以内部评级法改进信用风险限额管理

信用风险限额管理的基本涵义一般而言,信用风险由违约风险、清偿风险和头寸风险三部分组成。违约风险通常用违约概率(PD)度量;清偿风险是清偿率(RecoveryRate)不足以弥补银行的风险暴露所造成风险,用违约损失率(LGD)度量;头寸风险指暴露在信用风险下头寸大小的不确定性,用违约风险暴露(EAD)度量。信用风险限额是商业银行根据风险和收益相匹配的原则,采用一定的标准和方法,确定其可以承受的信用风险敞口上限,即其可接受的违约风险暴露上限。信用风险限额管理是指商业银行对信用风险限额进行分配、监测、预警和控制的全过程管理。通常,商…     

商业银行信用风险缓释工具及LGD估值研究

在信用风险内部评级初级法下,违约损失率(LGD)的估值是由监管当局给定的,然而在债项层面.依然有许多工作值得研究,一般说来,至少包括三个层次:一是合格风险缓释工具的认定;二是风险缓释工具价值及其覆盖的风险敞口的计量;三是组合风险缓释工具下违约损失率的估算.初级法下合格信用风险缓释工具通常包括抵质押品、净额结算、保证和信用衍生工具四大类,每类缓释工具对债项发挥不同的信用风险缓释功能,对于运用组合风险缓释工具的债项,在估算违约损失率时,应将债项违约风险暴露划分成若干部分,每一部分由一种或一类信用风险缓释工具覆盖,然后进行加权计算.     

信用违约互换的契约方程分析及其在中国的应用研究蒋静，

信用违约互换是信用衍生工具中运用最广泛的工具之一，其产生旨在对付信用风险，参与双方之间签订一项金融性合同，允许信用风险从其他风险中剥离出来，并可以从一方转移到另一方。本文通过对信用违约互换的分解分析和避险机制的研究，论证其在积极信贷资产组合管理、信用风险管理和提高资本市场运行效率方面的显著优势，认为其在我国将有极大的发展前景。     

内部评级法框架下商业银行信用风险的资本测算

依据信贷资产分类贷款迁徙率矩阵,获取商业银行信贷业务各级形态贷款的违约概率;依据商业银行信贷审批的管理原则、资产清收的执行原则以及商业银行在清收时不可能通过诉讼获利的司法特征,建立抵押品池综合违约损失率的计算模型。基于以上模型,采用巴塞尔新资本协议IRB法计算出的信用风险在一般情况下低于依据银监会资本充足率管理办法计算出的信用风险。     

新资本协议内部评级法对宏观经济运行的影响：亲经济周期效应研究

新资本协议内部评级法大幅度提高了资本监管的风险敏感度,有助于增强银行体系的运行效率和稳定性,但可能导致信贷运行和经济周期的过度波动。本文认为,由于信用风险是变化的,违约概率、违约损失以及违约风险暴露具有亲周期的特点,亲周期程度取决于银行所采用的模型方法和预测时间;通过第一支柱下降低风险参数的风险敏感度、降低风险权重函数曲线的斜率,第二支柱下的压力测试、设立超额资本要求、平滑风险权重函数的输出值,以及提取动态准备金和实施宏观经济政策等方法能够有效缓解内部评级法的亲经济周期效应;监管当局应在更宏观的框架下分析内部评级法的宏观经济效应,选择合理的政策工具解决亲经济周期效应问题。     

我国银行业信用风险宏观压力测试研究

本文通过实证研究提出并论证了一种宏观压力测试方法,该方法可用于银行业监管和系统性风险的防范.首先采用有序多分类Logistic模型测算行业原始违约概率,再运用MFD违约概率模型将宏观冲击因子引入以求得渗入宏观经济因子的违约概率,然后采用CreditRisk+模型分别测算不同宏观压力情景下与信用风险对应的经济资本变化,经...     

财务公司信贷资产风险防范的实践和思考

财务公司信贷资产风险其实就是信用风险又称违约风险，是指借款企业不能按期还本付息，给财务公司带来损失的可能性。信用风险主要受到贷款企业资本实力、经营效益、财务状况、还款意愿等诸多因素的影响。深入研究这一课题，对财务公司具有非常重要、非常深远的意义。     

基于信用违约互换的商业银行信用风险管理探析

信用风险是商业银行面临的最主要风险,目前传统的信用风险管理方法和工具在应用中愈发显得力不从心.本文主要分析了一种新型的管理信用风险的工具--信用违约互换,它可以在继续保持与客户关系的前提下,将信用风险从其他风险类型中剥离出来,以一定的代价转移给其他投资者,从而达到分散风险的目的,提高信贷资产的流动性.     

信用违约互换(CDS)在中国的实践及业务模式探讨

近年来喏全球金融市场信用违约事件多发喏利用各类信用风险管理工具管理、组合、规避风险成为重要课题喏信用违约互换工具在各国普遍应用.本文对中国CDS工具业务模式、运营机构情况进行了全面调查喏对进一步完善信用风险缓释工具提出了针对性建议.     

中小企业集合债券总体信用风险度量研究

中小企业集合债券总体信用风险既包括系统风险产生的周期性违约风险,又包括相互关联关系导致的传染性违约风险。首先通过对因素模型的改进构建模型Ⅰ,研究集合债券的周期性违约风险;在此基础上引入违约传染建立模型Ⅱ,分析违约传染对违约概率及违约相关性的影响,研究集合债券的总体信用风险。最后基于模型Ⅱ进行算例研究,得出结论：企业间的相互关联关系降低了其1次违约概率,增加了其多次违约概率即违约相关性。     

Counterparty Risk for Credit Default Swaps: Markov Chain Interacting Intensities Model with Stochastic Intensity

We analyze the counterparty risk for credit default swaps using the Markov chain model of portfolio credit risk of multiple obligors with interacting default intensity processes. The default correlation between the protection seller and underlying entity is modeled by an increment in default intensity upon the occurrence of an external shock event. The arrival of the shock event is a Cox process whose stochastic intensity is assumed to follow an affine diffusion process with jumps. We examine how the correlated default risks between the protection seller and the underlying entity may affect the credit default premium in a credit default swap.     

违约风险模型对违约定义的敏感性研究

本文根据贷款信用风险四级分类和五级分类定义三种违约,运用商业银行的贷款企业会计数据分析了Logistic违约风险模型对违约定义的敏感性。实证研究表明,在三种违约定义下,违约模型的结构相似,但模型选择的变量和变量的显著水平存在差异,违约模型对违约定义具有敏感性。     

From equity to default correlation with taxes

For fixed income investment, the preponderant risk is the clustering of defaults in the portfolio. Accurate prediction of such clustering depends on the knowledge of default correlation. We develop models with exogenous debt and endogenous debt to predict default correlations from equity correlations based on a self-consistent structural framework. We also examine how taxes affect the prediction of default correlations based on the two models. The empirical analysis shows that the corporate taxes tend to decrease default correlations, while personal taxes could increase or decrease default correlations. Our default correlation model with exogenous debt does a better job of predicting default correlations for high quality bonds, while the one with endogenous debt predicts more accurately for lower rated bonds. Our studies not only theoretically improve the modeling of default correlation in the structural setting but also shed new light on various aspects of default correlations and thereby help financial practitioners price credit derivatives more accurately and formulate more effective strategies to manage default risk of credit portfolios.     

Default correlation: An empirical investigation of a subprime lender

In recent years, subprime lending has grown substantially as an important sector of the credit markets. This paper is concerned with the risk management of subprime loan portfolios and the importance of default correlation in measuring that risk. Using a large portfolio of residential subprime loans from an anonymous subprime lender, we show that default correlation is substantial for this lender. In particular, the significance of default correlation increases as the internal credit rating declines. Our results suggest that lenders and regulators would be well served investing in the understanding of default correlation in subprime portfolios.     

Bilateral credit valuation adjustment for large credit derivatives portfolios

We obtain an explicit formula for the bilateral counterparty valuation adjustment of a credit default swaps portfolio referencing an asymptotically large number of entities. We perform the analysis under a doubly stochastic intensity framework, allowing default correlation through a common jump process. The key insight behind our approach is an explicit characterization of the portfolio exposure as the weak limit of measure-valued processes associated with survival indicators of portfolio names. We validate our theoretical predictions by means of a numerical analysis, showing that counterparty adjustments are highly sensitive to portfolio credit risk volatility as well as to the intensity of the common jump process.     

Systemic Bank Risk in Brazil: A Comprehensive Simulation of Correlated Market, Credit, Sovereign and Inter-Bank Risks

In this study we present a comprehensive forward‐looking portfolio simulation methodology for assessing the correlated impacts of market risk, private sector and Sovereign credit risk, and inter‐bank default risk. In order to produce better integrated risk assessment for banks and systemic risk assessments for financial systems, we argue that reasonably detailed modeling of bank asset and liability structures, loan portfolio credit quality, and loan concentrations by sector, region and type, as well as a number of financial and economic environment risk drivers, is required. Sovereign and inter‐bank default risks are increasingly important in the current economic environment and their inclusion is an important model extension. This extended model is demonstrated through an application to both individual Brazilian banks (i.e., 28 of the largest banks) and groups of banks (i.e., the Brazilian banking system) as of December 2004. When omitting Sovereign risk, our analysis indicates that none of the banks face significant default risk over a 1‐year horizon. This low default risk stems primarily from the large amount of government securities held by Brazilian banks, but also reflects the banks' adequate capitalizations and extraordinarily high interest rate spreads. We note that none of the banks which we modeled failed during the very stressful 2007‐2008 period, consistent with our results. Our results also show that a commonly used approach of aggregating all banks into one single bank, for purposes of undertaking a systemic banking system risk assessment, results in a misestimate of both the probability and the cost of systemic banking system failures. Once Sovereign risk is considered and losses in the market value of government securities reach 10% (or higher), we find that several banks could fail during the same time period. These results demonstrate the well known risk of concentrated lending to a borrower, or type of borrower, which has a non‐zero probability of default (e.g., the Government of Brazil). Our analysis also indicates that, in the event of a Sovereign default, the Government of Brazil would face constrained debt management alternatives. To the best of our knowledge no one else has put forward a systematic methodology for assessing bank asset, liability, loan portfolio structure and correlated market and credit (private sector, Sovereign, and inter‐bank) default risk for banks and banking systems. We conclude that such forward‐looking risk assessment methodologies for assessing multiple correlated risks, combined with the targeted collection of specific types of data on bank portfolios, have the potential to better quantify overall bank and banking system risk levels, which can assist bank management, bank regulators, Sovereigns, rating agencies, and investors to make better informed and proactive risk management and investment decisions.     

Estimating Default Probabilities Implicit in Commercial Mortgage Backed Securities (CMBS)

This paper uses a structural credit risk model, providing an analytical formula to estimate default probabilities implicit in commercial mortgage backed security prices. Empirical studies of CMBS default have focused on the probability of default depending on loan characteristics at the origination and market indices. Recent studies show that unobservable current loan-to-value (LTV) ratio is a key state variable driving default. We update this variable using Real Estate Investment Trust (REIT) property-type indices over time. Later, we employ first passage time approach to study CMBS default using implied LTV.

Bank-firm relationship and credit risk: An analysis on Tunisian firms

This paper analyses the impact of the intensity and length of bank-firm lending relationship on Tunisian banks’ credit risk over the period 2001–2012. The sample includes 494 bank-firm relationships for 383 firms. By applying probit and ordered probit models, our results indicate that firms which engage in intense relationships with banks are less likely to encounter a credit default. In addition, these firms exhibit a higher loan quality. However, no evidence has been found for the impact of the relationship length on credit risk. Further, the findings show that private banks, unlike public financial institutions, take advantage of their close lending relationships with borrowers to mitigate information asymmetry and therefore improve their loans portfolio quality.     

A simulation study of Basel II expected loss distributions for a portfolio of credit cards

Credit scoring models have been used traditionally as the basis of decisions to reject or accept credit applications. They are also used to categorize applicants or existing accounts into risk groups. Based on estimates of probability of default (PD), the risk groups may seem well separated. However, by considering distributions on risk elements such as model estimation uncertainty, exposure at default and loss given default, a simulation approach is used to compute Basel II expected loss distributions for a portfolio of credit cards. These show that discrimination between risk groups is not as clear as is immediately suggested simply by PD estimates. Based on these distributions, we also show that measuring extreme credit risk with Value at Risk can lead to considerable underestimation if distributions on these risk elements are not entered into the computation.     

Loan Portfolio Swaps and Optimal Lending

Theories on loan portfolio swap hedging are based on a portfolio-choice approach. This paper presents an alternative: a firm-theoretic model for bank behavior with loan portfolio swaps. Our paper derives the optimal loan rate and rate-taking loan amount of the banks portfolio, and relates them to the market loan rate, counterparty loan rate, swap default risk, capital-to-deposits ratio, and deposit insurance. We find that in the bilateral default risk approach, the comparative static results are generated by four factors: the banks risk magnitude about the equity market value, loan composition in the swap contract, the substitution effect in the loan portfolio, and the income effect from the swap transaction. The results imply that changes in the payoff asymmetry in the event of swap default and the banks regulatory parameters have a direct effect on the banks loan portfolio for lending and swap transactions.We would like to thank two anonymous referees for helpful comments and advice.