Corporate bond default risk: A 150-year perspective

We study corporate bond default rates using an extensive new data set spanning the 1866-2008 period. We find that the corporate bond market has repeatedly suffered clustered default events much worse than those experienced during the Great Depression. For example, during the railroad crisis of 1873-1875, total defaults amounted to 36% of the par value of the entire corporate bond market. Using a regime-switching model, we examine the extent to which default rates can be forecast by financial and macroeconomic variables. We find that stock returns, stock return volatility, and changes in GDP are strong predictors of default rates. Surprisingly, however, credit spreads are not. Over the long term, credit spreads are roughly twice as large as default losses, resulting in an average credit risk premium of about 80 basis points. We also find that credit spreads do not adjust in response to realized default rates.     

An Empirical Comparison of Credit Spreads between the Bond Market and the Credit Default Swap Market

This paper compares the pricing of credit risk in the bond market and the fast-growing credit default swap (CDS) market. The cointegration test confirms that the theoretical parity relationship between the two credit spreads holds as a long-run equilibrium condition. Nevertheless, substantial deviation from the parity can arise in the short run. The panel data study and the VECM analysis both suggest that the deviation is largely due to the higher responsiveness of CDS premia to changes in credit conditions. Moreover, it exhibits a certain degree of persistence in that only 10% of price discrepancies can be removed within a business day.     

Credit risk measurement: Developments over the last 20 years

This paper traces developments in the credit risk measurement literature over the last 20 years. The paper is essentially divided into two parts. In the first part the evolution of the literature on the credit-risk measurement of individual loans and portfolios of loans is traced by way of reference to articles appearing in relevant issues of the Journal of Banking and Finance and other publications. In the second part, a new approach built around a mortality risk framework to measuring the risk and returns on loans and bonds is presented. This model is shown to offer some promise in analyzing the risk-return structures of portfolios of credit-risk exposed debt instruments.     

信用评级中的违约率、违约概率研究

信用评级是对个人、经济体与金融工具履行各种经济承诺的能力及可信任程度的综合评价，本文通过对KMV评级模型的研究，指出在信用评级中的关键指标——“违约率和违约概率”在评级中的重要意义。     

Credit Spreads in Illiquid Markets: Model and Implementation

This paper presents a methodology for estimating a family of credit spread term structures in a market with few transactions. The authors propose partitioning the market into risk classes and modeling credit spread term structures for each risk class using a multifactor Vasicek model with some common and some risk class-specific factors. The approach uses information on the cross section and time series of corporate bonds in all the risk classes to estimate the term structure of credit spreads in each risk class. The model is jointly estimated using an extended Kalman filter and implemented using Chilean corporate and government bonds.     

Determinants of yield spread dynamics: Euro versus US dollar corporate bonds

This paper presents a systematic comparison between the determinants of euro and US dollar yield spread dynamics. The results show that US dollar yield spreads are significantly more affected by changes in the level and the slope of the default-free term structure and the stock market return and volatility. Surprisingly, euro yield spreads are strongly affected by the US (and not the euro) level and slope. This confirms the dominance of US interest rates in the corporate bond markets. Interestingly, I find that liquidity risk is higher for US dollar corporate bonds than euro corporate bonds. For both regions, the effect of changes in the bid-ask spread is mainly significant during periods of high liquidity risk. Finally, the results indicate that the credit cycle as measured by the region-specific default probability significantly increases US yield spreads. This is not the case for euro yield spreads.     

Credit derivatives and loan pricing

This paper examines the relation between the new markets for credit default swaps (CDS) and banks’ pricing of syndicated loans to US corporates. We find that changes in CDS spreads have a significantly positive coefficient and explain about 25% of subsequent monthly changes in aggregate loan spreads during 2000–2005. Moreover, when compared to traditional explanatory factors, they turn out to be the dominant determinant of loan spreads. In particular, they explain loan rates much better than same rated bonds. This suggests that CDS prices contain, beyond general credit risk, to a substantial extent information relevant for bank lending. We also find that, over time, new information from CDS markets is faster incorporated into loans, but information from other markets is not. Overall, our results indicate that the markets for CDS have gained an important role for banks.     

Credit Derivatives in an Affine Framework

An efficient method for valuing credit derivatives based on three entities is developed in an affine framework. This includes interdependence of market and credit risk, joint credit migration and counterparty default risk of three firms. As an application we provide closed form expressions for the joint distribution of default times, default correlations, and default swap spreads in the presence of counterparty default risk. Vienna Institute of Finance is funded by WWTF (Vienna Science and Technology Fund).     

国家主权信用评级质量检验方法研究

国家主权信用评级对当今国际经济和金融运行有着极为重要的影响力。但是,与其地位不相符的是,评级机构的评级结果事后多次被证明准确性和前瞻性较差。事先缺乏预警而事后大幅降级,甚至对加剧危机起到了推波助澜的作用。本文从国家主权信用评级质量的检验方法入手,系统分析了违约率和迁移率等传统方法在检验评级结果起到的作用及其不足,给出了检验评级质量的一般方法,并验证了该评级检验方法的科学性和准确性。     

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.     

Selecting credit rating models: a cross-validation-based comparison of discriminatory power

In commercial banking, various statistical models for corporate credit rating have been theoretically promoted and applied to bank-specific credit portfolios. In this paper, we empirically compare and test the performance of a wide range of parametric and nonparametric credit rating model approaches in a statistically coherent way, based on a ‘real-world’ data set. We repetitively (k times) split a large sample of industrial firms’ default data into disjoint training and validation subsamples. For all model types, we estimate k out-of-sample discriminatory power measures, allowing us to compare the models coherently. We observe that more complex and nonparametric approaches, such as random forest, neural networks, and generalized additive models, perform best in-sample. However, comparing k out-of-sample cross-validation results, these models overfit and lose some of their predictive power. Rather than improving discriminatory power, we perceive their major contribution to be their usefulness as diagnostic tools for the selection of rating factors and the development of simpler, parametric models.

经济学层面上的道德、信任、信用与征信

道德、信任、信用与征信这四个概念被相继引入经济学研究中经历了一个渐进的过程,四者之间存在相辅相成、共同促进、相互影响的作用与反作用的关系.道德规范是形成全社会共同遵守的价值观的基础,信任是除物质资本和人力资本之外决定一个国家经济增长和社会进步的主要社会资本,信用是商业交易的前提,是维系社会经济正常关系的纽带,而征信是对受信人信用状况的一个全面了解和高度概括,据此建立的奖惩机制能为良好的社会信用状态形成打下基础.     

Diversification,Fee Income,and Credit Union Risk

Australian credit unions (CUs) have introduced new fee generating activities, increased transaction fees on existing products, and diversified into residential mortgages. Using DeYoung and Roland’s degree of total leverage and other risk measures we find that more diversified CUs have lower risk and return. CUs that increase the revenue share of transaction fees (matched by a lower share of personal loan interest) increase risk and reduce returns while those that increase residential lending revenues reduce both risk and returns. There is also evidence of scale related economies with risk decreasing and returns increasing with CU size.JEL classification: G21Disclaimer: The views and opinions in this paper are those of the authors and do not necessarily reflect those of APRA.     

Recent Developments in Credit Markets

We summarize recent developments in the credit derivative markets. We show the role of dependence between individual debtors in portfolio derivatives in a study of implied correlation. The risk of changing dependence structures between stock and bond markets becomes evident in an example of capital structure arbitrage. How credit derivatives can introduce new risks is illustrated by the example of “overlay” in basket derivatives.     

构筑我国商业银行现代化信贷风险管理体系

文章从完善信贷管理组织结构入手 ,遵循系统性原则、权责一致原则和效率原则 ,建议对我国商业银行内部信贷组织构架应作具体的调整 :建立“信贷政策决策委员会”、完善“贷款审批制”、建立“信贷执行官负责制”和“成立风险检查部门”。在此基础上加强其他四项措施的落实 ,从而对我国商业银行信贷风险就能得到有效的控制     

短期融资券信用价差分析

短期融资券的信用价差初具分化趋势,不同评级机构给出同一信用等级的信用价差不同,说明各评级机构在评级标准和评级理念的把握上存在一定的差异。A-1 、 A-1信用等级之间没有形成明显不同的信用价差影射区间。短期融资券的发行利率的大幅上升主要是由于一级市场收益率微薄、流动性风险加剧以及作为定价基准的央行票据利率不断上调等直接原因造成的。     

信用风险水平与宏观经济变量的实证研究——基于中国、美国、日本部分银行的比较分析

基于1999～2007年中国、美国和日本部分银行的不良贷款率数据,本文对影响银行信用风险的宏观经济因素进行了实证研究和比较分析。结果表明:(1)中国的银行信用风险水平与失业率呈现显著的负相关关系;(2)表面上美国的银行信用风险水平极低,而且不受宏观经济变量波动的影响,但是实际上其风险被金融衍生工具隐藏并积累起来;(3)日本的银行信用风险水平与CPI呈现显著的负相关关系。最后本文提出了几点建议。     

个人信用风险评价系统的统计量表法

本文围绕信用风险统计量表构建的评价测算系统,概要阐述其构造方法与系统运行机理,对其中基本数据结构与算法体系作出明确描述,并对系统开发设计要点给予解析说明。     

基于Logistic模型的单个信用资产违约概率预测

在信用风险管理领域,由于中国商业银行信贷数据只满足Logistic模型的要求,因而预测单个信用资产违约率只能以Logistic模型为主线建模。以中国某商业银行1999~2005年的信贷数据为样本,实证分析得出,企业本身、宏观经济、地区及行业四方面因素对企业违约概率存在显著相关性。通过以上述四因素为变量,所构建的预测电力、公路、城镇建设三个行业信用资产违约概率的Logistic模型分析与预测单个信用资产违约的结果来看,四要素模型对中国商业银行的信用风险管理具有参照价值。