Risk structure of interest rates: an empirical analysis for Deutschemark‐denominated bonds

This paper empirically studies the risk structure of interest rates for Deutschemark‐denominated bonds. For this purpose, we estimate term structures of interest rates using the parsimonious fitting function of Nelson and Siegel (1987) for virtually risk free Government bonds and five different rating categories classified by Moody's ratings (Aaa, Aa, A, Baa, Ba). The sample period covers the time interval from July 1990 to December 1996. We investigate the pricing errors resulting from our estimation procedure and analyse credit spreads over the term structure of Government bonds.     

国有商业银行信贷评级模型的构建及实证检验

信贷评级是信贷风险管理的前提,目前我国国有商业银行都采用这一方式管理信贷风险.本文在对国有商业银行当前信用评级方法存在问题和国内外相关研究成果进行分析的基础上,提出了构建国有商业银行内部信用评级模型,提高信贷风险管理水平的建议.作者利用贷款历史数据,通过因子分析和聚类分析等方法构建内部信用评级模型;通过因子分析方法构建的模型使评级指标体系更加科学、合理,避免了反映风险信息的冗余与遗漏;聚类分析使评级模型直接与违约概率挂钩,度量风险的准确性进一步提高.论文最后对模型进行了实证分析,使其有效性得到了检验.     

资产证券化信用评级制度与系统性风险分析

资产证券化的复杂性和高度杠杆化加剧了投资者与发行人之间的信息不对称问题,信用评级制度作为信息披露手段,在减轻信息不对称、促进风险资产定价和保护投资者利益等方面发挥着重要作用.但若缺乏有效的制度保障,资产证券化信用评级过程中隐含的对系统性风险的累积和传导危险则会对金融系统稳定产生负面作用.我国信用评级制度缺乏良好的法律监管环境和充分的市场竞争,难以支持资产证券化产品的多样化发展和规模的快速扩大趋势.对此,需从宏观审慎监管框架的确立、信用评级监管权力的统一和制度完善以及评级行业的市场化推进等方面完善信用评级制度.     

Modeling severity risk under PD–LGD correlation

In this article, a generic severity risk framework in which loss given default (LGD) is dependent upon probability of default (PD) in an intuitive manner is developed. By modeling the conditional mean of LGD as a function of PD, which also varies with systemic risk factors, this model allows an arbitrary functional relationship between PD and LGD. Based on this framework, several specifications of stochastic LGD are proposed with detailed calibration methods. By combining these models with an extension of CreditRisk+, a versatile mixed Poisson credit risk model that is capable of handling both risk factor correlation and PD–LGD dependency is developed. An efficient simulation algorithm based on importance sampling is also introduced for risk calculation. Empirical studies suggest that ignoring or incorrectly specifying severity risk can significantly underestimate credit risk and a properly defined severity risk model is critical for credit risk measurement as well as downturn LGD estimation.     

基于企业规模的信贷决策支持：运用外部信用评级的一个试验

中小企业作为一个整体,需要根据企业的风险度来确定对它的信贷规模,风险度以企业信用级别来表示,信用级别通过外部评级来确定。为此本文介绍了一个外部评级体系,利用一个地区的评级样本——59家中小企业,反映外部评级体系对中小企业风险度的独特揭示,在此基础上建立了一个对中小企业的、基于信用级别的最高授信额度测算模型。     

Determinants of Sovereign Eurobonds Yield Spread

We examine the determinants of sovereign Eurobond spread at issuance covering 1991–2000. The results of the regression models showed that yield spread increases with maturity, issue size and gross fees and decreases with credit rating and the number of managers. Higher‐grade issuers also pay a relatively higher spread to borrow long‐term funds and for smaller issues. The findings are consistent with the notion of a term structure 'liquidity premium.' Low‐grade issuers pay a higher spread than better‐rated countries. However, low‐grade countries pay high spread for larger funds. Credit rating is found to provide additional information in explaining the spread on sovereign Eurobonds beyond that provided by macroeconomic variables.     

The ordered qualitative model for credit rating transitions

Information on the expected changes in credit quality of obligors is contained in credit migration matrices which trace out the movements of firms across ratings categories in a given period of time and in a given group of bond issuers. The rating matrices provided by Moody's, Standard & Poor's and Fitch became crucial inputs to many applications, including the assessment of risk on corporate credit portfolios (CreditVar) and credit derivatives pricing. We propose a factor probit model for modeling and prediction of credit rating matrices that are assumed to be stochastic and driven by a latent factor. The filtered latent factor path reveals the effect of the economic cycle on corporate credit ratings, and provides evidence in support of the PIT (point-in-time) rating philosophy. The factor probit model also yields the estimates of cross-sectional correlations in rating transitions that are documented empirically but not fully accounted for in the literature and in the regulatory rules established by the Basle Committee.     

On long-term credit risk assessment and rating: towards a new set of models

Institutional investors are supposed to assess credit risk by using a combination of quantitative information such as option models and qualitative assessments. Although option models can be easily constructed, they are not so suitable for the assessment of long-term credit risk that is required by institutional investors. This is mainly because the probability of bankruptcy varies so widely depending on the timing of assessment. We propose a new set of assessment models for long-term credit risk which does not necessarily use stock prices and may incorporate business cycles. The new grand model consists of the two pillars: a long-term cash flow prediction model and a credit risk spread assessment model. The calculated values derived from these models are effectively usable for reasonable calculation of risk spreads. It is quite interesting to see that our investigation indicates that rating bias may exist in the credit risk assessment of the market.     

Analyzing the impact of credit migration in a portfolio setting

Credit migration is an essential component of credit portfolio modeling. In this paper, we outline a framework for gauging the effects of credit migration on portfolio risk measurements. For a typical loan portfolio, we find credit migration can explain as much as 51% of volatility and 35% of economic capital. We compare through-the-cycle migration effects, implied by agency rating transitions, with point-in-time migration, implied by EDF? (Expected Default Frequency) transitions, and find that migration of point-in-time credit quality accounts for a greater fraction of total portfolio risk when compared with through-the-cycle dynamics. In a stylized analytic setting, we show that, when controlling for PD term structure effects, higher likelihood of moving away from the current credit state does not necessarily imply greater risk. Finally, we review methods for generating high-frequency transition matrices, needed for analyzing instruments with cash flows or contingencies whose frequencies are asynchronous to an available transition matrix. We further demonstrate that the naïve application of such methods can result in material deviations to portfolio analytics.     

Modeling of Contagious Credit Events and Risk Analysis of Credit Portfolios

We present a new model of the occurence of credit events such as rating changes and defaults for risk analyses of some portfolio credit derivatives. The framework of our model is based on a so-called top-down approach. Specifically, we first consider modeling the point process of each type of credit event in the whole economy using a self-exciting intensity process. Next, we characterize the point processes of credit events in the underlying sub-portfolio using random thinning processes specified by the distribution of credit ratings in the sub-portfolio. One of the main features of our model is that the model can capture credit risk contagion simultaneously among several credit portfolios. We present a credit event simulation algorithm based on our model and illustrate an application of the model to risk analyses of loan portfolios.     

Credit cycles and macro fundamentals

We use an intensity-based framework to study the relation between macroeconomic fundamentals and cycles in defaults and rating activity. Using Standard and Poor's U.S. corporate rating transition and default data over the period 1980–2005, we directly estimate the default and rating cycle from micro data. We relate this cycle to the business cycle, bank lending conditions, and financial market variables. In line with earlier studies, the macro variables appear to explain part of the default cycle. However, we strongly reject the correct dynamic specification of these models. The problem is solved by adding an unobserved dynamic component to the model, which can be interpreted as an omitted systematic credit risk factor. By accounting for this latent factor, many of the observed macro variables loose their significance. There are a few exceptions, but the economic impact of the observed macro variables for credit risk remains low. We also show that systematic credit risk factors differ over transition types, with risk factors for downgrades being noticeably different from those for upgrades. We conclude that portfolio credit risk models based only on observable systematic risk factors omit one of the strongest determinants of credit risk at the portfolio level. This has obvious consequences for current modeling and risk management practices.     

An Estimation Model for the Term Structure of Yield Spread

An estimation model for term structure of yield spread has become an extremely important subject to evaluate securities with default risk. By Duffie and Singleton model, yield spread was explained by two factors, namely collection rate and default probability. An estimation of the collection rate is given from historical earnings data, but estimation of default probability is known to be a remaining problem.There are some approaches to express default probability. One of them is to describe it through hazard process, and the other is to represent it by risk neutral transition probability matrix of credit-rating class. Some models that use Gaussian type hazard process or Vasicek type hazard process have already constructed.An advantage of evaluation using a rating transition probability matrix is that it is easy to obtain an image of movement of the credit-rating class. We do not need to show the calculation basis of the threshold or an assumption for distribution of prospective yield spread. But the model that uses the risk neutral transition probability matrix has not established yet, because of the computational difficulty required to estimate large number of the parameters.At first, for the purposes of this article, we will estimate the term structure of credit spreads results from the possibility of future defaults. It is assumed that credit risk is specified as a discrete-state Markov chain. And we construct a model which can be used to estimate the baseline transition matrix of the credit-rating class, risk-adjusting factors, industrial drift factors, corporate drift factors and recovery ratio, from yield spreads for individual bond. This enables us to compute the implied term structure from market data. We are capable of computing the implied term structure from market date by this process. Next, we will provide a valuation model for the term structure of yield spread.     

The Original Maturity of Corporate Bonds: The Influence of Credit Rating,Asset Maturity,Security, and Macroeconomic Conditions

We examine the determinants of the new issue maturity of corporate bonds. As credit rating decreases, new bond issues have longer maturities, but substantial variation in maturity within each rating class remains. We seek to explain the variation of new issue maturity within credit classes. We find that asset maturity, security covenants, and macroeconomic conditions influence the new issue maturity of bonds within rating categories.     

Credit Ratings and Bank Affiliation to Financial Holding Companies: Effects of Government Ownership and Financial Crisis

This study compares credit ratings between FHC affiliated banks and independent banks using Taiwan bank and FHC data. The results show banks that join Insurance- or Security-FHCs obtain better ratings than those that join Bank-FHCs. Second, banks that join FHCs with higher activity diversification can obtain better credit ratings. Third, joining government-owned FHCs enhances bank credit ratings and mitigates bank default risk compared to joining non-government-owned FHCs. Fourth, prior to the financial crisis, banks joining FHCs can obtain better credit ratings and reduce the cost of debt. However, during the financial crisis, rating agencies stopped regarding banks joining privately owned bank-based FHCs as risk diversification and assigning better credit ratings on this basis.     

信用评级在中国债券市场的影响力

信用评级能够为市场提供风险信息从而增强市场对企业的约束,因此对资本市场的健康发展起着重要的作用。在中国,评级市场刚刚起步。本文利用2007至2009年间发行的企业债数据,用实证的方法研究本土信用评级在债券市场上的影响力。我们建立真实利息成本(TIC)回归模型,以信用评级和其他相关因素对债券的真实利息成本进行计量回归,分析信用评级在一级市场中对债券发行成本的影响。我们发现债券评级和主体评级分别对发行成本具有解释力,但债券评级对发行成本的影响力大于主体评级。     

On the Term Structure of Default Premia in the Swap and LIBOR Markets

Existing theories of the term structure of swap rates provide an analysis of the Treasury–swap spread based on either a liquidity convenience yield in the Treasury market, or default risk in the swap market. Although these models do not focus on the relation between corporate yields and swap rates (the LIBOR–swap spread), they imply that the term structure of corporate yields and swap rates should be identical. As documented previously (e.g., in Sun, Sundaresan, and Wang (1993)) this is counterfactual. Here, we propose a model of the default risk imbedded in the swap term structure that is able to explain the LIBOR–swap spread. Whereas corporate bonds carry default risk, we argue that swap contracts are free of default risk. Because swaps are indexed on "refreshed"-credit-quality LIBOR rates, the spread between corporate yields and swap rates should capture the market's expectations of the probability of deterioration in credit quality of a corporate bond issuer. We model this feature and use our model to estimate the likelihood of future deterioration in credit quality from the LIBOR–swap spread. The analysis is important because it shows that the term structure of swap rates does not reflect the borrowing cost of a standard LIBOR credit quality issuer. It also has implications for modeling the dynamics of the swap term structure.     

Sovereign credit ratings and bank funding cost: Evidence from Africa

This paper aims to examine the relationship between sovereign credit ratings and funding costs of banks and also the relationship between sovereign credit ratings. Using over 300 banks operating in Africa from 2006 to 2012, the study investigates sovereign ratings’ impact on funding cost. The long term domestic sovereign ratings announced by Fitch and Standard & Poor’s during the period under study were used. The panel made use of Generalized Method of Moments estimation strategy for funding cost. The findings of the study indicate that sovereign ratings upgrades have an inverse and statistically significant relationship with funding costs. The findings suggest that sovereign rating upgrades makes it easier for banks to access funds from the capital and global market at a cheaper cost compared to rating downgrades. The study recommends and encourages emerging economies to use the services provided by credit rating agencies since these agencies may help improve accessibility of funds in the international markets by banks. It is recommended that sovereign rating should be considered as a supplement and not a substitute to our own perceived judgement and research.     

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.     

Default and Recovery Risk Dependencies in a Simple Credit Risk Model

This paper provides evidence for the relationship between credit quality, recovery rate, and correlation. The paper finds that rating grade, rating shift, and macroeconomic factors provide a highly significant explanation for default risk and recovery risk of US bond issues. The empirical data suggest that default and recovery processes are highly correlated. Therefore, a joint approach is required for estimating time‐varying default probabilities and recovery rates that are conditional on default. This paper develops and applies such a model.     

Tempered stable structural model in pricing credit spread and credit default swap

In this paper, we explore the features of a structural credit risk model wherein the firm value is driven by normal tempered stable (NTS) process belonging to the larger class of Lévy processes. For the purpose of comparability, the calibration to the term structure of a corporate bond credit spread is conducted under both NTS structural model and Merton structural model. We find that NTS structural model provides better fit for all credit ratings than Merton structural model. However, it is noticed that probabilities of default derived from the calibration of the term structure of a bond credit spread might be overestimated since the bond credit spread could contain non-default components such as illiquidity risk or asymmetric tax treatment. Hence, considering CDS spread as a reflection of the pure credit risk for the reference entity, we calibrate it in order to obtain more reasonable probability of default and obtain valid results in calibration of the market CDS spread with NTS structural model.