@1007477689
2020-07-30T09:40:52.000000Z
字数 16481
阅读 404
复杂网络
Andreea Constantin, Tuomas A. Peltonen, Peter Sarlin
①Building on the literature on systemic risk and financial contagion, the paper introduces estimated network linkages into an early-warning model to predict bank distress among European banks. ②We use "multivariate extreme value theory" to estimate equity-based tail-dependence networks, whose links proxy for the markets' view of bank interconnectedness in case of elevated financial stress. ③The paper finds that early warning models, including estimated tail dependencies, consistently outperform bankspecific benchmark models without networks. ④The results are robust to variation in model specification and also hold in relation to simpler benchmarks of contagion. ⑤Generally, this paper gives direct support for measures of interconnectedness in early-warning models, and moves toward a unified representation of cyclical and cross-sectional dimensions of systemic risk.
Kartik Anand, Iman van Lelyveld, Ádám Banai, Soeren Friedrich, Rodney Garratt, Grzegorz Hałaj, Jose Fique, Ib Hansen, Serafín Martínez Jaramillo, Hwayun Lee, José Luis Molina-Borboa, Stefano Nobili, Sriram Rajan, Dilyara Salakhova, Thiago Christiano Silva, Laura Silvestri, Sergio Rubens Stancato de Souza
①Capturing financial network linkages and contagion in stress test models are important goals for banking supervisors and central banks responsible for micro- and macroprudential policy. ②However, granular data on financial networks is often lacking, and instead the networks must be reconstructed from partial data. ③In this paper, we conduct a horse race of network reconstruction methods using network data obtained from 25 different markets spanning 13 jurisdictions. ④Our contribution is two-fold: first, we collate and analyze data on a wide range of financial networks. ⑤And second, we rank the methods in terms of their ability to reconstruct the structures of links and exposures in networks.
①We simulate shocks to the real sector and evaluate how the financial system reacts and amplifies these events using unique Brazilian loan-level data between banks and banks and firms. ②Our analysis considers the feedback behavior that exists between the financial and real sectors through a micro-level financial accelerator. ③We find a strong “network effect” in which the network structure can either attenuate or amplify shocks from the real sector and thus plays a major role in contagion processes. ④We also find that government-owned banks are the most susceptible banks to receiving shocks from firms of any economic sector. ⑤There is empirical evidence to support the claim that more diversified portfolios of banks contribute to higher sector riskiness levels. ⑥Our results suggest that systemic risk models should account for the interconnectedness among economic agents—such as the interbank and real and financial sector linkages—in a multilayer approach. ⑦Overall, we show that the feedback between the real and financial sector matters in systemic risk estimation and most models that do not take into consideration could be severely underestimating systemic risk
Joao Barata Ribeiro Blanco Barroso, Thiago Christiano Silva, Sergio Rubens Stancato de Souza
①In this paper, we propose a methodology to decompose drivers of systemic risk that arise due to insolvency contagion in evolving financial networks. ②There is an ongoing discussion on how network topology and capital buffer influence systemic risk. ③On the one hand, the network contagion literature tends to emphasize the influence of the network topology. ④On the other hand, policy works tend to discuss restrictions over the capital buffers of financial institutions. ⑤Systemic risk is usually a complex function of both risk drivers and thus isolating the contributive effects of each risk driver to systemic risk is not a trivial task. Our decomposition methodology identifies and isolates these effects. ⑥We apply our methodology to the global banking network and find that the network topology effect explains most of the systemic risk measure's volatility. ⑦Additionally, we show that the capital buffer effect explains the persistent reduction in systemic risk buildup with effects concentrated around the global financial crisis. ⑧Our results confirm the importance of both risk drivers to measuring systemic risk.
Solange Maria Guerraa, Thiago Christiano Silvaa, Benjamin Miranda Tabakb,Rodrigo Andrés de Souza Penalozac, Rodrigo César de Castro Miranda
①In this paper we present systemic risk measures based on contingent claims approach and banking sector multivariate density. ②We also apply network measures to analyze bank common risk exposure. ③The proposed measures aim to capture credit risk stress and its potential to become systemic. ④These indicators capture not only individual bank vulnerability, but also the stress dependency structure between them. ⑤Furthermore, these measures can be quite useful for identifying systemically important banks. ⑥The empirical results show that these indicators capture with considerable fidelity the moments of increasing systemic risk in the Brazilian banking sector in recent years.
and Latin America banking network#
Miguel A. Rivera-Castro a, Andrea Ugolini, Juan Arismendi Zambrano
①In this study the tail systemic risk of the Brazilian banking system is examined, using the conditional quantile as the risk measure. ②Multivariate conditional dependence between Brazilian banks is modelled with a vine copula hierarchical structure. ③The results demonstrate that Brazilian financial systemic risk increased drastically during the global financial crisis period. ④Our empirical findings show that Bradesco and Itaú are the origin of the larger systemic shocks from the banking system to the financial system network, the real economy, and the region. ⑤The results have implications for the capital regulation of financial institutions and for risk managers' decisions.
①We compare two widely employed models that estimate systemic risk: Debt-Rank and Differential Debt-Rank. ②We show that not only network cyclicality but also the average vulnerability of banks are essential concepts that contribute to widening the gap in the systemic risk estimates of both approaches. ③We find that systemic risk estimates are the same whenever the network has no cycles. ④However, in case the network presents cyclicality, then we need to inspect the average vulnerability of banks to estimate the underestimation gap. ⑤We find that the gap is small regardless of the cyclicality of the network when its average vulnerability is large. ⑥In contrast, the observed gap follows a quadratic behavior when the average vulnerability is small or intermediate. ⑦We show results using an econometric exercise and draw guidelines both on artificial and real-world financial networks.
Thiago Christiano Silva, Sergio Rubens Stancato de Souza, Benjamin Miranda Tabak
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①In this paper, we provide a detailed analysis of the roles financial institutions play within the Brazilian interbank market using a network-based approach. ②We present a novel methodology to assess how compliant networks are to being perfect core-periphery structures. ③The approach is flexible, allowing for the identification of multiple cores in networks. ④We verify that the interbank network presents a high disassortative mixing pattern, suggesting preferential attachment of highly connected financial institutions to others with few connections. ⑤We use the clustering coefficient to assess the substitutability of financial institutions. ⑥We find that large banking institutions are counterparties that are easily substitutable in normal times. ⑦We uncover that the rich-club effect is strongly present in the community comprising the large banking institutions, as they normally form near-clique structures. ⑧Since they play the role of liquidity providers in the interbank market, this interconnectedness effectively endows the network with robustness, as participants that are with liquidity issues can easily substitute counterparties that are liquidity suppliers. ⑨This substitutability will likely vanish during periods of stress, increasing systemic risk and the likelihood of cascade failures.
Thiago Christiano Silva, Solange Maria Guerra, Michel Alexandre da Silva and Benjamin Miranda Tabak
①We develop a novel approach to understand how central bank policy rates affect individual firms and banks and how aspects of interconnectedness accentuate these effects in nontrivial ways. ②We also innovate by taking into account the effect of the balance-sheet composition of each and every firm and bank in the economy. Each individual firm or bank has different responses to policy rate changes, for balance-sheet composition and network relationships are firm- and bank-specific.
①Changes in policy rate impact bank capital on spot, which in turn affect how banks issue credit to firms. ②After a policy tightening, credit lending decreases and firm financial costs increase, potentially causing solvency problems. Banks incur losses in view of firm credit defaults and restrict even more credit to them, leading firms into further financial distress.
①We apply our model to Brazil, which provides an ideal setup for numerous reasons. ②First, bank credit in the country is an important funding option for firms. Second, there was a strong credit growth in Brazil after 2008, which makes banks more exposed to firms and the business cycle. Third, Brazil has a very thorough database that contains detailed information on all loans made by banks to firms and between banks themselves, which permits us to track how policy rates are transmitted throughout the economy in a very granular level.
①We find that the effects of interest rate changes on the losses of financial institutions and firms are relatively low, which allows us to conclude that the systemic risk in Brazil arising from changes in policy rate and propagated through the financial networking is low.
①We find that there are nonlinear and asymmetric effects that depend on the magnitude and direction of policy rate changes. ②The effects of interest rate changes are distinct in environments of expansion and recession. Yet, gradual interest rate variations seem preferable to major changes in order to preserve financial stability.
Thiago Christiano Silva, Sergio Rubens Stancato de Souza and Benjamin Miranda Tabak
①In this paper, we propose novel risk-related network measurements to identify the roles that financial institutions play as potential targets or sources of contagion. ②We derive theoretical properties and provide a clear systemic risk interpretation for the proposed measures. ③Devised upon the notion of communicability in networks, we introduce the impact susceptibility index, which indicates whether market participants are locally or remotely vulnerable. ④We show that this index can be used as a financial stability monitoring tool and apply it to analyze the Brazilian financial market. ⑤We find that non-banking institutions are potentially remote vulnerable in certain periods, while banking institutions are not susceptible to indirect impacts. ⑥To address the perspective of market participants as sources of contagion, we propose the impact diffusion influence index, which captures the potential influence of financial institutions on propagating impacts in the network. ⑦We unveil the presence of a portion of non-large banking institutions that is consistently more influential than large banks in potentially diffusing impacts throughout the network. ⑧Regarding financial system stability, regulators should identify the entities that play these two roles, as they can render the system more risky.
Sergio Rubens Stancato de Souza, Thiago Christiano Silva, Benjamin Miranda Tabak, Solange Maria Guerra
①In this paper, we propose a novel methodology to measure systemic risk in networks composed of financial institutions. ②Our procedure combines the impact effects obtained from stress measures that rely on feedback centrality properties with the default probabilities of institutions. ③We also present new heuristics for designing feasible and relevant stress-testing scenarios that can subside regulators in financial system surveillance tasks. ④We develop a methodology to extract banking communities and show that these communities have a relevant effect on systemic risk. ⑤We find that these communities are mostly composed of non-large banks, suggesting that regulators should also broaden their surveillance efforts to these banking communities other than to the usual SIFIs and large banks. ⑥Finally, our results provide insights and guidelines for policymakers.
蒋 海 张锦意
中国经济进入新常态之后，经济下行压力加大，有效防范系统性金融风险已成为当前经济发展中亟须面对的重大问题。基于此，本文利用中国上市银行 年 月 日至 年 月 日的股票交易数据， 采用分位数回归和 算法，构建了上市银行尾部风险网络，同时使用滚动时间窗口法，分析了网络的动态关联性和拓扑结构。在此基础上，实证检验了上市银行尾部风险网络的关联性对系统性风险的影响。结果表明，银行尾部风险网络关联性与系统性风险显著正相关。虽然个体银行的尾部风险溢出会降低自身的风险承担水平，但也显著增强了银行网络的关联性，从而提高了系统性风险的整体水平。同时我国上市银行尾部风险网络存在较明显的时变特征，在风险积聚过程和经济下行期间，其关联性显著增强。另外，大型国有银行在整个银行网络中居中心地位，具有较强的尾部风险溢出效应。
林 琳， 曹 勇
影子银行体系引发的系统性风险最易以资金链断裂的方式爆发，而资金链 断裂后一般以“挤兑”的形式爆发系统性风险。本文以 － 模型为基础，区别以往研究，首次建立了一个包含商业银行和影子银行两种异质节点的网络，以银行间同业业务和管道业务为研究对象，考察流动性充足与不足情况下，商业银行和影子银行网络系统性风险的传染过程。通过仿真实验，得到主要结论：在流动性充足情况下，影子银行增加了商业银行的系统性风险程度，影子银行通过商业银行同业业务缓释风险，商业银行同业关联规模越大，受风险传染的可能性越大；流动性不足使系统性风险程度增加，同时，影子银行的存在也增大了系统性风险程度，影子银行关联的规模越大，越容易将更多风险传染给商业银行。
郭晓冬 柯艳蓉 吴晓晖
本文以 ~ 年中国 股非金融行业的上市公司为研究样本，利用机构投资者共同重仓持股建立的联结构建机构投资者网络，从坏消息的释放过程考察机构投资者网络中心性对股价崩盘的影响。研究发现，网络中心性最强的机构投资者为了私利会利用机构投资者网络通过传递噪音或过滤坏消息等方式掩盖坏消息，使其网络中心性以及同其他机构投资者的网络中心性差异与股价崩盘风险正相关；而其他机构投资者为了获取更多收益、避免过晚交易直至股价崩盘带来的巨大损失，会利用机构投资者网络揭露坏消息进行及时交易，以致其整体的网络中心性与股价崩盘风险负相关。在控制了内生性等问题之后，以上结论依然成立。本文拓展和深化了股价崩盘风险影响因素的研究，对如何防范股价崩盘具有重要的实践意义。
朱丽 刘军 刘超 杨杜
本文运用资源依赖理论和"结构洞"理论，从结构性网络嵌入视角出发，运用 股上市公司 - 年董事会全网络，探讨异质性行业连接和企业创新绩效之间的关系。研究结果表明，异质性行业连接促进企业创新绩效的提升和企业网络权力的获得；企业网络权力在异质性行业连接和创新绩效之间具有中介作用；网络权力在异质性行业连接与企业创新绩效之间发挥中介效应的强弱，受到企业吸收能力水平的影响，即与低吸收能力相比，高吸收能力水平下，网络权力在异质性行业连接与企业创新绩效关系之间起的中介作用更强。本文丰富了相关领域的成果，解释了异质性行业连接对创新绩效影响的内在机制，为企业的创新实践提供了经验指导。
王浩宇 孙启明
文章基于复杂网络的理论方法，采用 年投入产出数据构建了京津冀三地及地区间产业复杂网络模型，从关联结构和强度两个维度识别了京津冀各地区及地区间关键产业，进而将关键产业划分为区域核心关键产业、局部关键产业和潜在关键产业，并且对各地区域关键产业分布情况进行分析比较。研究结果表明：北京的区域关键产业最多，其中现代服务业占近 成，美中不足的是科技研发和服务业未能有效带动其他地区的产业升级发展；天津的区域关键产业分布呈现能源、制造和服务业三足鼎立的局面，但其区域关键产业大多为局部关键产业，仅带动了本地区发展，其优势产业未能惠及整个地区；河北区域核心关键产业数量最多，在全区域经济关联中贡献最大，但产业结构比较单一，农业和服务业发展滞后，限制了其进一步发挥对区域发展的基础支撑作用。
Michael Ellington
①We examine the link between financial market illiquidity and macroeconomic dynamics by fitting a Bayesian time-varying parameter VAR with stochastic volatility to UK data from 1988Q1 to 2016Q4. ②We capture liquidity conditions in the stock market using a battery of illiquidity proxies. ③This paper departs from previous studies examining macro-financial linkages by using theoretically grounded sign restrictions, and conducting structural inference in a non-linear framework. ④We document both statistically significant differences in the transmission of these shocks, and substantial increases in the economic importance of these shocks during the 2008 recession.
Anne-Caroline Hüser, Grzegorz Hałaj, Christoffer Kok, Cristian Perales, Anton van der Kraaij
①One of the most important elements of the post-crisis financial reforms was to establish credible resolution frameworks allowing for creditor bail-in when banks are entering resolution. ②Despite the obvious benefits of shifting the burden of resolution from taxpayers to bank creditors, bank bail-ins may also give rise to costs as the financial consequences for bank shareholders and creditors being bailed in could endanger their own financial situation and potentially entail systemic implications. ③Using granular data on the securities cross-holdings among the largest euro area banking groups, we construct a multi-layered network model where each layer represents bail-inable securities of a specific seniority layer of the creditor hierarchy. ④The model can be a useful tool for resolution authorities to inform the policy discussion on both the composition and level of loss absorbing capacity of banks and the direct contagion risk following a bail-in. ⑤We find that due to low levels of securities cross-holdings in the interbank network there is no direct contagion in terms of creditor banks failing as a result of another bank being bailed in. ⑥At the same time, we document that a bail-in will have pecuniary consequences on the different liability holders and our framework allows for an exact quantification of those effects. ⑦In addition, we show that recapitalisations following a bail-in will change the network structure and hence the embedded contagion risk.
Fulvio Corsi, Fabrizio Lillo, Davide Pirino, Luca Trapin
①Using the test of Granger-causality in tail of Hong et al. (2009), we define and construct Granger-causality tail risk networks between 33 systemically important banks (G-SIBs) and 36 sovereign bonds worldwide. ②Our purpose is to exploit the structure of the Granger-causality tail risk networks to identify periods of distress in financial markets and possible channels of systemic risk propagation. ③Combining measures of connectedness of these networks with the ratings of the sovereign bonds, we propose a flight-toquality indicator to identify periods of turbulence in the market. ④Our measure clearly peaks at the onset of the European sovereign debt crisis, signaling the instability of the financial system. ⑤Finally, we use the connectedness measures of the networks to forecast the quality of sovereign bonds. ⑥We find that connectedness is a significant predictor of the cross-section of bond quality.