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. 1 We are exceptionally grateful to Michael Harrison for his significant contributions to this paper, which are noted within. We are also grateful for insightful research assistance

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This is the first study that computes default measures for individual firms using Merton’s (1974) option pricing model, to assess the effect that default risk has on equity returns. We find that equally-weighted portfolios of stocks with high default probability earn significantly higher returns than equally-weighted portfolio of stocks with low default probability. In addition, both the size and book-to-market effects are present only within the portfolio of stocks with the highest default probabilities. Once stocks with the 30 % highest default probabilities are excluded from the sample, both size and B/M effects disappear. We also find that default risk is priced and can explain part of the cross-sectional variation in returns. The Fama-French factors SMB and HML, and particularly SMB, contain some default-related information, although it appears that this information is not the driving force behind the success of the Fama-French model. Keywords: default risk, equity returns, Merton’s (1974) model, size and book-to-market. JEL classification: G33, G12 1

1 We are very grateful to Kumar Visvanathan for graciously sharing the data on foreign currency derivatives. We also greatly appreciate comments received by Yakov Amihud, Pierluigi Balduzzi,

conversations.

This study compares eight international failure prediction models on one data set of Belgian company accounts, using performance indicators based on the inequality principle and performance measures based on a classification rule. After a brief theoretical review of the two basic modelling techniques in failure prediction research and the performance measures used to evaluate them, we report type I and type II error rates corresponding with the original cut-off point and calculate new optimal cut-off points, as well as Gini-coefficients. A wide range of performances was observed for the different models. However the models estimated on a sample of Continental European companies are found to be better performing when validated on a sample of Continental European, i.e. Belgian companies, than the Anglo-Saxon models. A remarkable finding is also that the Greek Gloubos-Grammaticos models show better predictive ability when validated on samples of Belgian failing and non-failing companies than on their own (Greek) validation samples. Another important finding is the robustness of the older discriminant models and the models that were estimated on bigger companies. The validation shows that very simple models can have great predictive ability. 2

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.

Faced with the question whether the Belgian failure prediction models by Ooghe, Joos and De Vos (1991) can be easily applied in all industries and for all sizeclasses, this study compares the performance of the OJD models across 18 different industries and different sizeclasses. After a brief theoretical review of the logistic regression modelling technique, which was used to design the OJD 1991 models, and the performance measures that are used to evaluate these models, we report type I and type II error rates corresponding with the original cut-off points of the models. Furthermore, we calculate new optimal cut-off points, as well as Ginicoefficients. Finally we report the reductions in unweighted error rates when using the new cut-off points instead of the original ones, and the graphs of the trade-off functions. As can be concluded from the performance results and the trade-off functions, there’s a wide range of performances for the different industries. However, we notice that the OJD 1991 models perform best for classical manufacturing industries- such as chemicals, paper and printing, textiles and apparel, paper and printing and metal- and financial services., while the models show the worst performance for service industries- such as real estate, hotel,

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.

This paper is adapted and updated from E. Altman, "Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy," Journal of Finance, September 1968; and E. Altman, R. Haldeman and P. Narayanan, "Zeta Analysis: A New Model to Identify Bankruptcy Risk of Corporations," Journal of Banking & Finance, 1, 1977. Predicting Financial Distress of Companies: Revisiting the Z-Score and ZETA Models Background This paper discusses two of the venerable models for assessing the distress of industrial corporations. These are the so-called Z-Score model (1968) and ZETA 1977) credit risk model. Both models are still being used by practitioners throughout the world. The latter is a proprietary model for subscribers to ZETA Services, Inc. (Hoboken, NJ). The purpose of this summary are two-fold. First, those unique characteristics of business failures are examined in order to specify and quantify the variables which are effective indicators and predictors of corporate distress. By doing so, I hope to highlight the analytic as well as the practical value inherent in the use of financial ratios. Specifically, a set of financial and economic ratios will be analyzed in a corporate distress prediction context using a multiple discriminant statistical methodology. Through this exercise, I will explore not only the quantifiable characteristics of potential bankrupts but also the utility of a much-maligned technique of financial analysis: ratio analysis. Although the models that we will discuss were developed in the late 1960's and mid-1970's, I will extend our tests and findings to include application to firms not traded publicly, to non-manufacturing entities, and also refer to a new bond-rating equivalent model for emerging markets corporate bonds. The latter util...