SPEAKER BIOS Viral Acharya Kent D. Daniel John C. Hull Kenneth J. Singleton Deepak Agrawal Darrell Duffie David Keisman Tyler Shumway Edward I. Altman Jan Ericsson David Lando Roger M. Stein Jeffrey R. Bohn Joost Driessen Francis A. Longstaff Marti Subrahmanyam Richard Cantor Bjorn Flesaker Raymond W. McDaniel Rangarajan Sundaram George C. Chacko Lorenzo Garlappi Lasse H. Pedersen M. Suresh Sundaresan Pierre Collin-Dufresne Timothy F. Geithner Stephen Schaefer Alan D. White Thomas Cooley Jens Hilscher Myron S. Scholes   ABSTRACTS & PAPERS Liquidity Risk Premia in Corporate Bond Markets  Frank de Jong and Joost Driessen This paper explores the role of liquidity risk in the pricing of corporate bonds. We show that liquidity is a priced factor in a multifactor model for the expected returns on corporate bonds. The exposures of corporate bond returns to fluctuations in Treasury bond liquidity and equity market liquidity help to explain the credit spread puzzle. For the US market, the total estimated liquidity premium is around 45 basis points for long-maturity investment grade bonds. For speculative grade bonds, which have higher exposures to the liquidity factors, the liquidity premium is around 100 basis points. Finally, we find very similar evidence for the liquidity risk exposure of corporate bonds using a sample of European corporate bond prices. The Determinants of Liquidity in the Corporate Bond Markets: An Application of Latent Liquidity  George Chacko, Sriketan Mahanti, Gaurav Mallik and Marti Subrahmanyam A great deal of work has focused on market microstructure, but relatively little work has been devoted to the study of risk associated with liquidity. The work that has been done has almost exclusively focused on US equities-primarily because that market is fairly liquid and therefore data is plentiful. However, because that market is liquid, the empirical results been mixed. For our work, we use a unique database of US corporate bond transactions and holdings. Because the corporate bond market is several orders of magnitude more illiquid than the equity market, this seems a much more appropriate setting to study the effects of illiquidity. To get around the problem of a lack of trading (and therefore data), we construct a new measure of liquidity which does not require trading. Using this measure, we show that not only is liquidity risk priced, but that the effects of liquidity risk are quite pervasive and need to be controlled for carefully when doing virtually any analysis of security returns. Default Risk, Shareholder Advantage, and Stock Returns  Lorenzo Garlappi, Tao Shu and Hong Yan In this paper, we analyze the relationship between default probability and stock returns. Using the market-based measure of Expected Default Frequency™ (EDF™) constructed by Moody's KMV, we first demonstrate that higher default probabilities are not necessarily associated with higher expected stock returns, a finding that complements the existing evidence based on alternative measures of default probability. We then show that the puzzling and complex relationship between stock returns and default probability is consistent with the implications of existing structural models of default that explicitly account for the renegotiation between equity-holders and debt-holders, and hence for the deviation from the absolute priority rule upon default. We derive an analytical relationship between expected returns and default probability based on one such model (Fan and Sundaresan (2000)). Our analysis implies that distressed firms in which shareholders have a stronger advantage in renegotiation should exhibit lower expected returns, and default risk to equity is not properly represented by default probability alone. We test this implication using several proxies for shareholder advantage and find strong support in the data. The data do not seem to support, conversely, the hypothesis that this relationship is caused by market mispricing of financially distressed firms. Our study highlights the effect of strategic interactions between firm's claimants on stock returns, and provides a novel understanding of the link between default risk and stock returns. In Search of Distress Risk  John Y. Campbell, Jens Hilscher, and Jan Szilagyi This paper explores the determinants of corporate failure and the pricing of financially distressed stocks using US data over the period 1963 to 2003. Firms with higher leverage, lower profitability, lower market capitalization, lower past stock returns, more volatile past stock returns, lower cash holdings, higher market-book ratios, and lower prices per share are more likely to file for bankruptcy, be delisted, or receive a D rating. When predicting failure at longer horizons, the most persistent firm characteristics, market capitalization, the market-book ratio, and equity volatility become relatively more significant. Our model captures much of the time variation in the aggregate failure rate. 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 a low risk of failure. These patterns hold in all size quintiles but are particularly strong in smaller stocks. They are inconsistent with the conjecture that the value and size effects are compensation for the risk of financial distress. Can Structural Models Price Default Risk? Evidence from Bond and Credit Derivative Markets  Jan Ericsson, Joel Reneby and Hao Wang Using a set of structural models, we evaluate bond yield spreads and the price of default protection for a sample of US corporations. Theory predicts that if credit risk alone explains these two quantities, their magnitudes should be similar. Our findings concur with previous results that bond yield spreads are underestimated. However, this is not systematically the case for CDS premia, which in our dataset are much lower than bond spreads. Furthermore, our results highlight the strong relationship between bond residuals and nondefault proxies, in particular illiquidity. CDS residuals exhibit no such relations. This suggests that the bond spread underestimation by our structural models may not stem from their inability to properly account for default risk, but rather from the importance of the omitted risk factors. Forecasting Default with the KMV-Merton Model  Sreedhar T. Bharath and Tyler Shumway 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. Measuring Systematic Risk in Recoveries on Defaulted Debt I: Firm-Level Ultimate LGDs  Mark Carey and Michael Gordy Several recent empirical papers report evidence of significant systematic variation in recovery rates on defaulted corporate debt, implying that the convenient assumption of independent recovery rates found in most defaultable debt pricing models and portfolio credit risk models is unrealistic. However, such work has used recoveries on individual assets. These are claims on the value of the bankrupt firm at emergence, so systematic variation in such firm value is the most natural source of systematic variation in recoveries. We examine the aggregate recovery at emergence on the debt of each firm in a sample of bankrupt firms. We find mixed evidence of systematic variation. Such evidence is driven largely by experience in a single historical episode and point estimates and statistical significance are sensitive to details of the empirical specification. Our evidence about predictors of recovery suggests that interactions between the default decision and recovery rates may be more complex than existing models imply. Humpbacks in Credit Spreads  Deepak Agrawal and Jeffrey R. Bohn Models of credit valuation generally predict a hump-shaped spread term structure for low quality issuers. This is understood to be driven by the shape of the underlying conditional default probabilities curve. We show that (a) recovery assumptions and (b) deviation of bond's price from par can also drive different term structure shapes. On examining a large set of speculative grade bonds and credit default swaps, we find evidence that par- spread term structures are likely to be downward sloping as credit quality deteriorates sufficiently. Our analysis explains the various theoretical results and resolves conflicting empirical evidence on the shape of speculative grade spread curves. An Empirical Analysis of the Pricing of Collateralized Debt Obligations  Francis A. Longstaff and Arvind Rajan We study the pricing of collateralized debt obligations (CDOs) using an extensive new data set for the actively-traded CDX credit index and its tranches. We find that a three-factor portfolio credit model allowing for firm-specific, industry, and economywide default events explains virtually all of the time-series and crosssectional variation in CDX index tranche prices. These tranches are priced as if losses of 0.4, 6, and 35 percent of the portfolio occur with expected frequencies of 1.2, 41.5, and 763 years, respectively. On average, 65 percent of the CDX spread is due to firm-specific default risk, 27 percent to clustered industry or sector default risk, and 8 percent to catastrophic or systemic default risk. Recently, however, firm-specific default risk has begun to play a larger role. Frailty Correlated Default Times  Darrell Duffie, Andreas Eckner, Guillaume Horel and Leandro Saita We analyze portfolio credit risk in light of incompletely observed default covariates. There are reasons to believe that the usual assumption that all relevant covariates have been incorporated into a standard duration-based model of default probabilities and default correlations may bias the model, and may lead to lower precision, especially when forecasting aggregate default rates. There are potentially important implications for default correlation across issuers, in that common dependence on unobservable covariates introduces an additional channel of default correlation. Standard models tend to under-predict default correlation. Our model incorporates a time-varying latent factor, common to all companies, that is driven by an unobservable Brownian motion. Compared to standard models, we find that our model implies higher cross-sectional default correlation, and generates much fatter tails in the aggregate default distribution of portfolios of corporate credit. In particular, the model is able to capture the spike in corporate default rates in 2001 and 2002.