资产证券化与银行业系统性风险 ——基于"去一"分析法的应用

本文以防范银行业系统性风险为出发点,考察资产证券化对银行业系统性风险的影响,并运用最新的"去一"分析法对不同类型银行的系统性风险贡献度展开研究.在此基础上,本文考察了资产证券化对银行业系统性风险的影响路径,以及不同类型银行构成的银行系统中,影响路径的异质性.研究结果表明,资产证券化显著增加了银行业系统性风险,且中等规模银行及股份制商业银行是风险的主要来源者和传播者;此外,银行间产品互持路径对银行业系统性风险的影响并不显著,但应用"去一"依次去除大规模银行以及大型国有商业银行后,该路径显著通畅.这说明,资产证券化产品在银行间的互持现象,在一定程度上增加了银行间的关联度,进而提升了银行业系统性风险.     

“双支柱”调控与银行系统性风险——基于SRISK指标的实证分析北大核心

健全货币政策和宏观审慎政策"双支柱"调控框架,促进金融稳定,实现经济金融平稳健康发展,是我国现阶段的重要任务。本文采用动态DCC-GARCH模拟方法计算SRISK衡量的银行系统性风险,以2002年第三季度—2019年第四季度中国A股上市银行为研究样本,研究了"双支柱"调控对银行系统性风险的影响。实证分析发现,总体上同时紧缩的货币政策与宏观审慎政策,能够抑制银行系统性风险。基于银行性质、房地产周期以及经济波动的异质性分析发现,在不同情景下,各类宏观审慎政策工具与货币政策配合,抑制银行系统性风险的有效性存在差异。需要说明的是,我国实施的MPA评估体系总体上对银行系统性风险具有抑制作用。本文研究结论对于"双支柱"调控框架的健全以及调控方式的改进具有一定的参考价值。     

资管新规下银行监管套利及系统性风险抑制

本文选用2015-2021年16家主要上市银行半年度数据作为样本，研究发现资管新规出台后，银行业系统性风险显著降低，但该政策效果在规模不同的银行间存在异质性。进一步分析发现，银行理财套利削弱了资管新规对降低系统性风险的影响。本文为资管新规对银行监管套利及系统性风险抑制提供了初步的微观证据，为强化系统性风险抑制，继续有效促进实体经济脱虚向实提供了重要政策启示。     

实体经济波动对银行系统性风险的影响——如何理解金融周期的作用

本文基于2007Q4-2021Q3的中国14家上市银行的数据,运用面板回归模型研究了实体经济波动对银行系统性风险的具体影响。研究发现:在金融周期演化过程的上行期实体经济波动对银行系统性风险有正向影响,在下行期有负向影响;金融周期和经济周期的同步对该影响具有增强作用,两者异步则和该影响具有减弱作用。因此,在银行系统性风险监管过程中,应针对金融周期不同时期采取差异性措施。     

银行业系统性金融风险评估研究——基于GARCH-CoVAR模型

本文从银行业系统性风险的产生和蔓延原因入手,测算8家上市股份制商业银行VAR. CoVAR及风险溢出效应,构建了银行业系统性风险评估模型,进而针对我国银行业系统性风险评估和防范提出对策建议。     

利率市场化与中国银行业系统性风险研究

为了量化利率市场化可能带来的系统性风险,本文构建了一个涵盖利率风险、银行间传染风险和流动性风险的系统性风险量化模型,采用中国129家银行的财务数据,通过拓展的矩阵法对不同冲击下的银行业系统性风险进行了压力测试。研究表明:利率市场化会显著增加中国银行系统的脆弱性,提高银行业的系统性风险水平;利率敏感性缺口较大、规模较小的银行更容易倒闭;重度压力测试下会爆发银行业系统性危机。基于实证结果,本文认为:为规避系统性风险,银行应当严控利率风险、加强产品创新和业务拓展,并且在存放同业资产时,选择同业资产少的银行作为交易对手,防止同业交易过于集中导致系统性风险的积聚。     

基于未定权益分析模型的我国银行业系统性风险测度研究

论文基于我国上市银行资产负债和股价数据,运用未定权益分析模型对我国银行业系统性风险进行测度。研究表明,2002年以来我国银行业经历了三个高风险时期,但当前风险水平较低。进一步分析发现,银行业系统性风险具有突变性、单个机构风险大幅上升可能是总体风险暴露的前兆、当前城市商业银行风险高于国有大型商业银行和中小股份制银行等特征。基于上述结论,论文提出了加强对个体风险处置、完善宏观审慎制度等政策建议。     

银行同质化对系统性风险的影响——基于我国上市银行的实证研究

本文选取我国A股上市银行财务数据,通过余弦相似度模型测算了银行间同质化水平,并实证检验了银行同质化与系统性风险的关系。结论表明,整体而言,我国上市银行同质化水平的提高可以显著降低其系统性风险,但这种影响效果与银行性质及贷款占比有关。机制检验显示,银行同质化可以通过降低银行个体风险和加强银行业竞争水平的渠道抑制系统性风险。基于以上结论,本文从商业银行个体和监管当局的角度,针对性地提出政策建议。     

我国银行业系统性风险研究——基于拓展的未定权益分析法北大核心CSSCISSCI

系统性风险一直以来是学术界研究的前沿问题。基于拓展的CCA方法本文研究了金融危机后我国商业银行的系统性风险。本文利用2007年第四季度到2012年第三季度上市银行的股票市场数据和财务报表数据,构建了具有前瞻性特征的隐含资产波动率、ADD、WDD、PDD、政府隐性担保等系统性风险日频指标序列,以能刻画银行间资产联动性的PDD和ADD之差以及政府隐性担保为基础,分析了我国大型商业银行、股份制商业银行以及银行业系统性风险的动态演变特征,研究发现银行体系的系统性风险受到国内外经济金融形势的显著影响,股份制商业银行的风险要小于大型银行,2012年第三季度银行业系统性风险呈现出增大的趋势。基于拓展的CCA方法的系统性风险指标综合了市场信息和财务报表信息,对市场信息反应迅速,能动态地刻画银行体系的风险状况。     

基于VaR模型的商业银行体系系统性风险研究

本文以中国2016年之前上市商业银行作为中国银行业的代表,测算银行业系统性 风险VaR。整体来讲,我国银行业系统性风险较低,但VaR在2015年较高。虽如此,我国银行业资本持有量能够抵御银行体系的系统性风险。在系统性风险VaR贡献度方面,本文实证分析表明,在样本期间内,浦发银行、中国银行、农业银行、交通银行贡献度较高。银行体系系统 性风险VaR受GDP增长率和沪深300指数收益率的显著影响。     

A simple indicator of systemic risk

We examine the relevance and effectiveness of stock return correlations among financial institutions as an indicator of systemic risk. By analyzing the trends and fluctuations of daily stock return correlations and default correlations among the 22 largest bank holding companies and investment banks from 1988 to 2008, we find that daily stock return correlation is a simple, robust, forward-looking, and timely systemic risk indicator. There is an increasing trend in stock return correlation among banks, whereas there is no obvious correlation trend among non-banks. We also disaggregate the stock returns into systematic and idiosyncratic components and find that the correlation increases are largely driven by the increases in correlations between banks’ idiosyncratic risks, which give rise to increasing systemic risk. Correlation spikes tend to predict or coincide with significant economic or market events, especially during the 2007–2008 financial crisis. Furthermore, we show that stock return correlations offer a perspective on the level of systemic risk in the financial sector that is not already captured by default correlations. Stock return correlations are not subject to data limitations or model specification errors that other potential systemic risk measures may face. Therefore, we recommend that regulators and businesses monitor daily stock return correlations among those large and highly leveraged financial institutions to track the level of systemic risk.     

基于经济资本管理的贷款系统性风险防范研究

在系统性风险防范的视角下,本文对经济资本管理的基本方法进行了重新梳理,发现现行的经济资本管理会导致亲周期效应问题,削弱其防范系统性风险的能力。为此,要在系统性风险防范目标下改进经济资本计量方法,以科学的系统性风险预测为基础确定经济资本限额,优化经济资本在行业和地区层面的分配,以及通过贷款集中度管理追求风险分散最大化,从而实现对系统性风险的有效防范。     

Systemic risk of commodity markets: A dynamic factor copula approach

This study aims to measure the systemic risk of commodity markets and investigate its causal relationship with the macroeconomy. First, we propose a novel measure called the joint probability of abnormal changes (JPAC) to measure the systemic risk of commodity markets. Second, we introduce two new measures, the expected proportion of commodities in abnormal price change (EPAPC) and the contribution to systemic risk (CSR), to identify the systemic importance of each commodity. Third, we examine the relationship between JPAC and some key macroeconomic variables using mixed-frequency Granger causality tests. We conduct an empirical study using 24 commodity indices from 2015 to 2021. Our results reveal that: (1) JPAC can well capture the risk events in the real world; (2) the systemic risk of commodity markets has increased significantly since the start of the US-China trade war; (3) EPAPC and CSR indicate that energy commodities have higher systemic importance than others and are most likely to cause market fluctuations; and (4) some causal relationships between the systemic risk of commodity markets and the macroeconomy are identified. Overall, this study improves our understanding of systemic risk in commodity markets and provides important implications for policymakers in China and the US.     

政策连续性与商业银行系统性风险

本文基于2007年第一季度至2019年第四季度中国A股32家上市银行非平衡面板数据,从“冲击”和“传染”两个维度考察了政策连续性对银行系统性风险的影响。实证结果表明,政策连续性程度的提高通过降低银行个体风险和减弱银行个体与系统的关联性进而显著降低了银行系统性风险。进一步分析发现,政策连续性降低了银行被动风险承担水平而非主动风险承担意愿,减弱了银行间接关联程度而非直接关联程度。异质性分析表明,经济下行和货币宽松时期,政策连续性对系统性风险的降低效应更大,并且本身破产风险越高、信息透明度越低的银行,其系统性风险受政策连续性的影响越大。区分不同类型的政策发现,货币政策、财政政策、汇率与资本项目政策的连续性上升均能显著降低银行系统性风险,其中货币政策连续性对银行系统性风险的影响力度最大。     

中国房地产企业间系统性风险溢出效应分析——基于尾部风险网络模型

本文以2007—2021年沪深A股上市房企为样本,首先基于SIM单指数分位数回归技术提出测量系统性风险的新指标SIM-CoVaR,并结合前沿的TENET网络模型,构造跨房地产企业风险动态传染的尾部风险网络,然后采用块模型探究房地产市场系统性风险溢出的聚类性、触发机制及传播路径,最后考察网络整体结构和宏观经济变量对房地产市场系统性风险溢出的影响。研究表明:(1)我国房地产企业间存在明显的系统性风险联动性和溢出效应,在市场动荡时期房地产部门是金融风险溢出的放大器;(2)评估系统重要性节点企业时,除考虑企业规模等内部属性,还应考虑房企间关联结构,利用系统性风险指数可有效捕捉网络中系统重要性节点;(3)跨房企的系统性风险溢出具有显著的聚类特征,尾部风险网络可被划分为4个不同的功能模块,各模块的成员及其角色呈现明显的时变特性,监管部门可据此从供给端“因企施策”;(4)网络聚集性、网络效率和网络匹配性的降低能显著降低房地产市场的系统性风险溢出效应。本文从企业微观层面探讨房地产市场风险的形成机制,为促进房地产业健康发展和防范化解宏观层面的系统性金融风险提供参考。     

碳定价、双重金融摩擦与“双支柱”调控

本文构建包含异质性企业、双重金融摩擦和“双支柱”政策的DSGE模型来探究碳税和碳交易这两种碳定价政策对中国宏观经济的长短期影响和作用机制。研究发现:(1)两种碳定价政策均会导致经济在短期出现一定衰退,但在长期则有助于推进经济高质量发展,达到更高的均衡水平;(2)在面对碳排放技术冲击时,相比碳税政策,碳交易政策下,碳价大幅波动会进一步加剧经济波动,在碳交易市场中对碳价设定上下限,可以有效地减轻碳排放技术冲击所导致的经济波动;(3)面对气候政策冲击,包含金融部门风险规避的双重金融摩擦会进一步加剧气候政策对宏观经济的负面影响;(4)在经济转型过程中,结构性供需不平衡会引发一定的通胀现象,但此时货币政策不宜对通胀做出过多反应,而应刺激产出,支持绿色发展,推动供需平衡,从根源上解决通胀问题。引入“双支柱”调控后发现,考虑到经济转型风险的宏观审慎政策能显著减弱气候政策所导致的经济波动和金融不稳定,提高居民福利。     

Research on stock volatility risk and investor sentiment contagion from the perspective of multi-layer dynamic network

In the post-epidemic period, the international economic structure has been readjusted, with risks contagious across financial and economic systems. This paper primarily uses the high-frequency TENET network and the Granger-causality network to describe the interconnectedness between the tail risk of stock volatility and investor sentiment, then the two-layer network is constructed by the generalized variance decomposition method to examine the inter-layer connectedness. Based on the two-layer network, the heterogeneity frequency response of network connectedness and dynamic network structure are further analyzed from the perspective of frequency domain. The study found that the tail risk of high-frequency stock volatility displays industry heterogeneity and time-varying property, and investor sentiment contagion network provides information transmission medium for stock risk. The double-layer network study found that stock volatility in consumer goods industry exhibits higher risk spillover to investor sentiment. The diversified financial industry, real estate industry and energy industry in the two-layer network are systemically important industries. In addition, the study of the frequency domain dynamic network found that the connectedness volatility in the short-term risk network of stock volatility was significantly higher than that of the investor sentiment network, and the short-term risk spillover effect of the network played a leading role in the total risk spillover. The research conclusions provide reference for preventing systemic risks from the perspective of systemically important industries and cyclical fluctuations.     

Systemic risk,economic policy uncertainty and firm bankruptcies: Evidence from multivariate causal inference

The paper investigates causal relationships between systemic risk, economic policy uncertainty and firm bankruptcies, conditional on global volatility proxied by the VIX index, in a sample of 15 advanced and major emerging market economies during January 2008-June 2018. We test for Granger causality in time and frequency domains as well as dissect multivariate causal linkages in the dynamic complex system framework by applying a novel technique – convergent cross mapping (Sugihara et al., 2012). Based on strictly coincident results from all the three approaches, we find that systemic risk causes firm exit in Spain, while in the UK and the Netherlands bankruptcies are triggered by economic policy uncertainty. In South Korea and the USA, the VIX index causes the firm shutdown. For the rest of the countries, the causality inference provides less robust evidence. We argue that the magnitude of deleveraging by banks with respect to the private nonfinancial sector, proxied by the volatility of credit-to-GDP gaps, shapes the presence or absence of causal impact by systemic risk, economic policy uncertainty or the VIX index on bankruptcies.     

Considerations of a gold-denominated life insurance policy

Global inflation and economic cyclical fluctuations have accelerated the depreciation rate of monetary assets. Safeguarding the purchasing power of long-term life insurance products’ cash flow becomes an issue of great theoretical and practical significance for life insurance. Using data from China, this article designs a long-term life insurance policy denominated in ounces of gold, and compares it with traditional long-term life insurance policies. For the time frame of interest to this study, we confirm that a long-term life insurance policy denominated in ounces of gold provided significant protection against the effects of inflation and economic cyclical fluctuations. We propose a risk management program aimed at price risk, interest rate risk, currency risk and investment risk as a result of the insurance policy denominated in ounces. Our recommended strategy includes an inducing index method to hedge against the losses caused by price fluctuations of gold.     

A semiparametric model for the systematic factors of portfolio credit risk premia

The aim of this paper is to investigate the empirical relationship between daily fluctuations in the risk premium for holding a large diversified credit portfolio, which we approximate by a benchmark credit index, and some tradeable market factors which capture systematic risk. The analysis is based on an adaptive nonparametric modelling approach which allows for the data-driven estimation of the nonlinear dynamic relationship between portfolio credit risk premia and their hypothetical components. Our main finding is that the empirical weights of the systematic factors display sudden jumps during market crises and a less intense time-dependent behaviour during normal market conditions. In addition, we find that during market crises the directions of the empirical relationships are often inconsistent with ordinary economic intuition, as they are influenced by the specific circumstances of financial markets distress.