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189
Macroeconomic dynamics and credit risk: A global perspective
 Journal of Money Credit and Banking
, 2006
"... 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 o ..."
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Cited by 37 (8 self)
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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 firmspecific heterogeneity as well as generate multiperiod 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 nonnormality on credit risk. We show that the effects of such shocks on losses are asymmetric and nonproportional, reflecting the highly nonlinear nature of the credit risk model. Nonnormal innovations such as Student t generate expected and unexpected losses which increase the fatter the tails of the innovations.
The Aggregate Demand for Treasury Debt
, 2008
"... Investors value the liquidity and safety of U.S. Treasury bonds. We document this by showing that changes in Treasury supply have large effects on a variety of yield spreads. As a result, Treasury yields are reduced by 72 basis points, on average over the period from 19262008. The low yield on Trea ..."
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Cited by 33 (1 self)
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Investors value the liquidity and safety of U.S. Treasury bonds. We document this by showing that changes in Treasury supply have large effects on a variety of yield spreads. As a result, Treasury yields are reduced by 72 basis points, on average over the period from 19262008. The low yield on Treasuries due to their extreme safety and liquidity suggests that Treasuries in important respects are similar to money. Evidence from quantities supports this idea. When the supply of Treasuries falls, reducing the overall supply of liquid and safe assets, the supply of bankissued money rises.
Default risk and diversification: Theory and applications
 Mathematical Finance
, 2002
"... 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 ..."
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Cited by 32 (5 self)
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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 mortgagebacked securities.
Liquidity Risk Premia in Corporate Bond Markets. Working Paper
, 2005
"... This paper explores the role of liquidity risk in the pricing of corporate bonds. We show that corporate bond returns have significant exposures to fluctuations in treasury bond liquidity and equity market liquidity. Further, this liquidity risk is a priced factor for the expected returns on corpora ..."
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Cited by 32 (1 self)
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This paper explores the role of liquidity risk in the pricing of corporate bonds. We show that corporate bond returns have significant exposures to fluctuations in treasury bond liquidity and equity market liquidity. Further, this liquidity risk is a priced factor for the expected returns on corporate bonds, and the associated liquidity risk premia help to explain the credit spread puzzle. In terms of expected returns, the total estimated liquidity risk premium is around 0.6 % per annum for US longmaturity investment grade bonds. For speculative grade bonds, which have higher exposures to the liquidity factors, the liquidity risk premium is around 1.5 % per annum. We find very similar evidence for the liquidity risk exposure of corporate bonds for a sample of European corporate bond prices. ∗ We are grateful to Inquire Europe for financial support. We thank Viral Acharya, Michael
How the Subprime Crisis Went Global: Evidence from Bank Credit Default Swap Spreads,” NBER Working Paper No. 14904
, 2009
"... How did the Subprime Crisis, a problem in a small corner of U.S. financial markets, affect the entire global banking system? To shed light on this question we use principal components analysis to identify common factors in the movement of banks ’ credit default swap spreads. We find that fortunes of ..."
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Cited by 30 (4 self)
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How did the Subprime Crisis, a problem in a small corner of U.S. financial markets, affect the entire global banking system? To shed light on this question we use principal components analysis to identify common factors in the movement of banks ’ credit default swap spreads. We find that fortunes of international banks rise and fall together even in normal times along with shortterm global economic prospects. But the importance of common factors rose steadily to exceptional levels from the outbreak of the Subprime Crisis to past the rescue of Bear Stearns, reflecting a diffuse sense that funding and credit risk was increasing. Following the failure of Lehman Brothers, the interdependencies briefly increased to a new high, before they fell back to the preLehman elevated levels – but now they more clearly reflected heightened funding and counterparty risk. After Lehman’s failure, the prospect of global recession became imminent, auguring the further deterioration of banks ’ loan portfolios. At this point the entire global financial system had become infected. 1
The RiskAdjusted Cost of Financial Distress
 JOURNAL OF FINANCE
, 2007
"... 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 riskadjusted default probabilities derived from corporate bond spreads. For a BBBrated firm, our benchmark calculations show that the riskad ..."
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Cited by 27 (2 self)
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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 riskadjusted default probabilities derived from corporate bond spreads. For a BBBrated firm, our benchmark calculations show that the riskadjusted NPV of distress is 4.5 % of predistress firm value. In contrast, a valuation that ignores risk premia produces an NPV of 1.4%. We show that riskadjusted, 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.
Understanding the Role of Recovery in Default Risk Models: Empirical Comparisons and Implied Recovery Rates
, 2006
"... This article presents a framework for studying the role of recovery on defaultable debt prices for a wide class of processes describing recovery rates and default probability. These debt models have the ability to differentiate the impact of recovery rates and default probability, and can be employe ..."
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Cited by 26 (0 self)
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This article presents a framework for studying the role of recovery on defaultable debt prices for a wide class of processes describing recovery rates and default probability. These debt models have the ability to differentiate the impact of recovery rates and default probability, and can be employed to infer the market expectation of recovery rates implicit in bond prices. Empirical implementation of these models suggests two central findings. First, the recovery concept that specifies recovery as a fraction of the discounted par value has broader empirical support. Second, parametric debt valuation models can provide a useful assessment of recovery rates embedded in bond prices.
Forecasting Default with the KMVMerton Model, Working paper
, 2004
"... 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 KMVMerton model to a similar but much simpler alternative, we find that it performs slightly worse as a predictor in hazard model ..."
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Cited by 26 (0 self)
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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 KMVMerton 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 KMVMerton default probabilities out of sample. Implied default probabilities from credit default swaps and corporate bond yield spreads are only weakly correlated with KMVMerton default probabilities after adjusting for agency ratings, bond characteristics, and our alternative predictor. We conclude that the KMVMerton 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 KMVMerton model. We include the SAS code we use to calculate KMVMerton default probabilities in an appendix.
Structural Models of Credit Risk are Useful: Evidence from
 Journal of Financial Economics
, 2004
"... Credit Management for help with the data. We are also grateful for helpful comments to participants at a University of Verona conference and a seminar at the QGroup. We are responsible for all remaining errors. ..."
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Cited by 24 (1 self)
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Credit Management for help with the data. We are also grateful for helpful comments to participants at a University of Verona conference and a seminar at the QGroup. We are responsible for all remaining errors.
Explaining the level of credit spreads: optionimplied jump risk premia in a firm value model
, 2005
"... Prices of equity index put options contain information on the price of systematic downward jump risk. We use a structural jumpdiffusion firm value model to assess the level of credit spreads that is generated by optionimplied jump risk premia. In our compound option pricing model, an equity index ..."
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Cited by 22 (2 self)
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Prices of equity index put options contain information on the price of systematic downward jump risk. We use a structural jumpdiffusion firm value model to assess the level of credit spreads that is generated by optionimplied jump risk premia. In our compound option pricing model, an equity index option is an option on a portfolio of call options on the underlying firm values. We calibrate the model parameters to historical information on default risk, the equity premium and equity return distribution, and S&P 500 index option prices. Our results show that a model without jumps fails to fit the equity return distribution and option prices, and generates a low outofsample prediction for credit spreads. Adding jumps and jump risk premia improves the fitofthe model in terms of equity and option characteristics considerably and brings predicted credit spread levels much closer to observed levels.