Contagion Channels Research Articles

Tests of Global Flights to Safety With US Financial Firm Bankruptcy Announcements

ABSTRACTThis paper investigates whether bankruptcy announcements by large US financial institutions can induce flights to safety, leading investors to seek safer investments. To test this relationship, we employ a short‐horizon event study methodology and show that low‐risk investments—such as the US dollar, sovereign bonds and gold—exhibit significant appreciation following such announcements. This result is more pronounced when the local country‐level investor sentiment declines in the postannouncement period. We also analyze the transmission mechanism through which bankruptcy announcements cause flights to safety and empirically identify a global information contagion channel via negative shocks to the cash flows of stocks.

Estimating the impact of supply chain network contagion on financial stability

Realistic credit risk assessment, the estimation of losses due to a debtors failure, is central for maintaining financial stability. Credit risk models focus on the financial conditions of borrowers and only marginally consider other risks from the real economy, supply chains in particular. Recent pandemics, geopolitical instabilities, and natural disasters demonstrated that supply chain shocks can contribute to financial losses large enough to threaten financial stability. Based on a unique nation-wide micro-dataset, containing practically all supply chain relations of all Hungarian firms, together with their bank loans, we develop a multi-layer shock propagation framework to estimate how economic shocks to firms cascade in the supply chain network (SCN), leading to additional financial losses to firms, additional defaults of loans and, hence, losses to banks’ equity buffers. First, we estimate the financial systemic risk of individual firms, by quantifying the expected financial losses caused by a firm’s own- and all the secondary defaulting loans caused by supply chain network contagion. We find a small fraction of firms carrying substantial financial systemic risk, affecting up to 22% of the banking system’s overall equity (assuming a loss given default of 100%). These losses are predominantly caused by SCN-contagion. Second, we calculate for every bank the expected loss (EL), value at risk (VaR) and expected shortfall (ES), with and without SCN-contagion. We find that SCN-contagion amplifies EL, VaR, and ES by a factor of 5.2, 6.7 and 4.4, respectively. Third, we showcase how the new framework can be used to assess the risks of a large real economy shock for financial stability. We simulate the financial losses from a COVID-19 inspired shock calibrated from firm-level employment data in the beginning of 2020. Our simulations show that without any interventions, system-wide bank equity would suffer losses of 6%. The framework can be used to design and test targeted policy interventions, e.g., optimally providing firms with enough liquidity-support to avert their default. By supporting selected illiquid (yet solvent) firms with additional liquidity totalling 0.5% of overall bank equity, the losses can be reduced from 6% to 1% of overall bank equity. These findings indicate that for a more complete picture of financial stability and realistic credit risk assessment, SCN contagion needs to be considered. This now quantifiable contagion channel is of relevance for future systemic risk assessments of regulators.

Structured factor copulas for modeling the systemic risk of European and United States banks

In this paper, we employ Credit Default Swaps (CDS) to model the joint and conditional distress probabilities of banks in Europe and the U.S. using factor copulas. We propose multi-factor, structured factor, and factor-vine models where the banks in the sample are clustered according to their geographic location. We find that within each region, the co-dependence between banks is best described using both, systematic and idiosyncratic, financial contagion channels. However, if we consider the banking system as a whole, then the systematic contagion channel prevails, meaning that the distress probabilities are driven by a latent global factor and region-specific factors. In all cases, the co-dependence structure of bank CDS spreads is highly correlated in the tail. The out-of-sample forecasts of several measures of systemic risk allow us to identify the periods of distress in the banking sector over the recent years including the COVID-19 pandemic, the interest rate hikes in 2022, and the banking crisis in 2023.

ETFs and tail dependence: Evidence from Chinese stock market

Using Chinese A-share market data, we empirically examine the impact of exchange-traded funds (ETFs) on tail dependence of the underlying securities. Our results show that ETFs can increase the tail dependence of stocks in their basket, showing that the average tail dependence of a stock is higher when it has stronger ETF holding similarity with other stocks. We investigate the role of arbitrage activity and find that ETF holding similarity increases stocks’ ETF arbitrage activity. This effect is primarily on discount arbitrage rather than premium arbitrage, which leads to higher tail dependence among stocks. Alongside propagating demand shocks from the ETF market to underlying securities, ETFs also propagate tail event shock from one stock to other stocks in their baskets. Additionally, arbitrage activities through ETFs add a new layer of non-fundamental tail dependence to the underlying securities. Unlike mutual funds, ETFs lead to more frequent and idiosyncratic tail risk contagion among underlying securities. Our study sheds light on how ETFs provide new channels for risk contagion among underlying securities in emerging markets.

Burial objects” or “Birds of a feather”: The contagion effect of financial violations in business groups——The evidence from China

This study explores the conagion effect of financial violations within Chinese business groups from 2012 to 2021. Findings reveal that violations lead to stock price declines in member companies, with contagion primarily driven by irrational investor sentiment (“burial objects”) over the short term. The financial and governance characteristics of infected companies deteriorate (“birds of a feather”), but do not impact their long-term stock returns. Mitigating investor irrationality in infected companies helps curb contagion. This research contributes to business group governance and risk contagion theories, revealing a unique irrational contagion channel of financial violations within business groups in emerging markets.

Interbank systemic risk network in an emerging economy

PurposeInterconnections among banks are an essential feature of the banking system as it helps in an effective payment system and liquidity management. However, it can be a nightmare during a crisis when these interconnections can act as contagion channels. Therefore, it becomes essentially important to identify good links (non-contagious channels) and bad links (contagious channels).Design/methodology/approachThe article estimated systemic risk using quantile regression through the ΔCoVaR approach. The interconnected phenomenon among banks has been analyzed through Granger causality, and the systemic network properties are evaluated. The authors have developed a fixed effect panel regression model to predict interconnectedness. Profitability-adjusted systemic index is framed to identify good (non-contagious) or bad (contagious) channels. The authors further developed a logit model to find the probability of a link being non-contagious. The study sample includes 36 listed Indian banks for the period 2012 to 2018.FindingsThe study indicated interconnections increased drastically during the Indian non-performing asset crisis. The study highlighted that contagion channels are higher than non-contagious channels for the studied periods. Interbank bad distance dominates good distance, highlighting the systemic importance of banking network. It is also found that network characteristics can act as an indicator of a crisis.Originality/valueThe study is the first to differentiate the systemic contagious and non-contagious channels in the interbank network. The uniqueness also lies in developing the normalized systemic index, where systemic risk is adjusted to profitability.

Financial Crises and Their Impacts on Global Economies: Lessons from the 2008 Financial Crisis

A reassessment of financial institutions, regulatory frameworks, and macroeconomic policies all over the world was prompted by the global financial crisis that occurred in 2008. This crisis is considered to be a watershed point in the history of the economy. in order to provide light on the effects that the financial crisis of 2008 had on economies throughout the world and the steps that were taken to alleviate those effects, the causes, repercussions, and lessons gained from the crisis are discussed. The paper examines the dynamics of financial crises, the transmission channels of crisis contagion, and the responses of policymakers, central banks, and international organisations to restore financial stability and stimulate economic recovery. The paper draws on economic theory, empirical evidence, and policy analysis to conduct its analysis. In addition, the paper investigates the long-term implications of the financial crisis that occurred in 2008 for financial regulation, monetary policy, fiscal policy, and international cooperation. It emphasises the significance of gaining knowledge from previous crises in order to construct financial systems that are more resilient and sustainable in the future.

Contagious greenwashing investment

PurposeThis study explores the contagion of greenwashing strategies among ESG mutual funds. It investigates how the greenwashing behaviors of peer funds within the same family influence a fund’s decision to engage in greenwashing. The research also examines the impact of greenwashing on genuine ESG funds and explores the mechanisms through which greenwashing strategies spread across ESG mutual funds.Design/methodology/approachThis paper employs a two-stage least squares regression model with cross-fund returns standard deviation as an instrumental variable to disentangle the peer effects of greenwashing from family-level characteristics. The analysis incorporates various fund characteristics and introduces four contagion channels through which greenwashing may influence genuine ESG funds.FindingsThe study finds greenwashing behavior in ESG funds is positively influenced by similar practices within their fund family. Larger assets under management and older funds with higher management fees show resilience against greenwashing influences, while team-managed funds are more susceptible. Additionally, socially responsible investors struggle to distinguish between genuine and greenwashing ESG funds, which may contribute to the persistence of greenwashing practices.Originality/valueThis paper contributes to the literature by delineating the mechanisms of greenwashing contagion within ESG mutual funds. It also examines the demand-side incentives for adopting greenwashing strategies, offering insights into the implications for fund flows and investor behavior. This study is among the first to analyze the contagion effects of greenwashing strategies across an extensive network of ESG funds, enriching our understanding of the broader impacts of greenwashing in the context of socially responsible investing.

Can investor sentiment connectedness predict banking systemic risk: evidence from China

ABSTRACT Investor sentiment connectedness (TCI), which depicts the aggregate effect of investor sentiment contagion, is documented as a potential risk contagion channel and plays an essential role in the evolution of systemic risk. This study applies the TVP-VAR model to construct TCI and examines whether TCI can predict banking systemic risk. Empirical results show that an increase in TCI strongly and stably predicts increasing banking systemic risk over the next month. Additionally, both in-sample and out-of-sample results indicate that TCI provides incremental information for banking systemic risk prediction.

Structural changes in contagion channels: the impact of COVID-19 on the Italian electricity market

AbstractOperating on electricity markets requires accurately identifying, quantifying, and measuring risk coupled with their corresponding return: this appears as a crucial point, particularly during and after the COVID-19 pandemic. The aim of the present paper is twofold. First, we propose a novel econometric approach to identifying relevant market factors that capture several elements of the risk transmission mechanism inherent in energy systems. The proposed model extends Bayesian graphical models with change points to a multiple-layer set-up. Multilayer graphs encompass the two relevant channels of shock transmission: volatility and price contagion effects. The choice of these two layers seems natural because electricity prices and their spiky nature, coupled with inherent volatility, constitute essential influential elements for market players to maximize their profits. The change-point specification allows for detecting relevant changes in the electricity market. Second, we apply the proposed econometric framework to the Italian zonal markets analyzing the effects of returns and volatility contagion in several periods detected by the model. The last time intervals identified by the change-point methodology overlap the COVID-19 pandemic period. The model captures relevant abrupt changes in prices and volatility in the zonal electricity market and provides new evidence of interconnections in the zones of the Italian market related to the risk alone, price process alone, and risk versus price process relationship and their interactions.

Research on systemic risk of China's bank-asset bipartite network

Systemic risk caused by banks due to common asset holdings serve as a significant contagion channel. In this study, we use empirical data from Chinese banks to construct a bank-asset bipartite network, employ the DebtRank algorithm for risk measurement, and incorporate asset price correlation into the DebtRank algorithm. Then we show the changes of the systemic risk in the Chinese banking system from 2018 to 2021. Furthermore, we analyze the systemic risk triggered by different types of banks and different industry assets and quantify the impact of each asset under different stress scenarios. We also conduct a validity analysis of asset price correlation, finding that the systemic risk considering asset price correlation is higher than that without considering asset price correlation. This study of financial systemic risk under the bank-asset bipartite network provides a new perspective for the regulation of systemic risk and is of significant importance for the prevention of systemic risk.

Financial risk contagion based on dynamic multi-layer network between banks and firms

Banks and firms play pivotal roles within the financial system and serve as primary channels for systemic risk contagion. While progress has been made in understanding risk contagion within financial network systems, many studies tend to overlook the intricate interplay of multi-channel risk transmission and the dynamic evolution of network structures. Leveraging complex network theory, we have developed a dynamic multi-layer financial network risk transmission model that encompasses traditional bank–firm lending relationships and incorporates dynamic short-term loans. Through our analysis of various parameters such as loan recovery ratios, cross-shareholding ratios, network structures, short-term loan ratios, and attack strategies, we have made significant observations: In scenarios where both the interbank lending network and cross-shareholding network among firms exhibit random network structure, the financial network presents the highest level of risk. Excessive deviations in network average degrees, either too high or too low, can also heighten network vulnerability. An increase in the recovery ratio of interbank loans and the cross-shareholding ratio among firms corresponds to an escalation in systemic risk. Nodes with higher lending assets, more liquid assets, greater total assets, or higher out-degrees within the network become significant contributors to an elevated network bankruptcy rate when subjected to targeted attacks. Notably, the dynamic short-term loan network significantly amplifies systemic risks, with this amplification effect intensifying as the scale of short-term loans increases. From both macro and micro perspectives, our findings furnish regulatory authorities with novel analytical tools and insights to effectively mitigate and manage systemic risks in the financial sector.

Распространение финансового заражения в странах Европы под воздействием глобальных шоков

This article examines the impact of global shocks of various nature on the development of the European economy within the framework of the theory and methodology of financial contagion. The content of the concept of “financial contagion” is revealed. The variety of methods of its detection is considered. It is shown that the methodology of financial contagion is useful in the study of financial crises. Based on data on local crises, the crisis burden indicator for the European region is calculated for the period from 1960 to 2019. In Europe, compared with other regions, this indicator takes on the lowest values, so the European economy is more resilient to crises. At the same time, the analysis of some empirical studies shows numerous episodes of financial contagion in the European zone. The results of original investigation which is based on large scale array of empirical data on stock indices and international trade are presented in the article. An advanced dynamic financial contagion test is used for analysis in this study. For situations caused by four global shocks contagion estimates are calculated which show different susceptibility levels of European countries to these shocks. On the other hand, the results of the analysis suggest that the COVID‑19 pandemic has the strongest impact on European countries because the calculated values of test statistics more often and significantly exceed the threshold level during this period (compared with other shocks such as the global financial crisis, BREXIT and the energy crisis). The main channel of contagion is the stock market, not trading. In addition, it can be noted that large European economies are not immune to financial contagion. They are as much its recipients as the weaker countries of the region. At the same time, they play the role of a damper, i. e. they do not transmit financial contagion within the European zone. Finally, the study identifies some directions of financial contagion counteractions in European countries that are linked to its transmission channels. Examples of the transformation of European economic policy caused by the impact of global shocks, contagion effects and stressful situations are given.

Research on the 2008 Financial Crisis Regarding Financial Network

The rapid withdrawal in the financial market due to the collapse of Silicon Valley Banks in 2023 brought reflections on the 2008 financial crisis. Past research has focused on modeling different types of financial networks that help explain bankruptcys contagion process. This paper discusses how these networks help to explain the 2008 financial crisis, followed by shedding light on the global impacts (European, Latin American, and Asian markets) of the crisis in terms of networks. The last section further discusses potential policies that could be used to prevent or predict severe contagion depending on different network structures, including adjusting the level of portfolio diversification for international investment, for example. This paper sheds light on the importance of financial networks regarding their contagion channel and wide application in the real economy.

Frontier markets sovereign risk: New evidence from spatial econometric models

This paper considers spatial linkages of bilateral trade, financial correlation, and bilateral distance to study the macroeconomic determinants of sovereign risk for frontier markets. It applies (Shi and Lee, 2017) dynamic spatial Durbin model with interactive fixed effects. Analysis confirms the existence of spillover effects stemming from the explanatory variables’ movement towards the Credit default swaps (CDSs) premium of itself and neighboring countries. Bilateral distance and trade are the most significant spatial linkages. All macroeconomics except reserves impact CDS spreads directly and through feedback effects. Spatial dependence strengthens during recessions. Findings suggest policymakers should account for regional contagion channels that transmit sovereign risk.

Systemic Risk Spillover Effects among China’s Financial Institutions: Evidence from the Spatial Econometric Model

This study investigates the spillover and contagion effects of systemic risk among Chinese financial institutions in terms of the conditional Value-at-Risk method and spatial econometric techniques. We construct different representative spatial weight matrices to demonstrate various risk connective categories and contagion channels. The spatial autoregression model is built to reveal the different magnitudes of systemic risk contagion effects and extended as the spatial quantile regression model to measure the change in spillovers across quantiles. The results highlight that the spatial agglomeration pattern of institution-level systemic risk is highly concentrated within the same sector but highly disparate between the different sectors. The closeness of the asset price channel and the information channel would enhance the systemic risk spillover effects among institutions. The higher the single institution’s systemic risk level is, the stronger its spillovers among all of them within the same financial department, yet contrarily, the spillovers are larger at lower quantiles between different sectors due to the disparate spatial tendency of systemic risk. Besides, the spillover effects across quantiles indicate the higher tail contagion of systemic risk spatial spillovers, especially during 2015 A-share market crash and 2020 COVID-19 outbreak.

Transmission Mechanism of U.S. Monetary Policy to Economies

Due to the special status of the United States and the U.S. dollar in the world economy, the U.S. monetary policy has a significant spillover effect on the world. Especially since the subprime mortgage crisis in 2007, the U.S. monetary policy has attracted more attention from the world. Combined with the previous literature, this paper finds that the transmission channels of the US monetary policy uncertainty spillover effect include exchange rate expectation channel, financial asset allocation channel, contagion of monetary policy uncertainty, and real option effect. Among them, the channel of exchange rate expectations, the channel of financial asset allocation and the channel of contagion of monetary policy uncertainty are responsive and rapid, while the real option effect has a slow and long-term impact on the real economy. At the same time, there are differences in the spillover effects of U.S. monetary policy uncertainty on different countries. The results of this study have certain guiding significance for monetary policy formulation in other countries, such as strengthening the supervision of cross-border bonds and cross-border investment. Especially under the impact of the new crown pneumonia epidemic, major developed economies have implemented a new round of quantitative easing monetary policies, and policymakers in emerging economies need to pay great attention to this.

Effects of mergers on network models of the financial system

Despite the ongoing consolidation trend in the banking industry and the attention some mergers (in particular between large banks) have been receiving, there is no consistent picture of the impact of mergers on the stability of the financial system. In this paper, we aim to provide a universal framework to study the generic effect of mergers and acquisitions on the resilience of financial systems based on different network models. We investigate the impact of a wide variety of model assumptions, e.g. connectivity, contagion channel and the merger process, on different static and dynamic stability measures. We provide a range of theoretical results highlighting the mechanisms that influence systemic risk in consolidated financial systems. Our main finding is that merger activities can stabilize or destabilize the modeled financial network, depending on various details such as the connectivity of the network and the assumed merger process. Merger activities can increase diversification of single banks and support their resilience to shocks, and may slow down contagious default. However, merger activities can also decrease stability if, for example, the network is driven into the contagion window or insufficiently stable banks emerge in key positions in the network.

Systemic risk in European banks: Does ownership structure matter?

We empirically test whether ownership concentration explains the cross-variation in systemic risk contribution for a sample of European banks over the 2004–2021 period and how this effect may vary depending on the category of the largest controlling shareholder. We explore two potential contagion channels: the risk-taking incentives and banks’ assets commonality. The results show that higher ownership concentration is associated with greater banks’ systemic risk contribution. Moreover, we find that banks’ systemic risk contribution is even stronger for banks where institutional investors or States are the largest controlling owners. Overall, our findings contribute to the literature examining the determinants of banks’ systemic risk in particular and financial stability as a whole and have several policy implications.

Contagion and loss redistribution in crypto asset markets

This paper addresses the growing concern of shock propagation in crypto asset markets. The integration of conventional financial institutions (CeFi) and decentralized financial protocols (DeFi) has introduced a set of complexities that are not adequately accounted for in current models. We build on the well-established framework by Eisenberg and Noe (2001) and propose a generalized extension that can be applied to mixed DeFi/CeFi networks. Our model serves as a tool for comprehending potential contagion channels and loss redistribution resulting from the non-recourse nature of DeFi loans.