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This paper explores the nature of default arrival and recovery implicit in the term structures of sovereign CDS spreads. We argue that term structures of spreads reveal not only the arrival rates of credit events (λ Q), but also the loss rates given credit events. Applying our framework to Mexico, Turkey, and Korea, we show that a single-factor model with λ Q following a lognormal process captures most of the variation in the term structures of spreads. The risk premiums associated with unpredictable variation in λ Q are found to be economically significant and co-vary importantly with several economic measures of global event risk, financial market volatility, and macroeconomic policy. THE BURGEONING MARKET FOR SOVEREIGN CREDIT DEFAULT SWAPS (CDS) contracts offers a nearly unique window for viewing investors ’ risk-neutral probabilities of major credit events impinging on sovereign issuers, and their risk-neutral losses of principal in the event of a restructuring or repudiation of external debts. In contrast to many “emerging market ” sovereign bonds, sovereign CDS

Investors demand high risk premia for defaultable claims, because (i) defaults tend to con-centrate in bad times when marginal utility is high; (ii) default losses are high during such times. I build a structural model of financing and default decisions in an economy with business-cycle variations in expected growth rates and volatility, which endogenously generate countercyclical comovements in risk prices, default probabilities, and default losses. Credit risk premia in the calibrated model not only can quantitatively account for the high corporate bond yield spreads and low leverage ratios in the data, but have rich implications for firms ’ financing decisions. Risks associated with macroeconomic conditions are crucial for understanding asset prices. Naturally, they should also have important implications for corporate decisions. By introducing macroeconomic conditions into firms ’ financing decisions, this paper provides a risk-based expla-

We examine the accuracy and contribution of the default forecasting model based on Merton’s (1974) bond pricing model and developed by the KMV corporation. Comparing the KMV-Merton model to a similar but much simpler alternative, we find that it performs slightly worse as a predictor in hazard models and in out of sample forecasts. Moreover, several other forecasting variables are also important predictors, and fitted hazard model values outperform KMV-Merton default probabilities out of sample. Implied default probabilities from credit default swaps and corporate bond yield spreads are only weakly correlated with KMV-Merton default probabilities after adjusting for agency ratings, bond characteristics, and our alternative predictor. We conclude that the KMV-Merton model does not produce a sufficient statistic for the probability of default, and it appears to be possible to construct such a sufficient statistic without solving the simultaneous nonlinear equations required by the KMV-Merton model. We include the SAS code we use to calculate KMV-Merton default probabilities in an appendix.

This paper presents computational techniques that make a certain class of fully dynamic intensity-based models for portfolio credit risk, along the lines of Duffie and Gârleanu (2001) and Mortensen (2006), just as computationally tractable as the static copula model. Compared to previous such models in the literature, we improve the fit to CDX tranche spreads by a factor of around five, by explicitly taking liquidity and modified-restructuring risk into account, and by allowing for a more flexible correlation structure. The resulting model can be used to hedge a wide range of risks in the credit market, such as the risk of changes in correlations, volatilities, or idiosyncratic default risk.

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This paper analyzes the empirical relationship between credit default swap, bond and stock markets during the period 2000-2002. Focusing on the intertemporal comovement, we examine weekly and daily lead-lag relationships in a vector autoregressive model and the adjustment between markets caused by cointegration. First, we find that stock returns lead CDS and bond spread changes. Second, CDS spread changes Granger cause bond spread changes for a higher number of firms than vice versa. Third, the CDS market is significantly more sensitive to the stock market than the bond market and the magnitude of this sensitivity increases when credit quality becomes worse. Finally, the CDS market plays a more important role for price discovery than the corporate bond market.

This paper explores the determinants of corporate failure and the pricing of financially distressed stocks whose failure probability, estimated from a dynamic logit model using accounting and market variables, is high. Since 1981, financially distressed stocks have delivered anomalously low returns. They have lower returns but much higher standard deviations, market betas, and loadings on value and small-cap risk factors than stocks with low failure risk. These patterns are more pronounced for stocks with possible informational or arbitrage-related frictions. They are inconsistent with the conjecture that value and size e¤ects are compensation for the risk of financial distress.

Financial distress is more likely to happen in bad times. The present value of distress costs therefore depends on risk premia. We estimate this value using risk-adjusted default probabilities derived from corporate bond spreads. For a BBB-rated firm, our benchmark calculations show that the risk-adjusted NPV of distress is 4.5 % of pre-distress firm value. In contrast, a valuation that ignores risk premia produces an NPV of 1.4%. We show that risk-adjusted, marginal distress costs can be as large as the marginal tax benefits of debt derived by Graham (2000). Thus, distress risk premia can help explain why firms appear to use debt conservatively.

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