This paper estimates recent default risk premia for U.S. corporate debt, based on a close relationship between default probabilities, as estimated by Moody's KMV EDFs, and default swap (CDS) market rates. The default-swap data, obtained through CIBC from 22 banks and specialty dealers, allow us to establish a strong link between actual and risk-neutral default probabilities for the 69 firms in the three sectors that we analyze: broadcasting and entertainment, healthcare, and oil and gas. We find dramatic variation over time in risk premia, from peaks in the thrid quarter of 2002, dropping by roughly 50% to late 2003.

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helpful comments on earlier drafts of this paper. Needless to say we are fully responsible for the content of the paper. 1 Merton’s Model, Credit Risk, and Volatility Skews In 1974 Robert Merton proposed a model for assessing the credit risk of a company by characterizing the company’s equity as a call option on its assets. In this paper we propose a way the model’s parameters can be estimated from the implied volatilities of options on the company’s equity. We use data from the credit default swap market to compare our implementation of Merton’s model with the traditional implementation approach. 2

We provide maximum likelihood estimators of term structures of conditional probabilities of bankruptcy over relatively long time horizons, incorporating the dynamics of firm-specific and macroeconomic covariates. We find evidence in the U.S. industrial machinery and instruments sector, based on over 28,000 firm-quarters of data spanning 1971 to 2001, of significant dependence of the level and shape of the term structure of conditional future bankruptcy probabilities on a firm's distance to default (a volatility-adjusted measure of leverage) and on U.S. personal income growth, among other covariates. Variation in a firm's distance to default has a greater relative e#ect on the term structure of future failure hazard rates than does a comparatively sized change in U.S. personal income growth, especially at dates more than a year into the future.

This paper shows that the probability of extreme default losses on portfolios of U.S. corporate debt is much greater than would be estimated under the standard assumption that default correlation arises only from exposure to observable risk factors. At the high confidence levels at which bank loan portfolio and CDO default losses are typically measured for economic-capital and rating purposes, our empirical results indicate that conventionally based estimates are downward biased by a full order of magnitude on test portfolios. Our estimates are based on U.S. public non-financial firms existing between 1979 and 2004. We find strong evidence for the presence of common latent factors, even when controlling for observable factors that provide the most accurate available model of firm-by-firm default probabilities. ∗ We are grateful for financial support from Moody’s Corporation and Morgan Stanley, and for research assistance from Sabri Oncu and Vineet Bhagwat. We are also grateful for remarks from Torben Andersen, André Lucas, Richard Cantor, Stav Gaon, Tyler Shumway, and especially Michael Johannes. This revision is much improved because of suggestions by a referee, an associate editor, and Campbell Harvey. We are thankful to Moodys and to Ed Altman for generous assistance with data. Duffie is at The Graduate School of Business, Stanford University. Eckner and Horel are at Merrill Lynch. Saita is at Lehman

Some modified structural and reduced-form models of credit risk implicitly assume that the market has less information than managers who declare default on their outstanding debt. As a result the announcement of default or disclosure of information that indicates a firm is in distress comes as a “surprise ” to the market. In this paper, we study the extent to which private information is revealed about a firm when it announces information indicating distress. The presence of this private information can be inferred from the extent to which investors can earn abnormal returns on bonds or equities issued by firms announcing distress or default. We analyze how much of the information revealed through the declaration of a credit event is publicly available before a specific announcement of credit difficulties. Using default probabilities supplied by Moody’s KMV (MKMV), known as the Expected Default Frequency�or the EDF�credit measure, we model market expectations regarding the firm’s likelihood of default. We then measure the impact of information revealed through an adverse credit event conditional on this expectation. We find that conditioning on EDF credit measures, only 11 % of the distressed firms’ equities and 18 % of the distressed bonds (belonging to 25 % of the distressed firms) display a

This paper investigates the source for common variation in the portion of re-turns observed in U.S. credit markets that is not related to changes in risk-free rates or expected default losses. We extract a latent common component from firm-specific changes in default risk premia that is orthogonal to known sys-tematic risk factors during our sample period from 2001 to 2004. Asset pricing tests using returns on Bloomberg-NASD corporate bond indices suggest that our discovered latent changes in default risk premia (DRP) factor is priced in the corporate bond market. A cross-sectional analysis of Merrill Lynch cor-porate bond portfolios sorted on either industry, maturity or rating supports these findings. In our tests we control for firm characteristics and find that the common variation in changes in default risk premia is not likely to be due to these. Using portfolios of put options written on the S&P 500 index and sorted on moneyness and maturity, we find that, for far-out-of-the-money op-tions, both average returns and the beta estimate for our DRP factor increase with increasing time to maturity. The same holds true for out-of-the-money and at-the-money index put options. There is little to no evidence, however, of the DRP factor being priced in the equity markets. We develop a theoretical framework that, while the DRP factor is part of the pricing kernel, supports our empirical findings. It shows that the DRP factor captures the jump-to-default risk associated with market-wide credit events. ∗ We are grateful to Moody’s KMV for access to Moody’s KMV EDF data, and to Markit Group Limited for providing us with data on credit default swap rates. We thank seminar participants

The volume of outstanding OTC derivatives has grown exponentially over the past 15 years. Market surveys conducted by the International Swaps and Derivatives Association (ISDA) show notional amounts of outstanding interest rate and currency swaps reaching US$866 billion in 1987, US$17.7 trillion in 1995, and US$99.8 trillion in 2002; an astonishing compounded

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This paper assesses whether ratings or market-based credit risk measures are more suitable for formulating portfolio governance rules. Such rules, which consist of buy and sell restrictions, are commonly used in investment management. Based on data from 1983 to 2002, it is not evident that one of the two measures is superior. The relative power of the two measures in predicting defaults depend on the investor’s investment horizon and risk appetite. The results support the agencies ' claim that their policy of reducing rating volatility, which builds on the though-the-cycle approach and the avoidance of frequent rating reversals, is beneficial to bond investors. The results also suggest that widely used statistical measures of rating quality may be insufficient to judge the economic value of rating information in specific contexts.