Overlapping portfolios,contagion, and financial stability

We study the problem of interacting channels of contagion in financial networks. The first channel of contagion is counterparty failure risk; this is captured empirically using data for the Austrian interbank network. The second channel of contagion is overlapping portfolio exposures; this is studied using a stylized model. We perform stress tests according to different protocols. For the parameters we study neither channel of contagion results in large effects on its own. In contrast, when both channels are active at once, bankruptcies are much more common and have large systemic effects.     

Did Vietnam stock market avoid the “contagion risk” from China and the U.S.? The contagion effect test with dynamic correlation coefficients

This paper examines the Vietnamese stock market with an extension of the recent investigation of risk contagion effects. Daily data spanning October 9, 2006–June 19, 2009 are sourced for the empirical validation of the risk contagion between the stock markets in Vietnam, China, and the U.S. To facilitate the validation of contagion effects with market related coefficients, this paper constructs a bivariable EGARCH model of dynamic condition correlation coefficients. First, we examine whether there are contagion effects when there is a financial crisis in the Vietnamese stock market. Next, we verify whether the contagion risk triggered by the crisis can affect the Vietnamese market and examine which market influences the Vietnamese market the most. We find that compared to the U.S. stock market, the Chinese stock market brings more contagion risk to the Vietnamese market, and these effects gain more significance after the sub-prime mortgage crisis.     

Financial contagion in inter-bank networks with overlapping portfolios

Journal of Economic Interaction and Coordination - By considering overlapping portfolios among financial institutions, we construct a financial contagion model for inter-bank networks with two...     

Contagion of network products in small-world networks

We formulate a model in which agents embedded in an exogenous social network decide whether to adopt a new network product or not. In the theoretical part of the paper, we characterize the stochastically stable equilibria for complete networks and cycles. For an arbitrary network structure, we develop a novel graph decomposition method to characterize the set of recurrent communication states, which is a superset of stochastically stable equilibria of the adoption game presented in our model. In the simulation part, we study the contagion process of a network product in small-world networks that systematically represent social networks. We simulate a generalization of the Morris (Rev Econ Stud 67(1):57–78, 2000) Contagion model that can explain the chasm between early adopters and early majority. Our numerical analysis shows that the failure of a new network product is less likely in a highly cliquish network. In addition, the contagion process reaches to steady state faster in random networks than in highly cliquish networks. It turns out that marketers should work with mixed marketing strategies, which will result in a full contagion of a network product and faster contagion rates with a higher probability.

     

Does diversification promote systemic risk?

We measure systemic risk when faced with simulated shocks through the systemic model of banking originated losses. The formation mechanism of systemic risk is explored from the perspective of investment diversification and asset similarity. The results indicate that contagion risks formed by the over similarity of investment assets are the main cause of systemic risk. The similarity generally promotes contagion risks, however, it shows a double-faced effect for state-owned commercial banks that disperse shocks from counterparties through their too-big-to-fail advantages. The similarity is determined by diversification, which initially promotes similarity and disperses it after a threshold. The diversification acts on the contagion process of systemic risk by the mediation of the similarity. Therefore, diversification generally has a nonlinear impact on systemic risk. The results provide regulatory implications for the systemic stability of the banking system.     

Contagion risk in the Czech financial system: A network analysis and simulation approach

This paper examines the potential for contagion within the Czech banking system via the channel of interbank exposures of domestic banks, enriched by a liquidity channel and an asset price channel, over the period March 2007 to June 2012. A computational model is used to assess the resilience of the Czech banking system to interbank contagion, taking into account the size and structure of interbank exposures as well as balance sheet and regulatory characteristics of individual banks in the network. The simulation results suggest that the potential for contagion due to credit losses on interbank exposures was rather limited. Even after the introduction of a liquidity condition into the simulations, the average contagion was below 3.8% of the remaining banking sector assets, with the exception of the period from December 2007 to September 2008. Activation of the asset price channel further increases the losses due to interbank contagion, showing that the liquidity of government bonds would be essential for the stability of Czech banks in stress situations. Finally, the simulation results for both idiosyncratic and multiple bank failure shocks suggest that the potential for contagion in the Czech banking system has decreased since the onset of the global financial crisis.     

Multiscale financial risk contagion between international stock markets: Evidence from EMD-Copula-CoVaR analysis

Considering the frequency domain and nonlinear characteristics of financial risks, we measure the multiscale financial risk contagion by constructing EMD-Copula-CoVaR models. Using a sample composed of nine international stock markets from January 4, 1999, to May 13, 2021, the empirical study reveals that: (1) EMD-Copula-CoVaR models can effectively measure the multiscale financial risk contagion, and the financial risk contagion is significant at all time scales; (2) The high-frequency component is the major contributor of financial risk contagion; meanwhile, the low-frequency component is the smallest among all time scale components; (3) The risk export of the US financial market to other markets, except the UK under the original and medium-frequency component, is higher than that it receives; and (4) Even though the magnitude of overall financial risk contagion is similar for the COVID-19 pandemic, Subprime Crises, 9/11 terrorist attack and other crises, the relative importance of different frequency components is heterogeneous. Therefore, the countermeasures of risk contagion should be designed according to its multiscale characteristics.     

Relative risk aversion and the transmission of financial crises

We study how investor behavior affects the transmission of financial crises. If investors exhibit decreasing relative risk aversion, then negative wealth shocks increase the risk premium required to hold risky assets. We integrate this into a second generation model of currency crises which allows for contagion through changes in fundamentals. Investor behavior can be a transmission channel of financial crises, as changes in risk premia increase the coverage ratio and makes the defense of a peg less attractive for the policy maker. The feedback effect of the risk premia on the probability of devaluation also makes multiple equilibria more likely. The possible stabilization effects of capital controls and a Tobin tax on the international transmission of financial crises are also studied.     

An empirical study of the Mexican banking system’s network and its implications for systemic risk

With the aim to measure and monitor systemic risk, we present some topological metrics for the interbank exposures and the payments system networks. The evolution of such networks is analyzed, we draw important conclusions from the systemic risk's perspective and propose a measure of interconnectedness. Additionally, we suggest non-topological measures to describe individual behavior of banks in both networks. The main findings of this paper are: the structures of the payments and exposures networks are different (in terms of connectivity); the topology of the exposures network changed after the collapse of Lehman Brothers, whereas the structure of the payments network does not; the proposed measure of interconnectedness can be used to determine the importance of a bank in terms of connectivity. Finally, we found that interconnectedness of a bank is not necessarily related with its assets size but it is linked to the contagion it might cause.     

Correlated risks vs contagion in stochastic transition models

This paper studies the problem of disentangling risk correlation and contagion in a set of individual binary processes. The two admissible values correspond to bad and good risk states of an individual. The risk correlation is captured by introducing a dynamic frailty, whereas the contagion passes through the effect of the lagged number of individuals in the bad risk state. We study carefully the dynamic properties of the joint process. Then, we focus on the limiting case of large populations (portfolios). The difficulty to identify risk correlation and contagion in finite samples is illustrated by means of Monte-Carlo simulations.     

Interest rate risk propagation: Evidence from the credit crunch

During the 2007–2009 financial crisis, US subprime mortgage risk exposures led to severe liquidity problems in several other foreign markets. Such risk contagion was caused by enormous changes in interest rates. Although risk contagion has been investigated by several literatures, the magnitude of propagated interest rate risk around global financial markets remains unexplored. Therefore, this study quantifies the degree to which the increased credit risk within the US financial system propagated to the European markets’ liquidity risks. Specifically, using a conditional value-at-risk (CoVaR) model, we quantitatively measure interest rate risk of a European country, by looking at the upside risk in distribution of changes in interest rate. And such propagation risk measure considers additional value-at-risk conditional on the interest rate movements in the US. The results show significantly positive differences between European country's value-at-risk conditional on the US financial markets being in a normal or distressed state. This propagating effect increased from 2007, and was particularly pronounced in the 2008–2009. In addition, the interest rate risk contagion is especially severe for some countries in the Euro regions with greater sovereign debt problems. Hence our result foretells the deterioration of the European sovereign debt crisis which started to unfold in 2010. Our work supplements the literature by successfully quantifying the magnitude of additional interest rate risk conditional on risk exposure from external sectors.     

Systemic liquidity contagion in the European interbank market

Systemic liquidity risk, defined by the International Monetary Fund as “the risk of simultaneous liquidity difficulties at multiple financial institutions,” is a key topic in financial stability studies and macroprudential policy-making. In this context, the complex web of interconnections of the interbank market plays the crucial role of allowing funding liquidity shortages to propagate between financial institutions. Here, we introduce a simple yet effective model of the interbank market in which liquidity shortages propagate through an epidemic-like contagion mechanism on the network of interbank loans. The model is defined by using aggregate balance sheet information of European banks, and it exploits country and bank-specific risk features to account for the heterogeneity of financial institutions. Moreover, in order to obtain the European-wide topology of the interbank network, we define a block reconstruction method based on the exchange flows between the various countries. We show that the proposed contagion model is able to estimate systemic liquidity risk across different years and countries. Results suggest that our effective contagion approach can be successfully used as a viable alternative to more realistic but complicated models, which not only require more specific balance sheet variables with high time resolution but also need assumptions on how banks respond to liquidity shocks.

     

Analysis of the cross-region risk contagion effect in stock market based on volatility spillover networks: Evidence from China

This article uses the stock market regional indexes of 31 provinces (include Province-level municipalities and Minority Autonomous Regions) in mainland China as a sample, and constructs an inter-regional volatility spillover network of China’s stock market based on the GARCH-BEKK model. Through network centrality analysis, Diebold and Yilmaz's spillover index method and block model analysis, we comprehensively analyze the risk contagion effect among different regions in China’s stock market. The empirical results show that: (i) The risk contagion intensity (risk reception intensity) in various regions of China’s stock market has a typical “core-periphery” distribution characteristic due to regions’ different levels of economic development. (ii) There are obvious risk spillover effect in China’s stock market, among which the economically developed regions along the southeastern coast of China, such as Beijing, Shanghai, Zhejiang and Jiangsu, are the main risk transmitters, while the economically undeveloped regions in the Midwest of China, such as Xinjiang, Xizang, Gansu, Nei Menggu and Qinghai are the main risk receivers. (iii) Each region is divided into 4 blocks according to their respective roles in the risk spillover process in China’s stock market. Block 1 that is composed of the economically underdeveloped regions in the Midwest is the “main benefit block”, it acts as a “receiver”. Block 2 that is composed of regions with strong economic growth vitality in the Midwest is a “Bilateral spillover block”, it both plays the role of “receiver” and “transmitter”. Block 3 that is composed of developed regions along the southeast coast, it acts as a “transmitter”; Block 4 that is composed of the relatively fast-growing regions in the Southwest is the “brokers block”, it serves as a “bridge”. The results of this article can provide some reference for investors in financial institutions and decision makers in financial regulators.     

Topological properties of reconstructed credit networks and banking systemic risk

Financial bipartite networks provide channels for contagion risks and their topological properties determine financial stability. We enrich the bipartite network reconstruction methods proposed by Ramadiah et al. (2020) and extend them to the Chinese banking system. By comparing the reproducibility of the real credit market and the corresponding systemic risk, the impact of topological properties for different reconstructed bipartite networks on financial stability is analyzed. The empirical evidence shows that network reconstruction methods based on maximum entropy ensembles capture more properties in the real credit network. It also highlights that the different systemic risk level is mainly contributed by the topological properties based on common exposures. These analyses for topological properties provide regulatory insights for systemic risk prevention. It shows that reducing credit similarity across banks while increasing credit diversification in different sectors helps to control systemic risk. The results imply the possibility of increasing financial stability through the macro-regulation of the credit market structure.     

中国影子银行部门系统性风险的形成、影响与应对

本文分析了影子银行风险传染机制及其影响,在违约风险基于会计账户传染的马尔科夫过程假设下,运用投入产出法构建影子银行系统性风险测度模型,以2007-2012年中国影子银行业务数据进行检验,结果显示：信托公司部门是主要的风险源,银行部门是系统性风险最主要的承担者,观测期内影子银行部门系统性风险整体呈现上升趋势。防控系统性风险应从影子银行业务风险隔离机制、资本与杠杆率监管、信息透明度、宏观审慎框架和风险应急机制等建设着手。     

Stock market linkages and financial contagion: A cobreaking analysis

Financial crises have shown that dramatic movements in one financial market can have a powerful impact on other markets. This paper proposes to use cobreaking to model comovements between stock markets during crises and to test for contagion. We find evidence of cobreaking between developed stock markets. In emerging stock markets, the evidence of cobreaking is mainly due to the non-financial event of the World Trade Center terrorist attacks in 2001. We find evidence of short-term linkages during times of crisis but not contagion. These short-term linkages have important implications for investors, risk managers and regulators.     

审计失败对公司债券发行定价的传染效应——基于共同审计师的视角

审计失败会对客户公司产生负面影响,并且可能波及拥有共同审计师的公司。基于共同审计师视角,选取2007—2022年公司债数据,实证检验审计失败在债券发行定价中的传染效应。研究发现,当发生审计失败后,拥有共同审计师的关联公司债券发行定价显著提高,即审计失败对债券发行定价具有传染效应,经过多种稳健性检验后结论依旧成立。机制检验表明,风险信息传递、低质量会计信息是审计失败产生传染效应的作用机制。进一步研究发现,当聘用学历较高或具有行业专长的审计师、投资者面临风险更小、投资者保护更好时,传染效应有所减弱。     

Network VAR models to measure financial contagion

Financial contagion among countries can arise from different channels, the most important of which are financial markets and bank lending. The paper aims to build an econometric network approach to understand the extent to which contagion spillovers (from one country to another) aris from financial markets, from bank lending, or from both. To achieve this aim we consider a model specification strategy which combines Vector Autoregressive models with network models. The paper contributes to the contagion literature with a model that can consider bank exposures and financial market prices, jointly and not only separately. From an empirical viewpoint, our results show that both bilateral exposures and market prices act as contagion channels in the transmission of shocks arising from a country to other countries.     

A survey of network-based analysis and systemic risk measurement

The financial crisis led to a number of new systemic risk measures and a renewed concern over the risk of contagion. This paper surveys the systemic risk literature with a focus on the importance of contributions made by those emphasizing a network-based approach, and how that compares with more commonly used approaches. Research on systemic risk has generally found that the risk of contagion through domino effects is minimal, and thus emphasized focusing on the resiliency of the financial system to broad macroeconomic shocks. Theoretical, methodological, and empirical work is critically examined to provide insight on how and why regulators have emphasized deregulation, diversification, size-based regulations, and portfolio-based coherent systemic risk measures. Furthermore, in the context of network analysis, this paper reviews and critically assesses newly created systemic risk measures. Network analysis and agent-based modeling approaches to understanding network formation offer promise in helping understand contagion, and also detecting fragile systems before they collapse. Theory and evidence discussed here implies that regulators and researchers need to gain an improved understanding of how topology, capital requirements, and liquidity interact.     

The contagion effect of jump risk across Asian stock markets during the Covid-19 pandemic

This paper tests the market jump contagion hypothesis in the context of the Covid-19 pandemic. We first use a nonparametric approach to identify jumps by decomposing the realized volatility into continuous and jump components, and we use the threshold autoregressive model to describe the jump interdependency structure between different markets. We empirically investigate the contagion effect across several major Asian equity markets (Mainland China, Hong Kong, Japan, South Korea, Singapore, Thailand, and Taiwan) using the 5-minute high frequency data. Some key findings emerge: jump behaviors occur frequently and make an important contribution to the total realized volatility; jump dynamics exhibit significant nonlinearity, asymmetry, and the feature of structural breaks, which can be effectively captured by the threshold autoregressive model; jump contagion effects are obviously detected and this effect varies depending on the regime.