Showing papers on "Credit risk published in 2001"

Term Structures of Credit Spreads with Incomplete Accounting Information

Abstract: We study the implications of imperfect information for term structures of credit spreads on corporate bonds. We suppose that bond investors cannot observe the issuer's assets directly, and receive instead only periodic and imperfect accounting reports. For a setting in which the assets of the firm are a geometric Brownian motion until informed equityholders optimally liquidate, we derive the conditional distribution of the assets, given accounting data and survivorship. Contrary to the perfect-information case, there exists a default-arrival intensity process. That intensity is calculated in terms of the conditional distribution of assets. Credit yield spreads are characterized in terms of accounting information. Generalizations are provided.

Systemic Risk in Financial Systems

Abstract: We consider default by firms that are part of a single clearing mechanism. The obligations of all firms within the system are determined simultaneously in a fashion consistent with the priority of debt claims and the limited liability of equity. We first show, via a fixed-point argument, that there always exists a "clearing payment vector" that clears the obligations of the members of the clearing system; under mild regularity conditions, this clearing vector is unique. Next, we develop an algorithm that both clears the financial system in a computationally efficient fashion and provides information on the systemic risk faced by the individual system firms. Finally, we produce qualitative comparative statics for financial systems. These comparative statics imply that, in contrast to single-firm results, even unsystematic, nondissipative shocks to the system will lower the total value of the system and may lower the value of the equity of some of the individual system firms.

Credit Risk: Modeling, Valuation and Hedging

Abstract: The main objective of Credit Risk: Modeling, Valuation and Hedging is to present a comprehensive survey of the past developments in the area of credit risk research, as well as to put forth the most recent advancements in this field. An important aspect of this text is that it attempts to bridge the gap between the mathematical theory of credit risk and the financial practice, which serves as the motivation for the mathematical modeling studied in the book. Mathematical developments are presented in a thorough manner and cover the structural (value-of-the-firm) and the reduced (intensity-based) approaches to credit risk modeling, applied both to single and to multiple defaults. In particular, the book offers a detailed study of various arbitrage-free models of defaultable term structures with several rating grades. This volume will serve as a valuable reference for financial analysts and traders involved with credit derivatives. Some aspects of the book may also be useful for market practitioners engaged in managing credit-risk sensitive portfolios. Graduate students and researchers in areas such as finance theory, mathematical finance, financial engineering and probability theory will benefit from the book as well. On the technical side, readers are assumed to be familiar with graduate level probability theory, theory of stochastic processes, and elements of stochastic analysis and PDEs some aquaintance with arbitrage pricing theory is also expected. A systematic exposition of mathematical techniques underlying the intensity-based approach is however provided.

Bankruptcy prediction for credit risk using neural networks: A survey and new results

Abstract: The prediction of corporate bankruptcies is an important and widely studied topic since it can have significant impact on bank lending decisions and profitability. This work presents two contributions. First we review the topic of bankruptcy prediction, with emphasis on neural-network (NN) models. Second, we develop an NN bankruptcy prediction model. Inspired by one of the traditional credit risk models developed by Merton (1974), we propose novel indicators for the NN system. We show that the use of these indicators in addition to traditional financial ratio indicators provides a significant improvement in the (out-of-sample) prediction accuracy (from 81.46% to 85.5% for a three-year-ahead forecast).

Do Liquidity Constraints and Interest Rates Matter for Consumer Behavior? Evidence from Credit Card Data

Abstract: This paper utilizes a unique new dataset of credit card accounts to analyze how people respond to changes in credit supply. The data consist of a panel of thousands of individual credit card accounts from several different card issuers, with associated credit bureau data. We estimate both marginal propensities to consume (MPCs) out of liquidity and interest-rate elasticities. We also evaluate the ability of different models of consumption to rationalize our results, distinguishing the Permanent-Income Hypothesis (PIH), liquidity constraints, precautionary saving, and behavioral models. We find that increases in credit limits generate an immediate and significant rise in debt, counter to the PIH. The average "MPC out of liquidity" (dDebt/dLimit) ranges between 10%-14%. The MPC is much larger for people starting near their limits, consistent with binding liquidity constraints. However, the MPC is significant even for people starting well below their limit. We show this response is consistent with buffer-stock models of precautionary saving. Nonetheless there are other results that conventional models cannot easily explain, for example, why so many people are borrowing on their credit cards, and simultaneously holding low yielding assets. Unlike most other studies, we also find strong effects from changes in account-specific interest rates. The long-run elasticity of debt to the interest rate is approximately -1.3. Less than half of this elasticity represents balance-shifting across cards, with most reflecting net changes in total borrowing. The elasticity is larger for decreases in interest rates than for increases, which can explain the widespread use of temporary promotional rates. The elasticity is smaller for people starting near their credit limits, again consistent with liquidity constraints.

Counterparty Risk and the Pricing of Defaultable Securities

Abstract: Motivated by recent financial crises in East Asia and the United States where the downfall of a small number of firms had an economy-wide impact, this paper generalizes existing reduced-form models to include default intensities dependent on the default of a counterparty. In this model, firms have correlated defaults due not only to an exposure to common risk factors, but also to firm-specific risks that are termed “counterparty risks.” Numerical examples illustrate the effect of counterparty risk on the pricing of defaultable bonds and credit derivatives such as default swaps. IT HAS BEEN WELL DOCUMENTED in Moody’s reports on historical default rates of corporate bond issuers that the number of defaults, the number of credit rating downgrades, and credit spreads are all strongly correlated with the business cycle. This has motivated reduced-form models such as Duffie and Singleton ~1999! and Lando ~1994, 1998!, which assume that the intensity of default is a stochastic process that derives its randomness from a set of state variables such as the short-term interest rate. This approach has the convenient features that conditioning on the state variables, defaults become independent events, and default correlation arises due to the common inf luence of these state variables. On the other hand, a default intensity that depends linearly on a set of smoothly varying macroeconomic variables is unlikely to account for the clustering of defaults around an economic recession. This is evident from a casual inspection of the exhibits in the latest Moody’s report ~see Keenan ~2000!!. Within the usual affine framework, one can model the state variables as jump diffusions ~see Duffie, Pan, and Single

The term structure of credit spreads with jump risk

Abstract: Default risk analysis is important for valuing corporate bonds, swaps, and credit derivatives and plays a critical role in managing the credit risk of bank loan portfolios. This paper offers a theory to explain the observed empirical regularities on default probabilities, recovery rates, and credit spreads. It incorporates jump risk into the default process. With the jump risk, a firm can default instantaneously because of a sudden drop in its value. As a result, a credit model with the jump risk is able to match the size of credit spreads on corporate bonds and can generate various shapes of yield spread curves and marginal default rate curves, including upward-sloping, downward-sloping, flat, and hump-shaped, even if the firm is currently in a good financial standing. The model also links recovery rates to the firm value at default so that the variation in recovery rates is endogenously generated and the correlation between recovery rates and credit ratings before default reported in Altman [J. Finance 44 (1989) 909] can be justified.

Stochastic processes in insurance and finance

Abstract: Publisher Summary This chapter dealt mainly with the application of financial pricing techniques to insurance problems. However, actuarial concepts are also of increasing relevance for finance problems. This chapter presents that realistic models for asset price processes are typically incomplete. Actuarial concepts for risk-management might prove helpful in dealing with these “unhedgeable” risks. An example where such concepts are already applied, is the RAC-(risk adjusted capital) approach in insurance that has become popular among investment banks as a tool for the determination of risk capital and capital allocations. It is no coincidence that Swiss Bank Cooperation (now UBS) called one of its credit risk management systems ACRA, which stands for Actuarial Credit Risk Accounting.

Banks as Monitors of Other Banks: Evidence from the Overnight Federal Funds Market*

Abstract: This study provides evidence that banks are effective monitors of their peers by showing that the interest rate paid on federal funds transactions reflects differences in credit risk across borrowers. In addition, the size and relative importance in the funds market of the trading institutions are shown to affect the rates charged for overnight borrowing, thereby providing insight into the nature of competition in the federal funds market. Transaction volume and size-of-transaction effects are uncovered, as is evidence of relationship banking between banks. These results are made possible by unique data identifying individual federal funds transactions. Copyright 2001 by University of Chicago Press.

Copula-Dependent Defaults in Intensity Models

Abstract: In this paper we present a new approach to incorporate dynamic default dependency in intensity-based default risk models. The model uses an arbitrary default dependency structure which is specified by the Copula of the times of default, this is combined with individual intensity-based models for the defaults of the obligors without loss of the calibration of the individual default-intensity models. The dynamics of the survival probabilities and credit spreads of individual obligors are derived and it is shown that in situations with positive dependence, the default of one obligor causes the credit spreads of the other obligors to jump upwards, as it is experienced empirically in situations with credit contagion. For the Clayton copula these jumps are proportional to the pre-default intensity. If information about other obligors is excluded, the model reduces to a standard intensity model for a single obligor, thus greatly facilitating its calibration. To illustrate the results they are also presented for Archimedean copulae in general, and Gumbel and Clayton copulae in particular. Furthermore it is shown how the default correlation can be calibrated to a Gaussian dependency structure of CreditMetrics-type.

An Analysis of Default Correlations and Multiple Defaults

Abstract: Evaluating default correlations or the probabilities of default by more than one firm is an important task in credit analysis, derivatives pricing, and risk management. However, default correlations cannot be measured directly, multiple-default modeling is technically difficult, and most existing credit models cannot be applied to analyze multiple defaults. This article develops a first-passage-time model, providing an analytical formula for calculating default correlations that is easily implemented and conveniently used for a variety of financial applications. The model also provides a theoretical justification for several empirical regularities in the credit risk literature. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.

Credit risk optimization with Conditional Value-at-Risk criterion

Abstract: This paper examines a new approach for credit risk optimization. The model is based on the Conditional Value-at-Risk (CVaR) risk measure, the expected loss exceeding Value-at-Risk. CVaR is also known as Mean Excess, Mean Shortfall, or Tail VaR. This model can simultaneously adjust all positions in a portfolio of financial instruments in order to minimize CVaR subject to trading and return constraints. The credit risk distribution is generated by Monte Carlo simulations and the optimization problem is solved effectively by linear programming. The algorithm is very efficient; it can handle hundreds of instruments and thousands of scenarios in reasonable computer time. The approach is demonstrated with a portfolio of emerging market bonds.

Valuing Credit Default Swaps II: Modeling Default Correlations

Abstract: “In the Fall 2000, Journal of Derivatives, Hull and White presented a model for pricing credit default swaps based on the realistic assumption that in a default the bondholders will claim the difference between the bond&9s post-default market value and its face value. An important feature of the approach is the use of market prices for a set of bonds from the same issuer to obtain a term structure of risk-neutral implied default probabilities. This article extends the model significantly to allow for the existence of multiple correlated default risks. Correlations are important either when the swap is subject to counterparty credit risk, or when there are multiple underlyings with correlated risks, as in a basket default swap.”

The Components of Corporate Credit Spreads: Default, Recovery, Tax, Jumps, Liquidity, and Market Factors - eScholarship

Abstract: This paper analyzes the components of corporate credit spreads. The analysis is based on a structural model that can offer a framework to understand the decomposition. The paper contends that default risk may correctly represent only a small portion of corporate credit spreads. This idea stems both from empirical evidence and from the following theoretical assumptions underlying contingent claim models of default: that markets for corporate stocks and bonds are (i) perfect, (ii) complete, and (iii) trading takes place continuously. Thus, in these models there are no transaction or bankruptcy costs, no tax effects, no liquidity effects, no jump effects reflecting market incompleteness, and no market risk factors effecting the pricing of corporate stocks or bonds. The paper starts with the use of a modified version of the Black-Scholes-Merton diffusion based option approach. We estimate corporate default spreads as simply a component of corporate credit spreads using data from November 1991 to December 1998, which includes the Asian Crisis in the Fall, 1998. First we measure the difference between the observed corporate credit spreads and option based estimates of default spreads. We define this difference as the residual spread. We show that for AAA (BBB) firms only a small percentage, 5% (22%), of the credit spread can be attributed to default risk. We show that recovery risk also cannot explain this residual spread. Next, we show that state taxes on corporate bonds also cannot explain the residual. We note that the pure diffusion assumption may lead to underestimates of the default risk. In order to include jumps to default, we next estimate what combined jump-diffusion parameters would be necessary to force default spread to eliminate the residual spread. In each rating class on average firms would be required to experience annual jumps that decrease firm value by 20% and increase stock volatility by more than 100% over their observed volatility in order to eliminate the residual spread. We consider this required increase in stock volatility to be unrealistic as the sole explanation of the residual spread. So next we consider whether the unexplained component can be partly attributable to interest rates, liquidity, and market risk factors. We find the following empirical results: i) increases in liquidity as measured by changes in each firm’s trading volume significantly reduces the residual spread, but does not alter the default spread; ii) increases in stock market volatility significantly reduces the residual spread by increasing the default spread relative to the credit spread, and iii) increases in stock market returns significantly increases the residual spread by reducing the default spread relative to the credit spread. This paper concludes that credit risk and credit spreads are not primarily explained by default and recovery risk, but are mainly attributable to taxes, jumps, liquidity, and market risk factors.

The Effects of Credit Attitude and Socioeconomic Factors on Credit Card and Installment Debt

Abstract: Most previous research on credit use has examined the effect of socioeconomic and attitude variables without considering the possible correlation among these factors. Also, the studies have not considered whether there is a difference between general and specific attitudes toward credit and the use of credit. This study addresses those problems and includes installment debt as well as credit card debt in the analysis. The study used data from the 1998 Survey of Consumer Finances. The findings show the higher the specific attitude index, the higher the outstanding credit card balances, and the more favorable the general attitude toward using credit, the higher the installment debt. The results suggest the need for greater awareness on the part of consumers and consumer educators on the influence of attitude in the use of credit.

Prototype risk rating system

Abstract: This paper explores the traditional and prevalent approach to credit risk assessment – the rating system. We first describe the rating systems of the two main credit rating agencies, Standard & Poor's and Moody's. Then we show how an internal rating system in a bank can be organized in order to rate creditors systematically. We suggest adopting a two-tier rating system. First, an obligor rating that can be easily mapped to a default probability bucket. Second, a facility rating that determines the loss parameters in case of default, such as (i) “loss given default” (LGD), which depends on the seniority of the facility and the quality of the gurantees, and (ii) “usage given default” (UGD) for loan commitments, which depends on the nature of the commitment and the rating history of the borrower.

Stability of ratings transitions

Abstract: The distribution of ratings changes plays a crucial role in many credit risk models. As is well known, these distributions vary across time and different issuer types. Ignoring such dependencies may lead to inaccurate assessments of credit risk. In this paper, a quantification is provided of the dependence of ratings transition probabilities on the industry and domicile of the obligor, and on the stage of the business cycle. The incremental impact of these factors is identified using ordered probit models. This approach gives a clearer picture (than is obtained by comparing transition matrices estimated from different sub-samples) of which conditioning factors are important.

An empirical analysis of interest rate spread in Kenya

Abstract: Financial reform predicts achievement of efficiency in the intermediation process and reduced transaction costs, which is proxied by a narrowing wedge between the lending and deposit rates. Kenya's experience shows a rise in interest rate spread during the financial reform and subsequent financial liberalization process, which suggests the failure to meet the prerequisites for successful financial liberalization. Interest rates were liberalized amidst inflationary pressure, declining economic growth, financial instability, the failure to sustain fiscal discipline and lack of proper sequencing of the shift to use monetary policy tools. At the micro level, our results show that when the profit margin is threatened, banks sustain a widening spread. Faced with a rising credit risk due to distress borrowing and poor macroeconomic conditions, banks charge a higher risk premium on their lending rate. The accumulation of non-performing loans results from a weak legal system and a poor business environment that squeezes the profit margin, and banks respond by increasing the lending rate. Policy actions also affect the spread. An asymmetric response is indicated with the treasury bill rate where lending rates increase with the treasury bill rate, and become sticky downward when the treasury bill rate declines. Further, increased implicit costs that accompany tight monetary policy sustain a widening spread even when inflationary pressure is reduced. Thus a widening interest rate spread indicates inefficiency in the intermediation process and rising costs of intermediation.

Analytical value-at-risk with jumps and credit risk

Abstract: This paper provides an analytical approximation for computing value at risk and other risk measures for portfolios that may include options and other derivatives with defaultable counterparties or borrowers The risk setting is that of a classical multi-factor jump-diffusion for default intensities and asset returns, under which between-jump returns are correlated Brownian motions, with return jumps at Poisson arrivals that are jointly normally distributed This allows for fat-tailed and skewed return distributions

Parameterizing credit risk models with rating data

Abstract: Estimates of average default probabilities for borrowers assigned to each of a financial institution’s internal credit risk rating grades are crucial inputs to portfolio credit risk models. Such models are increasingly used in setting financial institution capital structure, in internal control and compensation systems, in asset-backed security design, and are being considered for use in setting regulatory capital requirements for banks. This paper empirically examines properties of the major methods currently used to estimate average default probabilities by grade. Evidence of potential problems of bias, instability, and gaming is presented. With care, and perhaps judicious application of multiple methods, satisfactory estimates may be possible. In passing, evidence is presented about other properties of internal and rating-agency ratings. ” 2001 Elsevier Science B.V. All rights reserved.

An Empirical Analysis of Personal Bankruptcy and Delinquency

Abstract: This paper uses a new panel data set of credit card accounts to analyze credit card delinquency, personal bankruptcy, and the stability of credit risk models. We estimate duration models for default and assess the relative importance of different variables in predicting default. We investigate how the propensity to default has changed over time, disentangling the two leading explanations for the recent increase in default rates - a deterioration in the risk - composition of borrowers versus an increase in borrowers' willingness to default due to declines in default costs, including social, information, and legal costs. Even after controlling for risk-composition and other economic fundamentals, the propensity to default significantly increased between 1995 and 1997. By contrast, increases in credit limits and other changes in risk-composition explain only a small part of the change in default rates. Standard default models appear to have missed an important time-varying default factor, consistent with a decline in default costs.

Understanding the Role of Recovery in Default Risk Models: Empirical Comarisons and Implied Recovery Rates

Abstract: This article presents a framework for studying the role of recovery on defaultable debt prices (for a wide class of processes describing recovery rates and default probability). These debt models have the ability to differentiate the impact of recovery rates and default probability, and can be utilized to invert the market expectation of recovery rates implicit in bond prices. Empirical implementation of these models suggests two central findings. First, the recovery concept that specifies recovery as a fraction of the discounted par value has broader empirical support. Second, parametric debt valuation models can provide a useful assessment of recovery rates embedded in bond prices. This article has attempted to model recovery and comprehend their impact on debt values.

The Components of Corporate Credit Spreads: Default, Recovery, Taxes, Jumps, Liquidity, and Market Factors

Abstract: This paper analyzes the components of corporate credit spreads. The analysis is based on a structural model that can offer a framework to understand the decomposition. The paper contends that default risk may correctly represent only a small portion of corporate credit spreads. This idea stems both from empirical evidence and from the following theoretical assumptions underlying contingent claim models of default: that markets for corporate stocks and bonds are (i) perfect, (ii) complete, and (iii) trading takes place continuously. Thus, in these models there are no transaction or bankruptcy costs, no tax effects, no liquidity effects, no jump effects reflecting market incompleteness, and no market risk factors effecting the pricing of corporate stocks or bonds. The paper starts with the use of a modified version of the Black-Scholes-Merton diffusion based option approach. We estimate corporate default spreads as simply a component of corporate credit spreads using data from November 1991 to December 1998, which includes the Asian Crisis in the Fall, 1998. First we measure the difference between the observed corporate credit spreads and option based estimates of default spreads. We define this difference as the residual spread. We show that for AAA (BBB) firms only a small percentage, 5% (22%), of the credit spread can be attributed to default risk. We show that recovery risk also cannot explain this residual spread. Next, we show that state taxes on corporate bonds also cannot explain the residual. We note that the pure diffusion assumption may lead to underestimates of the default risk. In order to include jumps to default, we next estimate what combined jump-diffusion parameters would be necessary to force default spread to eliminate the residual spread. In each rating class on average firms would be required to experience annual jumps that decrease firm value by 20% and increase stock volatility by more than 100% over their observed volatility in order to eliminate the residual spread. We consider this required increase in stock volatility to be unrealistic as the sole explanation of the residual spread. So next we consider whether the unexplained component can be partly attributable to interest rates, liquidity, and market risk factors. We find the following empirical results: i) increases in liquidity as measured by changes in each firm's trading volume significantly reduces the residual spread, but does not alter the default spread; ii) increases in stock market volatility significantly reduces the residual spread by increasing the default spread relative to the credit spread, and iii) increases in stock market returns significantly increases the residual spread by reducing the default spread relative to the credit spread. This paper concludes that credit risk and credit spreads are not primarily explained by default, leverage, firm specific risk, and recovery risk, but are mainly attributable to taxes, jumps, liquidity, and market risk factors.

Default risk and diversification: theory and applications

Abstract: Recent advances in the theory of credit risk allow the use of standard term structure machinery for default risk modeling and estimation. The empirical literature in this area often interprets the drift adjustments of the default intensity’s diffusion state variables as the only default risk premium. We show that this interpretation implies a restriction on the form of possible default risk premia, which can be justified through exact and approximate notions of “diversifiable default risk.” The equivalence between the empirical and martingale default intensities that follows from diversifiable default risk greatly facilitates the pricing and management of credit risk. We emphasize that this is not an equivalence in distribution, and illustrate its importance using credit spread dynamics estimated in Duffee (1999). We also argue that the assumption of diversifiability is implicitly used in certain existing models of mortgage-backed securities. Reduced-form models of defaultable securities, which view the default of corporate bond issuers as an unpredictable event, have become a popular tool in credit risk modeling. A key advantage of this approach is that it brings into play the machinery of classical term structure modeling techniques. This is convenient for the econometric specification of models for credit risky bonds as well as for the pricing of credit derivatives. The strong analogy with ordinary term structure modeling, which will be briefly recalled in the next section, allows for specifications of default intensities and short rates using for example the affine term structure machinery of which the models by Cox, Ingersoll and Ross (1985) and Vasicek (1977) are the classic examples.1 Pricing bonds and derivatives in this framework requires only the evolution of the state variables under an equivalent martingale measure. However, in order to understand the factor risk premia in bond markets and to utilize time-series information in the empirical estimation, a joint specification of the evolution of the state variables under the “physical measure” and the equivalent martingale measure is required. The structure of these risk premia is well understood, for example, in the affine models of the term structure. A key concern in our understanding of the corporate bond market is the form and size of the risk premia for default risk. Since the reduced-form approach allows us to model default risk using standard term structure machinery, it is natural to use the same structure for the risk premia of the intensity processes as we would use for the short rate process in ordinary term structure models. This choice has led to an interpretation of the drift adjustment on the state variables underlying the martingale default intensity as a “default risk premium” or “price of default risk.”2 Recent examples of this approach are the empirical works by Duffie and Singleton (1997), Duffee (1999), and Liu, Longstaff and Mandell (2001). The last paper proceeds a step further along the risk premium interpretation by computing the expected returns on defaultable bonds using these drift adjustments. We show in this paper that this specification for the default risk premia implies a strong re- striction on the set of possible risk premia. The fact that the intensity process is not just an affine function of diffusion state variables but is also the compensator of a jump process allows for a much richer class of risk premia. The critical distinction is really whether agents only price variations in the default intensity, which then must be pervasive, or they also price the default event itself. This insight can be derived from existing works such as Back (1991) and Jarrow and Madan (1995). Through the well-known connection between the state-price density and the marginal utility of a representative investor or a single optimizing agent, it is easy to see that the structure of the default risk premia used in the current empirical literature implies that there can be no For more general works on affine models, see for example Duffie and Kan (1996) and Dai and Singleton (2000). To be precise, the martingale intensity is usually assumed to depend on short rate factors. This is to capture the systematic dependence of credit spreads on the default-free term structure. The drift adjustments on these short rate factors are appropriately interpreted as interest rate risk premia. However, usually one more state variable is included for the intensity and its risk adjustment is given the interpretation of a default risk premium.

Rating Agency Actions and the Pricing of Debt and Equity of European Banks: What Can We Infer About Private Sector Monitoring of Bank Soundness?

Abstract: The recent consultative papers by the Basel Committee suggest an explicit role for external rating agencies in the assessment of the credit risk of banks' assets. In this context, an assessment of the information contained in credit ratings is important. We address this issue via an event study of rating change announcements by leading international rating agencies, focussing on a sample of European banks. We find no evidence of announcement effects on bond prices. We are largely able to exclude lack of liquidity as an explanation for this puzzling result and suggest some alternatives, such as "too-big-to-fail." For equity prices, we find strong effects of unexpected ratings changes and confirm prior evidence that stock prices may react very differently to ratings downgrades, depending on the underlying reason. Overall, our results suggest that ratings agencies may perform a useful role in summarising and obtaining non-public information on banks, at least for stockholders.

An analysis and critique of the BIS proposal on capital adequacy and ratings

Abstract: In June 1999, the BIS released its long awaited proposal on reform of the 8% risk-based capital ratio for credit risk that has been in effect since 1993 (see Basel Committee on Banking Supervision, 1999).1 The 8% ratio has been criticized on at least three major grounds. First, it gives an equal risk-weighting to all corporate credits whether of high or low credit quality. Second, it fails to incorporate potential capital savings from credit (loan) portfolio diversification. The latter is a result of its simple additive nature. And third, it has led to extensive regulatory capital arbitrage which adds to the riskiness of bank asset portfolios.

Credit handling in an anonymous trading system

Abstract: In an anonymous trading system, credit between counterparties is effectively increased by netting buy and sell trades to reflect the true risk to which each party is exposed. Credit limits are adjusted by calculating the exposure in each currency at the relevant time and then converted into the credit limit currency equivalent. The credit limits are adjusted accordingly. The resulting credit limits may be different for bids and offers by or from a given counterparty.

An analytic approach to credit risk of large corporate bond and loan portfolios

Abstract: We derive an analytic approximation to the credit loss distribution of large portfolios by letting the number of exposures tend to infinity. Defaults and rating migrations for individual exposures are driven by a factor model in order to capture co-movements in changing credit quality. The limiting credit loss distribution obeys the empirical stylized facts of skewness and heavy tails. We show how portfolio features like the degree of systematic risk, credit quality and term to maturity affect the distributional shape of portfolio credit losses. Using empirical data, it appears that the Basle 8% rule corresponds to quantiles with confidence levels exceeding 98%. The limit law's relevance for credit risk management is investigated further by checking its applicability to portfolios with a finite number of exposures. Relatively homogeneous portfolios of 300 exposures can be well approximated by the limit law. A minimum of 800 exposures is required if portfolios are relatively heterogeneous. Realistic loan portfolios often contain thousands of exposures implying that our analytic approach can be a fast and accurate alternative to the standard Monte-Carlo simulation techniques adopted in much of the literature.