Corporate Credit Risk Premia

Considering the fundamental role played by small and medium sized enterprises (SMEs) in the economy of many countries and the considerable attention placed on SMEs in the new Basel Capital Accord, we develop a distress prediction model specifically for the SME sector and to analyse its effectiveness compared to a generic corporate model. The behaviour of financial measures for SMEs is analysed and the most significant variables in predicting the entities' credit worthiness are selected in order to construct a default prediction model. Using a logit regression technique on panel data of over 2,000 U.S. firms (with sales less than $65 million) over the period 1994-2002, we develop a one-year default prediction model. This model has an out-of-sample prediction power which is almost 30 per cent higher than a generic corporate model. An associated objective is to observe our model's ability to lower bank capital requirements considering the new Basel Capital Accord's rules for SMEs.

Encyclopedia of Systems and Control, 2014

The detailed proofs of most results can be found in papers by Bielecki and Rutkowski [20], Bielecki et al. [12, and Jeanblanc and Rutkowski . We also quote some of the seminal papers, but, unfortunately, we were not able to provide here a survey of an extensive research in the area of credit risk modeling. For more information, the interested reader is thus referred to original papers by other authors as well as to monographs by Ammann [2], Bluhm, Overbeck and Wagner [28], Bielecki and Rutkowski [20], Cossin and Pirotte [55], Duffie and Singleton [68], McNeil, Frey and Embrechts [123], Lando [109], or Schönbucher [138] which is valid for t ∈ [0, T [. As one might easily guess, this is a non-trivial mathematical problem, in general. In addition, the practical problem of the lack of direct observations of the value process V largely limits the applicability of the first-passage-time models based on the firm value process V . Merton's [124] research in several directions by taking into account such specific features of real-life debt contracts as: safety covenants, debt subordination, and restrictions on the sale of assets. Following Merton [124], they assume that the firm's stockholders

SSRN Electronic Journal, 2006

This paper provides new evidence on the empirical success of structural models in explaining corporate credit risk changes. A parsimonious set of common factors and firm-level fundamentals, inspired by structural models, explains more than 54% (67%) of the variation in credit spread changes for medium (low) grade bonds. No dominant latent factor is present in the unexplained variation. While our set of variables has lower explanatory power among high-grade bonds, it does capture most of the systematic variation of credit-spread changes in that category as well. It also subsumes the explanatory power of the Fama and French (1993) factors among all grade classes. Not necessarily. Studying a large and diverse cross-section of 2,375 domestic corporate bonds over the 1990-2003 period, which covers the full spectrum of credit ratings (from AAA to D), we demonstrate that structural models are impressively successful in explaining credit spread changes in the middle and low-grade bond segments. Specifically, they explain more than 54% and even 67% of individual bond credit spread changes in these categories, respectively. In the highest-grade tercile the explanatory power is about 35%. Explanatory power differs across bond classes partly due to the different role played by firm-level fundamentals such as volatility, leverage, and growth opportunities. These variables are particularly important in the low-grade segment, but they play little role in the high-grade segment. Moreover, our common factors capture twice as much variation in the low-grade tercile relative to the highest-grade tercile. Principal component analysis reveals no latent factor in the residual variation of low-and medium-grade bond portfolios and a strong latent factor in high-grade portfolios. However, analysis of individual bond regression residuals reveals virtually no common variation across any of the credit risk groups, providing solid evidence that structural models capture essentially all the systematic variation in individual bond credit spread changes for all credit risk classes. We provide additional evidence that idiosyncratic volatility and the price-tobook ratio have a strong basis in empirical corporate bond pricing. Campbell and Taksler (2003) document a synchronous upward trend in aggregate idiosyncratic volatility and aggregate credit spread levels. Pastor and Veronesi (2003) show that the priceto-book ratio and idiosyncratic volatility are both driven by uncertainty about the firm's future profitability. Since future profitability affects default probability in a structural model framework, Pastor and Veronesi (2003) establish a theoretical link between credit spread levels (and potentially changes), idiosyncratic volatility, and the price-to-book ratio. We provide fresh empirical evidence on this link by showing that changes in idiosyncratic volatility and the price-to-book ratio, both at the aggregate and firm level, are economically and statistically significant in explaining both crosssectional differences, as well as the time-series variation, in corporate credit spread changes. Our findings indicate that these variables should be considered along with more traditional ones in studies of credit risk changes at the individual bond level.

Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l'Administration, 2008

Centre interuniversitaire sur le risque, les politiques économiques et l'emploi Cahier de recherche/Working Paper 06-13

2019

This book was prepared for the Finance Master program of the Corvinus University of Budapest started in the academic year 2019/2020. The book consists of two main parts, the first part deals with corporate finance and financing issues, while the second part covers risk management and liquidity management in financial markets. The cases in this book highly build on the knowledge base of the master’s program curriculum, therefore, it is imperative for students to familiarize themselves with the basic notions first, before starting to solve the exercises. If you experience any knowledge gaps, then refer to the regular textbooks before solving the cases. In several cases, the related regulations should also be read in conjunction with the case in order to be able to understand and solve the exercises. This highlights the ever increasing relevance of regulation in the finance industry. Apart from the knowledge of the financial notions, and related regulations, students should also be ski...

In this paper we focus on the analysis of the effect of prediction and estimation risk on the loss distribution, risk measures and economic capital. When variables for the determination of probability of default and loss distribution have to be predicted because they are not available at the time the prediction is made, the prediction is prone to errors. The model parameters for the estimation of probability of default or asset correlation are not available, and usually have to be estimated using historical data. The incorporation of prediction and estimation risk generally leads to broader loss distributions and therefore to rising values of risk parameters such as Value at Risk or Expected Shortfall. The level of economic capital required may be strongly underestimated if prediction and estimation risk are ignored.

2004

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 counterparts 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 macroeconomic stance 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 derive two measures of portfolio credit risk, Value-at-Risk-type and Expected Shortfall, by means of a Monte-Carlo simulation method that employs model-based probabilities of default. This two-step approach allows us to (i) make individual forecasts of default risk conditional on firm and loan characteristics, as well as prevailing macroeconomic conditions, (ii) study the evolution of portfolio credit risk over time while conditioning on the macroeconomy. 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 pin down the absolute level of (default, and thus also credit) risk.

Journal of Banking & …, 2007

Despite a surge in the research efforts put into modeling credit and default 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, loanrelated 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 risk.

1997

I wish to thank my thesis advisors BertH Niislund, Tomas Bjork and Peter Jennergren for making this work possible. Kerstin Lindskog and Anki Helmer have helped with more matters than I have deserved. Thanks are also due to Mike Burkart, Gustaf Hagerud, Pelle Stromberg for helpful comments and constructive criticisms. Sune Karlsson deserves recognition for his constant willingness to provide clear and concise answers to queries related to econometrics. Patrik Slifvenblad has helped me with the finer points of~'IF) C.

Journal of Banking & Finance, 2020

This paper examines the predictive power of the main default-risk measures used by both academics and practitioners, including accounting measures, market-price-based measures and the credit rating. Given that some measures are unavailable for some firm types, pair wise comparisons are made between the various measures, using same-size samples in every case. The results show the superiority of market-based measures, although their accuracy depends on the prediction horizon and the type of default events considered. Furthermore, examination shows that the effect of withinsample firm characteristics varies across measures. The overall finding is of poorer goodness of fit for accurate default prediction in samples characterised by high book-to-market ratios and/or high asset intangibility, both of which suggest pricing difficulty. In the case of large-firm samples, goodness of fit is in general negatively related to size, possibly because of the "too-big-to-fail" effect.