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Abstract:
The new Basel II regulation contains a number of new regulatory features. Most importantly, internal ratings will be given a central role in the evaluation of bank loans' riskiness. Another novelty is that retail credit and SME loans will receive a special treatment in recognition of the fact that the riskiness of such exposure derives to a greater extent from idiosyncratic risk and much less from common factor risk. Much of the work done on the differences between the risk properties of retail, SME and corporate credit has been based on parameterized model of credit risk. In this paper we present new quantitative evidence on the implied credit loss distributions for two Swedish banks using a non-parametric Monte Carlo re-sampling method following Carey [1998]. Our results are based on a panel data set containing both loan and internal rating data from the banks' complete business loan portfolios over the period 1997-2000. We compute the credit loss distributions that each rating system implies and compare the required economic capital implied by these loss distributions with the regulatory capital under Basel II. By exploiting the fact that a subset of all businesses in the sample is rated by both banks, we can generate loss distributions for SME, retail and corporate credit portfolios with a constant risk profile. Our findings suggest that a special treatment for retail credit and SME loans may not be justified. We also investigate if any alternative definition of SME's and retail credit would warrant different risk weight functions for these types of exposure. Our results indicate that it may be difficult to find a simple risk weight function that can account for the differences in portfolio risk properties between banks and asset types.

Internal ratings, credit risk, Value-at-Risk, banks, Basel II, retail credit, SME, risk weights

Abstract:
Although much research has been devoted to external credit ratings, relatively little is known about the workings of banks' internal ratings. This paper aims at improving our understanding of internal risk rating systems (IRS) at large banks and the way in which they are implemented, and at verifying if IRS produce consistent estimates of banks' loan portfolio credit risk. An important property of our work is that we derive our measures of credit risk without making any assumptions about correlations between loans, due to the fact that the size of the data allows us to apply Carey's [16] non-parametric Monte Carlo re-sampling method. We find substantial differences between the implied loss distributions of the two banks with equal regulatory risk profiles; both expected losses and the credit loss rates at a wide range of loss distribution percentiles vary considerably. Such variation will most likely translate into different levels of required economic capital. Our results also confirm the quantitative importance of size for portfolio credit risk: for common parameter values, we find that tail risk can be reduced by up to 40 percent by doubling portfolio size. Our analysis makes clear that not only the formal design of a rating system, but also the way in which it is implemented (e.g. a portfolio's rating grade composition; the degree of homogeneity within rating classes) can be quantitatively important for the shape of credit loss distributions and thus for banks' required capital structure. The evidence of differences between lenders also hints at the presence of differentiated market equilibria, that are more complex than might otherwise be supposed: different lending or risk management styles may emerge and banks strike their own balance between risk-taking and (the cost of) monitoring (that risk).

Internal ratings, rating systems, credit risk, tails, Value-at-Risk, banks, Basel II

Abstract:
Counterpart risk rating is at the heart of the banking business. In the new Basel II regulation, internal ratings have been given a central role. Although much research has been done on external ratings, much less is known about banks' internal ratings. This paper presents new quantitative evidence on the consistency of internal ratings based on panel data from the complete business loan portfolios of two Swedish banks and a credit bureau over the period 1997-2000. We study rating class distributions, transitions and default behavior and compute the credit loss distributions that each rating system implies by means of a semi-parametric Monte Carlo re-sampling method following Carey (1998). Our results reveal, for a portfolio with identical counterparts, substantial differences in the implied riskiness between banks. Such differences could translate into different amounts of required economic capital and create (new) incentives to securitize part of their loan portfolios or increase the riskiness of loans in certain rating classes. We also shed light on the quantitative importance of portfolio composition, portfolio size and the forecast horizon for loss distributions. For example, with common portfolio parameters, credit risk can be reduced by up to 40 percent by doubling the loan portfolio size. We also discuss the relation between loss distributions and the desirable level of insolvency risk.

Internal ratings, credit risk, tails, Value-at-Risk, banks, Basel II

Abstract:
The Internal Ratings Based (IRB) approach for capital determination is one of the cornerstones in the proposed revision of the Basel Committee rules for bank regulation. We evaluate the IRB approach using historical business loan portfolio data from a major Swedish bank for the period 1994 to 2000. First, we estimate a duration model that takes into account both company, loan related and macroeconomic variables. Next, we obtain a Value-at-Risk-type (VaR) credit risk measure, by model-based simulations. Moreover, we study how both the bank's credit risk and buffer capital changes over time (had the bank been subject to the proposed rules). This approach allows us to (i) make individual forecasts of default risk conditional on company, loan and macro variables, (ii) study portfolio credit risk over time, (iii) assess to what extent the new Accord will achieve its main objective of increasing credit risk sensitivity in minimal capital charges, and (iv) compare current capital requirements to those under the proposed system. Our results show that macro conditions have great explanatory power in predicting default risk and calculating credit risk. The IRB approach, although sensitive to the choice of some horizon parameters, is an achievement in the intended direction.

Internal Ratings Based approach, relative risk weights, Value-at-Risk, credit risk models

Abstract:
Despite a surge in the research efforts put into modelling credit risk during the past decade, few studies have incorporated the impact that macroeconomic conditions have on business defaults. In this paper, we estimate a duration model to explain the survival time to default for borrowers in the business loan portfolio of a major Swedish bank over the
period 1994-2000. The model takes both firm-specific characteristics, such as accounting ratios and payment behaviour, loan-related information, and the prevailing macroeconomic conditions into account. The output gap, the yield curve and consumers' expectations of future economic development have significant explanatory power for the default risk of firms. We also compare our model with a frequently used model of firm default risk that conditions only on firm-specific information. The comparison shows that while the latter model can make a reasonably accurate ranking of firms' according to default risk, our model, by taking
macro conditions into account, is also able to account for the absolute level of (default, and thus also credit) risk.

Firm default, default risk, credit risk, corporate loans, duration model, survival, macroeconomy

Abstract:
The Internal Ratings Based (IRB) approach for determining banks' capital adequacy is one of the cornerstones of the Basel Committee's proposed revision of the Basel Accord for banking regulation. This article presents the ideas behind the IRB approach and its fundamental features, and discusses the consequences of a number of its components for the banks' capital adequacy requirements. Using a simulation-based analysis, we will illustrate the relationship between IRB-determined capital and the risks inherent in a loan portfolio in a dynamic perspective assuming different macroeconomic developments.1 We will also examine the effect of the number of risk classes that banks use and of different risk profiles of their credit portfolios.

IRB, Basel II, internal ratings, loan portfolio, credit risk, macroeconomic development

Abstract:
This paper studies the relation between macroeconomic fluctuations and corporate defaults while conditioning on industry affiliation and an extensive set of firm-specific factors. Using a multiperiod logit approach on a panel data set for all incorporated Swedish businesses over 1990-2002, we find strong evidence for a substantial and stable impact of aggregate fluctuations. Macroeffects differ across industries in an economically intuitive way. Out-of sample evaluations show our approach is superior to both models that exclude macro information and best fitting naive forecasting models. While firm-specific factors are useful in ranking firms' relative riskiness, macroeconomic factors capture fluctuations in the absolute risk level.

business cycles, default, default-risk model, logit model, macroeconomic variables and micro-data

Abstract:
This paper studies the relation between macroeconomic fluctuations and corporate defaults while conditioning on industry affiliation and an extensive set of firm-specific factors. Using a logit approach on a panel data set for all incorporated Swedish businesses over 1990-2002, we find strong evidence for a substantial and stable impact of aggregate fluctuations. Macroeffects differ across industries in an economically intuitive way. Out-of-sample evaluations show our approach is superior to both models that exclude macro information and best fitting naive forecasting models. While firm-specific factors are useful in ranking firms' relative riskiness, macroeconomic factors capture fluctuations in the absolute risk level.

Default, default-risk model, business cycles, aggregate fluctuations, microdata, logit, firm-specific variables, macroeconomic variables

Abstract:
This paper studies the relation between macroeconomic fluctuations and corporate defaults while conditioning on industry affiliation and an extensive set of firm-specific factors. Using a logit approach on a panel data set for all incorporated Swedish businesses over 1990-2002, we find strong evidence for a substantial and stable impact of aggregate fluctuations. Macroeffects differ across industries in an economically intuitive way. Out-of-sample evaluations show our approach is superior to both models that exclude macro information and best fitting naive forecasting models. While firm-specific factors are useful in ranking firms’ relative riskiness, macroeconomic factors capture fluctuations in the absolute risk level.

default, default-risk model, business cycles, aggregate fluctuations, microdata, logit, firm-specific variables, macroeconomic variables

Abstract:
New multivariate panel co-integration methods are used to analyze nominal exchange rates and prices in four major economies in Europe: France, Germany, Italy and the United Kingdom for the post-Bretton Woods period. We test for purchasing power parity (PPP) between these four countries and find that the theoretical PPP relationship does not hold. However, the estimated unrestricted relationship is found to be remarkably close to the theoretical one (1, 1.5, 0.9 instead of 1, 1,1). Relevant asymptotic results are stated, proved, and evaluated using Monte Carlo simulations. The asymptotic results are general and may hence be used in similar empirical contexts using the same model structure. Parametric bootstrap inference is used in order to deal with test size distortions.

Abstract:
This paper studies the relation between macroeconomic fluctuations and corporate defaults while conditioning on industry affiliation and an extensive set of firm-specific factors. Using a multiperiod logit approach on a panel data set for all incorporated Swedish businesses over 1990-2002, we find strong evidence for a substantial and stable impact of aggregate fluctuations. Macroeffects differ across industries in an economically intuitive way. Out-of-sample evaluations show our approach is superior to both models that exclude macro information and best fitting naive forecasting models. While firm-specific factors are useful in ranking firms' relative riskiness, macroeconomic factors capture fluctuations in the absolute risk level.

Business cycles, Default, Default-risk model, Logit model, Macroeconomic variables, Micro-data

Abstract:
In this paper we empirically study interactions between real activity and the financial stance. Using aggregate data we examine a number of candidate measures of the financial stance of the economy. We find strong evidence for substantial spillover effects on aggregate activity from our preferred measure. Given this result, we use a large micro data-set for corporate firms to develop a macro-micro model of the interaction between the financial and real economy. This approach implies that the impulse responses of a given aggregate shock will depend on the portfolio structure of firms at any given point in time.

Default risk models, business cycles, price stability, financial stability, financial and real interaction

Abstract:
We study three necessary conditions for work sharing to increase employment. First, there must exist a negative long-run relation between working time and employment. Second, hours per worker must be exogenous with respect to wages and employment. Third, policy makers must be able to influence actual hours per worker. We formulate a theoretical model for employment, hours per worker, production, and real wages. A VAR system with cointegrating constraints is estimated by maximum likelihood using Swedish private sector data 1970-1-1990:4. We find: 1) no long-run relation between hours per worker and employment, 2) that hours per worker are endogenous with respect to the estimation of long-run parameters, and 3) that legislated working time and hours per worker are related to each other in the long run.