城市网络视角下金融中心性与区域技术创新

基于当前城市网络和金融地理研究,应用社会网络分析法构建城市金融中心性指标以衡量金融发展水平,并运用中国2005-2019年285个地级及以上城市面板数据对金融中心性和区域创新能力的关系进行实证研究.结果表明:金融中心性指数的增强显著提升城市创新能力,且这种促进作用呈现明显的"边际效应"递减的非线性特征;城市金融中心性的提高不仅能直接作用于区域创新能力,而且可以通过加快生产资本形成、促进产业结构升级以及加大外商投资力度产生积极影响;中、西部区域创新系统将从城市金融中心性提升中获益更多,金融危机前后城市金融中心性的提高对创新能力的影响明显不同,危机后的作用效果上升明显.     

Determinants of risk in the banking sector during the European Financial Crisis

Risk assessment in the banking sector has been a prominent topic in the banking literature and has gained attention especially since the recent financial crises. In particular, the European crisis, which was the first since the formation of the Eurozone, underlined a number of significant problems and increased concerns on the tail or crash risk of banks. In the present study, we seek to examine whether information asymmetry, the importance of banks in the financial system and systemic risk play significant roles in the evolution of stock crashes in the banking sector. Information asymmetry is proxied by opacity, the importance of a bank in a financial network is proxied by network centrality, and systemic risk is proxied by clustering. The research framework considers a number of regulatory, reporting and financial market factors that have also been determined to relate to stock crashes and shows that all of the above factors are related to (idiosyncratic) stock crash risk under specific conditions.     

Concentrated commonalities and systemic risk in China's banking system: A contagion network approach

China's banking system has seen increasing convergence in exposures to different asset types. These concentrated commonalities have far reaching implications on systemic financial risk. Based on the commonality structure of banks' balance sheets, we construct a bipartite financial network and design novel indicators to analyze the systemic risk of China's banking system and its relation to the real economy. Results show that (1) considering the interconnectivity, indirect loss arising from common exposure is much higher than direct loss; (2) concentrated common exposure to mortgage is demonstrated to be the most significant source of systemic vulnerability in China; (3) the derived contagion network shows the property of “small world”, which plays an important role in generating systemic risk, amplified non-linearly by multi-rounds of contagion; (4) a bank's systemic importance/vulnerability depends on complex interaction between asset volume, leverage rate, and its commonality of asset composition to other banks. The model proposed in this study provides a new structural perspective to investigate the systemic risk, and a macroprudential instrument to complement existing stress testing that contributes to more efficient and precise regulations. Moreover, we contribute a ranking framework to assess each bank's systemic importance as well as vulnerability corresponding to specific real sectors.     

A financial stability index for Colombia

The imbalances of the financial systems have showed the vast economic and social costs generated by financial instability. As a consequence, the development of stress indexes has spread as an alternative to assess the soundness of financial systems. The aim of this paper is to construct a continuous and quantifiable index with the capacity of establishing the stress level of the Colombian financial system as a function of profitability, liquidity and probability of default. Results show that the index determines effectively the stress level of the system. In addition, we performed forecasts of the financial stability index using macroeconomics variables.     

波动溢出网络视角的金融风险传染研究

当前各类经济风险交叉关联,金融系统的风险溢出效应备受关注,为刻画我国金融系统性风险传染的路径特征,本文从波动溢出网络的视角分析金融系统内部的风险传染机制。首先使用广义动态因子模型对收益波动的共同波动率成分和特质性波动率成分进行区分。然后,根据货币市场、资本市场、大宗商品交易市场、外汇市场、房地产市场和黄金市场之间的特质性波动溢出效应,利用基于TVP-VAR模型的方差分解溢出指数分析金融系统波动溢出的动态联动性和风险传递机制。在分析方向性波动溢出效应的基础上,采用方差分解网络方法构建起信息溢出复杂网络,从网络视角分析金融系统内部的风险传染特征。实证研究发现,房地产市场和外汇市场的净溢出效应绝对值相较于其他市场更大,其受其他市场风险冲击的影响强于对外风险溢出效应,而股票市场的单向对外风险溢出效应强度最大。在波动溢出的基础上,进一步考虑股市波动率指数与其他市场波动率指数进行投资组合的资产配置权重,计算了波动率指数投资组合的最优组合权重和对冲策略。研究结论有助于更好地理解我国金融系统的风险传染机制,对监管机构加强宏观审慎监管、投资者规避投资风险具有重要意义。     

Regulatory Capital Charges for Too‐Connected‐to‐Fail Institutions: A Practical Proposal

The recent financial crisis has highlighted once more that interconnectedness in the financial system is a major source of systemic risk. I suggest a practical way to levy regulatory capital charges based on the degree of interconnectedness among financial institutions. Namely, the charges are based on the institution's incremental contribution to systemic risk based on a risk budgeting approach. The imposition of such capital charges could go a long way towards internalizing the negative externalities associated with too‐connected‐to‐fail institutions and providing managerial incentives to strengthen an institution's solvency position, and avoid too much homogeneity and excessive reliance on the same counterparties in the financial industry.     

基于金融压力指数的金融系统性风险测度及影响因素

基于CRITIC赋权法构建中国金融压力指数,以此衡量中国金融系统性风险,并对其影响因素进行分析.研究结果显示:样本期间内,中国金融压力指数呈阶段性变化特征,其中2007-2010年是中国金融压力指数最大时期.国内生产总值指数对中国金融压力指数产生负影响,抑制中国金融压力指数上升;银行信贷余额、信贷膨胀率等其它变量对中国金融压力指数产生显著正影响,促使中国金融压力指数的上升.     

Assessing systemic risk using interbank exposures in the global banking system

This paper contributes to the literature on systemic risk by examining the network structure of bilateral exposures in the global banking system. The global interbank market constitutes a major part of the global banking system. The market has a hierarchical network structure, composed of the national or jurisdictional area's local markets and the cross-border interbank market. First, we estimate the bilateral exposures matrix using aggregate financial data on loans and deposits from Bankscope and analyze the interconnectedness in the market using network centrality measures. Subsequently, for the model analysis, we apply the Eisenberg–Noe framework to a multi-period setting. In this framework, bank defaults are classified into stand-alone defaults and contagious defaults. The banks in our sample (i.e., the top 202 banks with more than $50 billion in total assets) comprise a major part of this global banking system. The main findings are as follows: The theoretical network analysis using network centrality measures showed that most of the banks designated as global systemically important banks (G-SIBs) play a central role in the global interbank market. The theoretical default analysis showed a few contagious defaults triggered by the basic defaults during and after the global financial crisis. Our stress test proved that many G-SIBs theoretically caused 1–6 contagious defaults. Our methodology would assist in the development of a monitoring system by the respective supervisory authorities as well as in the implementation of bank-internal stress tests of default contagion.     

Systemic risk spillovers in the European banking and sovereign network

We propose a framework for estimating time-varying systemic risk contributions that is applicable to a high-dimensional and interconnected financial system. Tail risk dependencies and systemic risk contributions are estimated using a penalized two-stage fixed-effects quantile approach, which explicitly links time-varying interconnectedness to systemic risk contributions. For the purposes of surveillance and regulation of financial systems, network dependencies in extreme risks are more relevant than simple (mean) correlations. Thus, the framework provides a tool for supervisors, reflecting the market's view of tail dependences and systemic risk contributions. The model is applied to a system of 51 large European banks and 17 sovereigns during the period from 2006 through 2013, utilizing both equity and CDS prices. We provide new evidence on how banking sector fragmentation and sovereign-bank linkages evolved over the European sovereign debt crisis, and how they are reflected in estimated network statistics and systemic risk measures. Finally, our evidence provides an indication that the fragmentation of the European financial system has peaked.     

Risk spillovers between FinTech and traditional financial institutions: Evidence from the U.S.

In this paper, we propose a novel approach to examine the risk spillovers between FinTech firms and traditional financial institutions, during a time of fast technological advances. Based on the stock returns of U.S. financial and FinTech institutions, we estimate pairwise risk spillovers by using the Granger causality test across quantiles. We consider the whole distribution: the left tail (bearish case), the right tail (bullish case) and the center of the distribution and construct three types of spillover networks (downside-to-downside, upside-to-upside, and center-to-center) and obtain network-based spillover indicators. We find that linkages in the network are stronger in the bearish case when the risk of spillover is higher. FinTech institutions' risk spillover to financial institutions positively correlates with financial institutions' increase in systemic risk. These results have important policy implications, as they underscore the importance of enhancing the supervision and regulation of FinTech companies, to maintain financial stability.     

基于动态因子Copula模型的我国银行系统性风险度量

本文基于2007年至2019年我国14家上市银行的股票收益率,构建偏态t-分布动态因子Copula模型,利用时变荷载因子刻画单家银行与整个系统的相关性,计算联合风险概率作为系统性风险整体水平的度量,基于关联性视角提出了新的单家机构系统脆弱性和系统重要性度量指标——系统脆弱性程度和系统重要性程度。该方法充分考虑了银行个体差异性和系统的内在关联性以及收益率的厚尾性和非对称性,从而能够捕捉到更多的信息且兼具时效性。研究表明:银行机构在风险聚集时期相关程度更大,联合风险概率能够准确识别出系统性风险事件且在我国推行宏观审慎评估体系以后有明显降低;整体而言,大型商业银行系统重要性水平最高,同时风险抗压能力也最强;本文使用的度量方法降低了数据获取成本且更具时效性,有助于为宏观审慎差异化监管工作提供借鉴和参考。     

Belief Networks for Expert System Development in Auditing

This study examines the use of a belief network based expert system for an auditing task—financial distress evaluation for banks. A belief network uses probability measures to store important dependencies across variables of interest in a problem domain, and makes inferences based on observed evidence using probability calculus. This paper discusses how belief network structures can be constructed, and used to assist auditor's in making appropriate recommendations regarding the financial health of a bank under audit. The ability of a belief network to make reliable predictions depends on how well the network structure reflects the underlying dependencies across variables in the problem domain (e.g. financial ratios and the financial health of a bank). The first part of this study illustrates how a computer program developed by the authors can be used to generate and evaluate different feasible belief network structures based on historical data. The program uses an information-theoretic measure to compare the alternative structures. The ability of the program to identify existing dependencies across variables is demonstrated by using it to reconstruct a known network structure from simulated data. Next, the program is used on a database of twelve important bank financial ratios over a three-year period. The predictive ratios identified by the program reflect important areas of a bank's health, such as loan quality, efficiency, profitability and capital adequacy. Finally, a belief revision mechanism is encoded for the belief network structure identified earlier, and is used to illustrate how it can assist auditors in making recommendations about financial health based on a bank's critical financial ratios. The probability estimates provided by the system are validated using data on banks not used in the network design stage, and are found to be reliable.     

Good for one,bad for all: Determinants of individual versus systemic risk

We analyze a sample of large international banks in major advanced economies and examine the impact that bank-specific factors have on an institution's solvency risk and its contribution to systemic risk. We focus on the five categories that the Basel Committee on Banking Supervision has recently proposed as indicators of systemic importance. Our findings suggest that unstable funding is the main factor driving systemic risk. Furthermore, the combination of significant trading activities with global presence appears to exacerbate spillover risks to the global financial system. Interestingly, whereas trading activities contribute to the build-up of correlated or ‘wrong-way’ risk they help to mitigate individual solvency risk. Conversely, a decentralized approach to liquidity management seems to alleviate individual solvency risk but amplifies the transmission of financial distress across the financial system. This suggests that a macro-prudential approach to financial regulation should focus not only on scaling up micro-prudential measures but also on enabling the efficient transfer of risk between financial institutions.     

Measuring systemic risk in the European banking sector: a copula CoVaR approach

We propose a new methodology based on copula functions to estimate CoVaR, the Value-at-Risk (VaR) of the financial system conditional on an institution being under financial distress. Our Copula CoVaR approach provides simple, closed-form expressions for various definitions of CoVaR for a broad range of copula families and allows the CoVaR of an institution to have time-varying exposure to its VaR. We extend this approach to estimate other ‘co-risk’ measures such as Conditional Expected Shortfall (CoES). We focus on a portfolio of large European banks and examine the existence of common market factors triggering systemic risk episodes. Further, we analyse the extent to which bank-specific characteristics such as size, leverage, and equity beta are associated with institutions' contribution to systemic risk and highlight the importance of liquidity risk at the outset of the financial crisis in summer 2007. Finally, we investigate the link between macroeconomy and systemic risk and find that changes in major macroeconomic variables can contribute significantly to systemic risk.     

Does supply network location affect corporate investment efficiency?

Using social network analysis, we compute a firm's network position characteristics and then examine their effects on firm investment efficiency. The results show that both supply network centrality and structural holes have no significant impact on corporate overinvestment but can ease corporate underinvestment by alleviating financial constraints. The specific paths are as follows: a firm that has a high level of centrality or rich structural holes in the supply network is more likely to obtain commercial credit and bank loans; however, supply network position has no significant impact on equity financing.     

Are Market‐Based Measures of Global Systemic Importance of Financial Institutions Useful to Regulators and Supervisors?

We analyze whether four market‐based measures of the global systemic importance of financial institutions offer early warning signals during three financial crises. The tests based on the 2007–2008 crisis show that only one measure (?CoVaR) consistently adds predictive power to conventional early warning models. However, the additional predictive power remains small and it is not normally confirmed for the Asian and the 1998 crises. We conclude that it is problematic to identify a market‐based measure of systemic importance that remains valid across crises with different features. The same criticism also applies to several conventional proxies of systemic importance, of which size is the most consistent performer.     

关于开放市场条件下防范系统性风险的研究

随着经济金融全球化程度的加深,评价和防范开放经济条件下一国系统性金融风险的重要性日益明显。文章根据系统性金融风险的表现形式,提出了一个三层次的风险评价指标体系,并通过熵值法确定各子系统风险因子之间的权重。实证分析结果显示,近年来我国金融业总体稳健程度得到有效提升,但未来仍需密切关注风险因素的动态变化,采取切实有效的措施夯实系统性金融风险管理体系建设。     

基于动态因子Copula模型的我国银行系统性风险度量

本文基于2007年至2019年我国14家上市银行的股票收益率,构建偏态t-分布动态因子Copula模型,利用时变荷载因子刻画单家银行与整个系统的相关性,计算联合风险概率作为系统性风险整体水平的度量,基于关联性视角提出了新的单家机构系统脆弱性和系统重要性度量指标——系统脆弱性程度和系统重要性程度。该方法充分考虑了银行个体差异性和系统的内在关联性以及收益率的厚尾性和非对称性,从而能够捕捉到更多的信息且兼具时效性。研究表明:银行机构在风险聚集时期相关程度更大,联合风险概率能够准确识别出系统性风险事件且在我国推行宏观审慎评估体系以后有明显降低;整体而言,大型商业银行系统重要性水平最高,同时风险抗压能力也最强;本文使用的度量方法降低了数据获取成本且更具时效性,有助于为宏观审慎差异化监管工作提供借鉴和参考。     

监测系统性金融风险——中国金融市场压力指数构建和状态识别

对系统性金融风险进行识别和评估,日益成为各国中央银行的核心关切。囿于数据频率,基于金融机构经营稳健性评估的金融系统性风险监测存在一定的滞后性,不利于中央银行及时进行风险应对,利用金融市场交易数据进行风险监测可极大程度克服滞后性问题。本文根据中国金融市场特点,选取债券市场、股票市场、货币市场和外汇市场17个有代表性的指标,运用经验累积分布函数法分别构造了各子市场的压力指数,以各子市场之间时变的相关关系刻画系统性金融风险的跨市场传染特征,合成金融市场压力指数,并通过建立马尔可夫区制转换模型,对金融市场压力状态进行识别。金融市场压力指数能有效反映样本域内的压力事件,并兼具稳健性、能逐日监测等优点,为监测评估系统性金融风险、选择政策实施窗口和评估政策实施效果等提供了有力工具。     

基于宏观审慎的金融监管指标体系构建研究

传统的微观审慎监管只关注单个金融机构的稳定,无法避免其繁荣期的过度冒险行为,导致系统性风险累积爆发。宏观审慎监管则需识别和控制金融系统性风险,确保整个金融体系的稳定。通过构建4个子系统24项指标的金融监管指标体系,并运用主成分分析法,把24项指标划分为六个主成分,共能解释89.724%的变异量。分析我国1995年—2009年的面板数据,发现我国金融稳定指数不断升高,尽管遭遇两次大规模金融危机的冲击,但保持了难得的金融稳定,这得益于金融监管水平的提高和逆周期调控措施的实施。