Delegation and the regulation of U.S. financial markets

We analyze the institutional determinants of U.S. financial market regulation with a general model of the policy-making process in which legislators delegate authority to regulate financial risk at both the firm and systemic levels. The model explains changes in U.S. financial regulation leading up to the financial crisis. We test the predictions of the general model with a novel, comprehensive data set of financial regulatory laws enacted specifically between 1950 and 2009. The theoretical and empirical analysis finds that economic and political factors impact Congress’ decision to delegate regulatory authority to executive agencies, which in turn impacts the stringency of financial market regulation, and our estimation results indicate that political factors may have been stronger and resulted in inefficiencies.     

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。     

资产透明度、监管套利与银行系统性风险

资产不透明的金融机构过度依赖批发性融资进行监管套利不利于系统性风险的防控。在此背景下,本文首先在经典银行道德风险模型的基础上引入关联性,从资产透明度和监管套利的视角分析银行系统性风险累积的内在机理。而后利用2007-2018年中国上市银行微观数据,构建资产透明度指标和系统性风险指标(SRISK、MES),对理论推论进行实证检验。主要结论有:(1)资产不透明、监管套利会提高银行的系统性风险。(2)监管套利弱化了资产透明度和资本监管机制对银行系统性风险承担的约束作用,资产透明度与资本监管机制在约束系统性风险承担中的协调作用不明显。(3)以大银行为主的债权银行受监管套利的影响相较于受资产透明度的影响更明显。在此基础上,我们对完善金融风险防范体系以及监管机制提出了若干建议。     

Multilayer financial networks and systemic importance: Evidence from China

In this paper, we develop a multilayer network structure and reveal the relationship between network structure and systemic risk. Unlike many previous studies, our model considers both liability and cross-holding of shares between financial institutions simultaneously. We propose a new systemic risk measurement by exploring the dynamic mechanism of financial contagion in the multilayer network. We display the network structure of Chinese financial institutions, including connectivity and diversity, and identify the systemic importance of them. We demonstrate that the multilayer network plays a non-linear role in financial risk spreading. Using the panel regression model and several experiment evidences, we show that the systemic risk can be explained more effectively by the linkage diversity more than the connectivity at both the institutional level and the system level. Our results highlight the importance of considering contagion mechanisms that go beyond a simple single-layer network structure.     

Bank profitability in the Eurasian Economic Union: Do funding liquidity and systemic importance matter?

The post-crisis regulatory architecture targets greater banking stability by imposing additional capital and liquidity requirements. Profit persistence, however, remains an important factor for attaining this goal. Using annual data for 2008–2017, this study analyzes the relationship between funding stability, systemic importance, and the profitability of banks in the three founding states of the Eurasian Economic Union (EAEU): Russia, Kazakhstan, and Belarus. The results show a strong degree of stability in net interest margin (NIM) and a lack of persistence in return on assets (ROA). Compliance with the minimum level of the Net Stable Funding Ratio (NSFR) reduces both the funding liquidity risk and the NIM of EAEU banks. Moreover, systemically important banks in the region historically operate at a lower interest spread and less prudent NSFR, which implies a potentially greater adverse effect on their NIM. Bank-specific variables have various impacts depending on the measure of profitability. The results also highlight that greater market concentration protects the NIM and negatively impacts the ROA of EAEU banks. Finally, Western sanctions have a destabilizing effect on the NIM of EAEU banks, but not on systemically important banks.     

Systemic financial risk early warning of financial market in China using Attention-LSTM model

We propose an Attention-LSTM neural network model to study the systemic risk early warning of China. Based on text mining, the network public opinion index is constructed and used as a training set to be incorporated into the early warning model to test the early warning effect. The results show that: (i) the network public opinion is the non-linear Granger causality of systemic risk. (ii) The Attention-LSTM neural network has strong generalization ability. Early warning effects have been significantly improved. (iii) Compared with the BP neural network model, the SVR model and the ARIMA model, the LSTM neural network early warning model has a higher accuracy rate, and its average prediction accuracy for systemic risk indicators has been improved over short, medium and long terms. When the attention mechanism is included in the LSTM, the Attention-LSTM neural network model is even more accurate in all the cases.     

中国金融系统风险溢出效应研究——基于溢出指数和波动溢出网络

文章基于溢出指数和波动溢出网络方法，从静态和动态分别度量我国金融系统不同子市场间的风险联动水平及变动趋势。研究结果表明，我国金融系统风险溢出效应整体水平较高，各市场间联动性较强；市场内部滞后效应大于市场之间溢出效应，两两有向溢出效应具有强不对称性；作为我国金融系统的风险中心，货币市场始终处于风险溢出方，但在金融危机时期，其对外风险溢出效应相对减弱，而大宗商品市场、资本市场、房地产市场等其余市场的风险溢出效应相对增强。值得注意的是，当前我国金融系统整体风险溢出水平较高，市场间风险相关性较强，需要进一步加强系统性风险的监测与防范。     

TrAffic LIght system for systemic Stress: TALIS3

For the purposes of financial stability, identifying financial institutions that, when in distress, could have a significant adverse impact on financial markets is important. A TrAffic LIght System for Systemic Stress (TALIS-cube) is proposed that provides a comprehensive color-based classification for grouping companies according to both the stress reaction level of the system when the company is in distress and the company’s stress level. TALIS³ can integrate multiple signals from the interaction between different risk metrics. Starting from specific risk indicators, companies are classified by combining two loss functions—one for the system and one for each company—evaluated over time and as a cross section. An aggregated index is also obtained from the color-based classification of companies. TALIS³ can be used to enhance the performance and robustness of existing systemic risk measures. An empirical analysis of the U.S. market is also provided.     

Capital and resolution policies: The US interbank market

We develop an empirically based simulation study to test two types of policies designed to control systemic risk: preventive policies targeting capital requirements and mitigation policies targeting default resolution. We find that capital buffers reduce both the number of defaults and the resulting losses. The loss reduction benefit increases as the magnitude of adverse shocks becomes higher. We find that a simple branch-breakup resolution strategy reduces the loss borne by the Federal Deposit Insurance Corporation (FDIC). The mitigation effect becomes higher as the fraction of assets resolved through auctions and auction competitiveness increase.     

我国金融市场基础设施管理:现状、难点和立法路径

随着我国金融市场的纵深化发展,金融市场基础设施因其基础服务、系统性风险管理、辅助监管以及助力金融市场开放和营商环境完善等作用而日益受到重视,并成为现代金融治理和推动金融现代化的重要内容。但我国金融市场基础设施在运行和管理过程中却存在监管分散、制度空白、支持宏观审慎监管不力等情况,各方在相关概念和标准、统筹监管、恢复与处置安排等方面难以形成法律共识。为更好发挥金融市场基础设施作用,完善制度环境,我国应从金融市场基础设施的相关概念入手,明确其稳健运行所需的保障手段,完善统筹监管框架,有效衔接其他相关法律,并通过分步走的方式填补制度空白,提高立法层级。