Systemic risk contributions: A credit portfolio approach

We put forward a framework for measuring systemic risk and attributing it to individual banks. Systemic risk is coherently measured as the expected loss to depositors and investors when a systemic event occurs. The risk contributions are calculated so as to ensure a full risk allocation among institutions. Applying our methodology to a panel of 54–86 of the world’s major commercial banks for a 13-year time span with monthly frequency not only allows us to closely match the list of G-SIBs; we can also use individual risk contributions to compute bank-specific surcharges: systemic capital charges as well as countercyclical buffers. We therefore address both dimensions of systemic risk – cross-sectional and time-series – in a single integrated approach. As the analysis of risk drivers confirms, the main focus of macroprudential supervision should be on a solid capital base throughout the financial cycle and de-correlation of banks’ asset values.     

Risk factor contributions in portfolio credit risk models

Determining contributions to overall portfolio risk is an important topic in risk management. For positions (instruments and sub-portfolios), this problem has been well studied, and a significant theory built, around the calculation of marginal contributions. We consider the problem of determining the contributions to portfolio risk of risk factors. This cannot be addressed through an immediate extension of techniques for position contributions, since the portfolio loss is a nonlinear function of the risk factors. We employ the Hoeffding decomposition of the portfolio loss into a sum of terms depending on the factors. This decomposition restores linearity, but includes terms arising from joint effects of groups of factors. These cross-factor terms provide information to risk managers, since they can be viewed as best hedges of the portfolio loss involving instruments of increasing complexity. We illustrate the technique on multi-factor portfolio credit risk models, where systematic factors represent industries, geographical sectors, etc.     

Applying a factor copula to value basket credit linked notes with issuer default risk

This paper explores a reasonable coupon rate for basket credit linked notes (BCLN) with issuer default risk. Based on the one factor Gaussian copula model, this paper proposes three methods of incorporating issuer default into BCLN pricing. Numerical results indicate that issuer default risk impacts BCLN coupon rate. Furthermore, coupon rate differs with changes in correlation structure among the three methods. One of the three methods is ultimately identified as the most suitable.     

个人信用评分有力推进信贷风险管理转型

随着我国全面建设小康社会进程的加速,社会财富不断增加,个人客户对银行的个人业务提出了更多需求,进一步拉动了个人金融服务的增长.由于个人业务具有笔数多、单笔金额小,数据丰富的特点,所以要对其采用精细化、智能化、自动化的管理模式.然而长期以来,我国商业银行个人业务的经营管理方式一直比较粗放.中国人民银行最新研发的全国个人信用评分,可以对个人客户在未来一定时期内的违约概率进行评估和预测.它可以有效防范风险,为商业银行实现个人信贷风险管理转型提供先进的风险管理技术支持.     

基于市场定价测算信用评级指标权重

一般而言,投资者会参考一系列指标来综合评估企业债券的信用水平,合理设定这些指标的权重是相对准确地衡量债券信用水平的关键。文章基于有效市场假定,在分类梳理备选信用指标的基础上,将由加权信用指标计算的债券信用估值差异与债券实际收益率差异进行拟合,以此确定最优的信用指标权重组合,以期为简要分析企业信用资质和债券定价判断提供一个参考。     

Granularity adjustment for mark-to-market credit risk models

The impact of undiversified idiosyncratic risk on value-at-risk and expected shortfall can be approximated analytically via a methodology known as granularity adjustment (GA). In principle, the GA methodology can be applied to any risk-factor model of portfolio risk. Thus far, however, analytical results have been derived only for simple models of actuarial loss, i.e., credit loss due to default. We demonstrate that the GA is entirely tractable for single-factor versions of a large class of models that includes all the commonly used mark-to-market approaches. Our approach covers both finite ratings-based models and models with a continuum of obligor states. We apply our methodology to CreditMetrics and KMV Portfolio Manager, as these are benchmark models for the finite and continuous classes, respectively. Comparative statics of the GA reveal striking and counterintuitive patterns. We explain these relationships with a stylized model of portfolio risk.     

Copula-based factor model for credit risk analysis

A standard quantitative method to assess credit risk employs a factor model based on joint multivariate normal distribution properties. By extending the one-factor Gaussian copula model to produce a more accurate default forecast, this paper proposes the incorporation of a state-dependent recovery rate into the conditional factor loading and to model them sharing a unique common factor. The common factor governs the default rate and recovery rate simultaneously, implicitly creating their association. In accordance with Basel III, this paper shows that the tendency toward default during a hectic period is governed more by systematic risk than by idiosyncratic risk. Among those considered, the model with random factor loading and a state-dependent recovery rate is shown to be superior in terms of default prediction.     

Vector-valued coherent risk measures

We define (d,n)-coherent risk measures as set-valued maps from into satisfying some axioms. We show that this definition is a convenient extension of the real-valued risk measures introduced by Artzner et al. [2]. We then discuss the aggregation issue, i.e., the passage from valued random portfolio to valued measure of risk. Necessary and sufficient conditions of coherent aggregation are provided.Received: February 2004, Mathematics Subject Classification (2000): 91B30, 46E30JEL Classification: D81, G31     

Counterparty credit risk and the credit default swap market

Counterparty credit risk has become one of the highest-profile risks facing participants in the financial markets. Despite this, relatively little is known about how counterparty credit risk is actually priced. We examine this issue using an extensive proprietary data set of contemporaneous CDS transaction prices and quotes by 14 different CDS dealers selling credit protection on the same underlying firm. This unique cross-sectional data set allows us to identify directly how dealers' credit risk affects the prices of these controversial credit derivatives. We find that counterparty credit risk is priced in the CDS market. The magnitude of the effect, however, is vanishingly small and is consistent with a market structure in which participants require collateralization of swap liabilities by counterparties.     

Up and down credit risk

This paper discusses the main modeling approaches that have been developed for handling portfolio credit derivatives, with a focus on the question of hedging. In particular, the so-called top, top down and bottom up approaches are considered. We give some mathematical insights regarding the fact that information, namely the choice of a relevant model filtration, is the major modeling issue. In this regard, we examine the notion of thinning that was recently advocated for the purpose of hedging a multi-name derivative by single-name derivatives. We then illustrate by means of numerical simulations (semi-static hedging experiments) why and when the portfolio loss process may not be a ‘sufficient statistic’ for the purpose of valuation and hedging of portfolio credit risk.     

信用风险模型探究

在经济金融全球化的背景下，我国银行业的开放力度正在逐步加大。如何有效防范金融风险，是我国银行业参与国际金融活动面临的重大课题，新巴塞尔协议反映了当今先进的风险管理技术和监管理念与实践，为商业银行建立风险管理体系指明了方向。其核心内容是全面提高风险管理水平，准确识别、计量和控制风险。     

Correlation in credit risk changes

The current economic climate makes understanding credit risk correlation particularly important. After allowing for a comprehensive set of observable firm-specific, industry, market, and macroeconomic factors, there is an economically significant co-movement in credit default swap spreads that remains to be explained. Including a time dummy completely accounts for the remaining co-movement, confirming the existence of a systematic component that has been previously unaccounted for. Our findings suggest that it may be important to consider unobservable risk factor(s) in credit risk models.     

Asset financing with credit risk

This paper develops a model for the unified valuation of all forms of real asset financing, such as bank loans, leases, securitization vehicles, and credit guarantees, secured by assets that generate a stochastic service flow to the operator, or a rental stream to the lessor, and depreciate over a finite economic life to their scrap value. Examples include mobile equipment, such as aircraft, railroad equipment, ships, trucks and trailers, as well as energy generation assets, heavy factory equipment and construction equipment. In the event of obligor default, after a repossession delay and incurring costs of repossession, maintenance, re-marketing and re-deployment, the lender repossesses the asset and sells it on the secondary market and is, thus, subject to the risk of decline in the market value of the asset. The model we develop in this paper treats all forms of asset financing in a unified fashion as contingent claims on the collateral asset and the credit of the borrower. As an application, we estimate the collateral asset model on historical secondary market data for aircraft values and calibrate the financing model to the Enhanced Equipment Trust Certificates (EETCs) issued in 2007 by Continental Airlines and secured by a fleet of new aircraft. We then apply the calibrated model to value private market financing, including bank loans, leases, and credit guarantees, consistently with the capital market financing, and assess the impact of repossession delays on credit spreads. This analysis leads to a policy insight suggesting that bankruptcy laws limiting asset repossession delays lead to lower costs of asset financing.     

Information risk and credit contagion

This paper demonstrates a positive relationship between information risk and the credit contagion effect. We use abnormal changes in the Credit Default Swaps (CDS) spreads to measure the contagion effect, and the dispersion of analyst forecasts as a proxy for information risk. We find that firms with higher information risk suffer a greater contagion effect that occurs in advance to the credit default events. This finding is robust under controls of key firm-specific characteristics and general condition of stock and credit markets.     

Fast simulations in credit risk

We consider the problem of simulating tail loss probabilities and expected losses conditioned on exceeding a large threshold (expected shortfall) for credit portfolios. Our new idea, called the geometric shortcut, allows an efficient simulation for the case of independent obligors. It is even possible to show that, when the average default probability tends to zero, its asymptotic efficiency is higher than that of the naive algorithm. The geometric shortcut is also useful for models with dependent obligors and can be used for dependence structures modeled with arbitrary copulae. The paper contains the details for simulating the risk of the normal copula credit risk model by combining outer importance sampling with the geometric shortcut. Numerical results show that the new method is efficient in assessing tail loss probabilities and expected shortfall for credit risk portfolios. The new method outperforms all known methods, especially for credit portfolios consisting of weakly correlated obligors and for evaluating the tail loss probabilities at many thresholds in a single simulation run.     

Sustainability and sovereign credit risk

The study investigates the impact of Environmental, Social, and Governance (ESG) ratings on sovereign credit risk. The study measures sovereign credit risk using a market-based, structural and an analyst-based approach, while ESG scores are obtained from three different rating agencies. The contributions of this paper are multifold. First, we discover that higher sustainability performance at the corporate level significantly decreases market-based (CDS spreads) and structural (Distance-to-default) sovereign credit risk but has no consistent impact on analyst-based (Credit ratings) sovereign credit risk measure. Second, by expanding our research to include the concept of financial materiality based on the SASB materiality map, we break down and highlight the sustainability themes that require the most attention at the sovereign level and those that can affect the credit health of countries. Third, we demonstrate that the relationship between sustainability and sovereign credit risk varies across ESG rating providers, supporting the widespread belief that sustainability metrics lack standardization and are difficult to compare across providers.     

Exploring the components of credit risk in credit default swaps

In this paper, we test the influence of various fundamental variables on the pricing of credit default swaps. The theoretical determinants that are important for pricing credit default swaps include the risk-free rate, industry sector, credit rating, and liquidity factors. We suggest a linear regression model containing these different variables, especially focusing on liquidity factors. Unlike bond spreads which have been shown to be inversely related to liquidity (i.e., the greater the liquidity, the lower the spread), there is no a priori reason that the credit default swap spread should exhibit the same relationship. This is due to the economic characteristics of a credit default swap compared to a bond. Our empirical result shows that all the fundamental variables investigated have a significant effect on the credit default swap spread. Moreover, our findings suggest that credit default swaps that trade with greater liquidity have a wider credit default swap spread.     

Rollover risk and credit risk under time-varying margin

For a firm financed by a mixture of collateralized (short-term) debt and uncollateralized (long-term) debt, we show that fluctuations in margin requirements, reflecting funding liquidity shocks, lead to increasing the firm’s default risk and credit spreads. The severity with which a firm is hit by increasing margin requirements highly depends on both its financing structure and debt maturity structure. Our results imply that an additional premium should be added when evaluating debt in order to account for rollover risks, especially for short-matured bonds. In terms of policy implications, our results strongly indicate that regulators should intervene fast to curtail margins in crisis periods and maintain a reasonably low margin level in order to effectively prevent creditors’ run on debt.