the existence of significant international transmission effects among these major world markets, both in terms of returns and volatility, and mostly in a positive direction. The U.S. market, as expected, is the leading market in the sense that it has the most pervasive and significant impact on all markets across continents. However, the U.S. market exhibits a different relationship with European markets from that with Asia-Pacific markets. The evidence also suggests that strong regional transmission effects exist. A further investigation using the extended model reveals that the linkages between U.S. and European markets are driven by positive global common forces and by negative international competitive effects. On the other hand, the U.S. and Asian markets are linked through positive global common forces and positive international contagion effects. The United States, Canada, and the U.K. are the three markets that still demonstrate contagion influence over countries outside its own region. The Asia-Pacific markets are more susceptible to contagion effects. Finally, it is interesting to find that Japanese market performance became more contagious toward other markets during the Asian financial crisis period.     

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.     

An empirical analysis of herd behavior in global stock markets

This paper examines herding behavior in global markets. By applying daily data for 18 countries from May 25, 1988, through April 24, 2009, we find evidence of herding in advanced stock markets (except the US) and in Asian markets. No evidence of herding is found in Latin American markets. Evidence suggests that stock return dispersions in the US play a significant role in explaining the non-US market’s herding activity. With the exceptions of the US and Latin American markets, herding is present in both up and down markets, although herding asymmetry is more profound in Asian markets during rising markets. Evidence suggests that crisis triggers herding activity in the crisis country of origin and then produces a contagion effect, which spreads the crisis to neighboring countries. During crisis periods, we find supportive evidence for herding formation in the US and Latin American markets.     

The impact of COVID-19 pandemic on transmission of monetary policy to financial markets

This study uses event-study methodology to estimate the impact of the COVID-19 pandemic on the transmission of monetary policy to financial markets, based on a sample of 37 countries with severe pandemics. Financial markets include government bond, stock, exchange rate and credit default swap markets. The results suggest that the emergence of pandemic has weakened the transmission of monetary policy to financial markets to a more significant degree. During our sample period following the outbreak of pandemic, neither conventional nor unconventional monetary policies have significant effects on all four of the financial markets. Of course, the unconventional monetary policies are slightly more effective as they can affect the stock and exchange rate markets to some extent. Therefore, in the post-pandemic period, if the monetary policy is used to stimulate financial markets, stronger policy adjustments, or other macro policies such as fiscal policies, may be needed to achieve the desired effect     

Stock market cycles, financial liberalization and volatility

In this paper we analyze the cycles of the stock markets in four Latin American and two Asian countries, and we compare their characteristics. We divide our sample in two subperiods in order to account for differences induced by the financial liberalization processes of the early 1990s. We find that cycles in emerging countries tend to have shorter duration and larger amplitude and volatility than in developed countries. However, after financial liberalization Latin American stock markets have behaved more similarly to stock markets in developed countries whereas Asian countries have become more dissimilar. Concordance of cycles across markets has increased significantly over time, especially for Latin American countries after liberalization.     

Financial market interdependencies: A quantile regression analysis of volatility spillover

This paper investigates the degree and structure of interdependence between emerging (Asian and Latin American) and developed (USA and Japan) stock markets through the study of volatility spillovers for the period spanning from January 1, 1993 to October 13, 2010. Using both standard GARCH model and quantile regression approach, we find the evidence of significant interdependence between financial markets which may give evidence of volatility transmission. The volatility transmission is closely associated with geographical proximity as well as with crisis periods which confirm the presence of contagion. The analysis of upper and lower quantiles allows observing that the interdependence increases during bullish markets while decreases during bearish markets. Accordingly, the structure of interdependence is asymmetric for both Asian and Latin American emerging markets. These findings open up new insights for government policy makers as well as for managerial purposes.     

The recovery of global stock markets indices after impacts due to pandemics

The COVID-19 brings back the debate about the impact of disease outbreaks in economies and financial markets. The error correction terms (ECT) and cointegration processing tools have been applied in studies for identifying possible transmission mechanisms between distinct time series. This paper adopts the vector error correction model (VECM) to investigate the dynamic coupling between the pandemics (e.g., the COVID-19, EBOLA, MERS and SARS) and the evolution of key stocks exchange indices (e.g., Dow-Jones, S&P 500, EuroStoxx, DAX, CAC, Nikkei, HSI, Kospi, S&P ASX, Nifty and Ibov). The results show that the shocks caused by the diseases significantly affected the markets. Nonetheless, except for the COVID-19, the stock exchange indices reveal a sustained and fast recovering when an identical length time window of 79 days is analyzed. In addition, our findings contribute to point a higher volatility for all financial indices during the COVID-19, a strong impact over the Ibov-Brazil and its poor recover when compared to the other indices.     

Does COVID-19 open a Pandora's box of changing the connectedness in energy commodities?

With the rapid spread of coronavirus, the global financial markets have been undergoing tremendous changes, which bring investors more risks in the short term. Against such background, this study concentrates on the far-reaching energy commodities, aiming to explore the impact of COVID-19 on cross-market linkages. To capture the dynamic nature of interdependence, we applied the TVP-VAR based connectedness index method and individually focused on the total, net, and pairwise connectedness. The empirical results show that there is a dramatic rise in the total connectedness in energy markets following the outbreak of COVID-19, but this change only lasted about two months and then fell back to the prior level. Further analyzing the net spillover conditions, we find that the connectedness structure has also displayed some temporary changes. At last, the spillover networks indicate that there are only three pairwise connectedness relations have changed in direction before and after the outbreak of COVID-19. We also try to discuss the underlying COVID-19 shock propagation mechanism, and the results suggest the significant mediation effect of the financial panic risk. In general, our study offers several urgent and prominent implications to understand the financial impact of COVID-19.     

‘Slow-burn’ spillover and ‘fast and furious’ contagion: a study of international stock markets

‘Fast and furious’ contagion across capital markets is an important phenomenon in an increasingly integrated financial world. Different from ‘slow-burn’ spillover or interdependence among these markets, ‘fast and furious’ contagion can occur instantly. To investigate this kind of contagion from the US, Japan and Hong Kong to other Asian economies, we design a research strategy to capture fundamental interdependence, or ‘slow-burn’ spillover, among these stock markets as well as short-term departures from this interdependence. Based on these departures, we propose a new contagion measure which reveals how one market responds over time to a shock in another market. We also propose international portfolio analysis for contagion via variance decomposition from the portfolio manager’s perspective. Using this research strategy, we find that the US stock market was cointegrated with the Asian stock markets during four specific periods from 3 July 1997 to 30 April 2014. Beyond this fundamental interdependence, the shocks from both Japan and Hong Kong have significant ‘fast and furious’ contagion effects on other Asian stock markets during the US subprime crisis, but the shocks from the US have no such effects.     

Measuring financial contagion: A Copula approach

This paper models dependence with switching-parameter copulas to study financial contagion. Using daily returns from five East Asian stock indices during the Asian crisis, and from four Latin American stock indices during the Mexican crisis, it finds evidence of changing dependence during periods of turmoil. Increased tail dependence and asymmetry characterize the Asian countries, while symmetry and tail independence describe the Latin American case. Structural breaks in tail dependence are a dimension of the contagion phenomenon. Therefore, the rejection of the correlation breakdown hypothesis should not be considered, without further investigation, as evidence of a stable dependence structure.     

Are stock market crises contagious? The role of crisis definitions

Financial contagion studies generally examine whether co-movement between markets increases during a crisis. We use a flexible co-movement measure to examine how conclusions of such analyses depend on the sample chosen as the ‘crisis’. To this end, we analyse stock market co-movement during the 1997 Asian crisis and the 2007 global financial crisis for all possible source countries and for all possible time periods or extreme return quantiles. This way we account for the main crisis dating approaches adopted in the literature. Our results suggest there is no clear relationship between excess co-movement and commonly used crisis samples.