We develop a framework for modeling conditional loss distributions through the introduction of risk factor dynamics. Asset value changes of a credit portfolio are linked to a dynamic global macroeconometric model, allowing macro effects to be isolated from idiosyncratic shocks from the perspective of default (and hence loss). Default probabilities are driven primarily by how firms are tied to business cycles, both domestic and foreign, and how business cycles are linked across countries. The model is able to control for firm-specific heterogeneity as well as generate multi-period forecasts of the entire loss distribution, conditional on specific macroeconomic scenarios. The approach can be used, for example, to compute the effects of a hypothetical negative equity price shock in South East Asia on the loss distribution of a credit portfolio with global exposures over one or more quarters. The approach has several other features of particular relevance for risk managers, such as the exploration of scale and symmetry of shocks, and the effect of non-normality on credit risk. We show that the effects of such shocks on losses are asymmetric and non-proportional, reflecting the highly non-linear nature of the credit risk model. Non-normal innovations such as Student t generate expected and unexpected losses which increase the fatter the tails of the innovations.

Procyclicality has emerged as a potential drawback to adoption of risk-sensitive bank capital requirements. Systematic risk factors may result in increases (decreases) in bank capital requirements when the economy is depressed (overheated), thereby decreasing (increasing) bank lending capacity and exacerbating business cycle fluctuations. Procyclicality may result from systematic risk emanating from common macroeconomic influences or from interdependencies across firms as financial markets and institutions consolidate internationally. We survey the literature on cyclical effects on operational risk, credit risk and market risk measures. Incorporating Systemic Influences Into Risk Measurements: A Survey of the Literature Bank regulations focus on individual institutions. The Basel Capital Accords (both current and proposed) base international bank capital requirements on the measurement of risk for each individual bank. Aggregate capital levels are then obtained by simply adding each bank’s individual capital requirement. To the extent that there is any attention paid to aggregate capital levels at all, it is only as a means to calibrate the

Please send questions and/or remarks of nonscientific nature to driessen@tinbergen.nl. Most TI discussion papers can be downloaded at

Abstract not found

Abstract not found

A major topic in empirical finance is correlation of default risk. Correlations are the main drivers for credit risk on a portfolio basis and for banks ’ capital requirements under the New Basel Accord. However, empirical evi-dence on the magnitude of correlations is rather scarce, mainly due to data limitations. Using a large database of bankruptcies in Germany we estimate correlations using a simple version of the Basel II factor model. Then we extend the model to an approach with observable risk factors and suggest that this model with default probabili-ties depending on the state of the economy may be more adequate. Empirical evidence on proxies for the credit cycles is presented for German industry sectors. We find that much of the co-movements can be explained by our variables. Finally, we discuss some implications for forecasts of distributions of potential future defaults of a bank’s portfolio. 1

Using a limiting approach to portfolio credit risk, we obtain analytic expressions for the tail behavior of credit losses. To capture the co-movements in defaults over time, we assume that defaults are triggered by a general, possibly non-linear, factor model involving both systematic and idiosyncratic risk factors. The model encompasses default mechanisms in popular models of portfolio credit risk, such as CreditMetrics and CreditRisk +. We show how the tail characteristics of portfolio credit losses depend directly upon the factor model’s functional form and the tail properties of the model’s risk factors. In many cases the credit loss distribution has a polynomial (rather than exponential) tail. This feature is robust to changes in tail characteristics of the underlying risk factors. Finally, we show that the interaction between portfolio quality and credit loss tail behavior is strikingly different between the CreditMetrics and CreditRisk + approach to modeling portfolio credit risk. Key words: portfolio credit risk; extreme value theory; tail events; tail index; factor models; economic capital; portfolio quality; secondorder expansions.

This paper examines latent risk factors in models for migration risk. We employ the standard statistical framework for ordered categorical variables and induce dependence between migrations by means of latent risk factors. By assuming a Markov process for the dynamics of the latent factors, the model can be interpreted as a state space model. The paper contains an empirical study on quarterly migration data from Standard & Poor’s for the years 1981–2000, in which the ordered logit model with serially correlated latent factors is fitted by computational Bayesian techniques (Gibbs sampling). Apart from highlighting the usefulness of the Gibbs sampler for statistical inference in models of this kind, the survey in particular investigates the issues of rating-specific factor loadings and heterogeneity among industry sectors, with emphasis on their implications in terms of implied asset correlations.

This paper investigates the pricing of step-up bonds, ie, corporate bonds with provisions stating that the coupon payments increase as the credit rating level of the issuer declines. To assess the risk-neutral rating transition probabilities necessary to price these bonds, we introduce a new calibration method within the reduced-form rating-based model of Jarrow, Lando and Turnbull (1997). We also treat split ratings and adjust for rating outlook. Step-up bonds have been issued in large quantities in the European telecom sector, and we find that, through most of the sample, step-up bonds issued by the two largest issuers have traded at a discount relative to comparable fixed-coupon bonds from the same issuers. Our findings cannot be attributed to traditional liquidity factors, and they suggest that issuing step-up bonds increased the cost of capital for the issuers.

The Center for Financial Studies is a nonprofit research organization, supported by an association of more than 120 banks, insurance companies, industrial corporations and public institutions. Established in 1968 and closely affiliated with the University of Frankfurt, it provides a strong link between the financial community and academia. The CFS Working Paper Series presents the result of scientific research on selected topics in the field of money, banking and finance. The authors were either participants in the Center´s Research Fellow Program or members of one of the Center´s Research Projects. If you would like to know more about the Center for Financial Studies, please let us know of your interest.