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227
The Determinants of Credit Spread Changes
, 2001
"... Using dealer’s quotes and transactions prices on straight industrial bonds, we investigate the determinants of credit spread changes. Variables that should in theory determine credit spread changes have rather limited explanatory power. Further, the residuals from this regression are highly crossco ..."
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Cited by 401 (2 self)
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Using dealer’s quotes and transactions prices on straight industrial bonds, we investigate the determinants of credit spread changes. Variables that should in theory determine credit spread changes have rather limited explanatory power. Further, the residuals from this regression are highly crosscorrelated, and principal components analysis implies they are mostly driven by a single common factor. Although we consider several macroeconomic and financial variables as candidate proxies, we cannot explain this common systematic component. Our results suggest that monthly credit spread changes are principally driven by local supply0 demand shocks that are independent of both creditrisk factors and standard proxies for liquidity.
Structural Models of Corporate Bond Pricing: An Empirical Analysis
, 2003
"... This paper empirically tests five structural models of corporate bond pricing: those of Merton (1974), Geske (1977), Leland and Toft (1996), Longsta# and Schwartz (1995), and CollinDufresne and Goldstein (2001). We implement the models using a sample of 182 bond prices from firms with simple capita ..."
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Cited by 233 (5 self)
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This paper empirically tests five structural models of corporate bond pricing: those of Merton (1974), Geske (1977), Leland and Toft (1996), Longsta# and Schwartz (1995), and CollinDufresne and Goldstein (2001). We implement the models using a sample of 182 bond prices from firms with simple capital structures during the period 19861997. The conventional wisdom is that structural models do not generate spreads as high as those seen in the bond market, and true to expectations we find that the predicted spreads in our implementation of the Merton model are too low. However, most of the other structural models predict spreads that are too high on average. Nevertheless, accuracy is a problem, as the newer models tend to severely overstate the credit risk of firms with high leverage or volatility and yet su#er from a spread underprediction problem with safer bonds. The Leland and Toft model is an exception in that it overpredicts spreads on most bonds, particularly those with high coupons. More accurate structural models must avoid features that increase the credit risk on the riskier bonds while scarcely a#ecting the spreads of the safest bonds.
Macroeconomic conditions and the puzzles of credit spreads and capital structure
, 2008
"... Investors demand high risk premia for defaultable claims, because (i) defaults tend to concentrate 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 businesscycle variations in ..."
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Cited by 103 (12 self)
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Investors demand high risk premia for defaultable claims, because (i) defaults tend to concentrate 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 businesscycle 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.
Term structure dynamics in theory and reality
 Review of Financial Studies
, 2003
"... This paper is a critical survey of models designed for pricing fixed income securities and their associated term structures of market yields. Our primary focus is on the interplay between the theoretical specification of dynamic term structure models and their empirical fit to historical changes in ..."
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Cited by 101 (11 self)
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This paper is a critical survey of models designed for pricing fixed income securities and their associated term structures of market yields. Our primary focus is on the interplay between the theoretical specification of dynamic term structure models and their empirical fit to historical changes in the shapes of yield curves. We begin by overviewing the dynamic term structure models that have been fit to treasury or swap yield curves and in which the risk factors follow diffusions, jumpdiffusion, or have “switching regimes. ” Then the goodnessoffits of these models are assessed relative to their abilities to: (i) match linear projections of changes in yields onto the slope of the yield curve; (ii) match the persistence of conditional volatilities, and the shapes of term structures of unconditional volatilities, of yields; and (iii) to reliably price caps, swaptions, and other fixedincome derivatives. For the case of defaultable securities we explore the relative fits to historical yield spreads. 1
Extensions to the Gaussian copula: random recovery and random factor loadings
 JOURNAL OF CREDIT RISK
, 2004
"... This paper presents two new models of portfolio default loss that extend the standard Gaussian copula model yet preserve tractability and computational efficiency. In one extension, we randomize recovery rates, explicitly allowing for the empirically wellestablished effect of inverse correlation be ..."
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Cited by 90 (0 self)
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This paper presents two new models of portfolio default loss that extend the standard Gaussian copula model yet preserve tractability and computational efficiency. In one extension, we randomize recovery rates, explicitly allowing for the empirically wellestablished effect of inverse correlation between recovery rates and default frequencies. In another extension, we build into the model random systematic factor loadings, effectively allowing default correlations to be higher in bear markets than in bull markets. In both extensions, special cases of the models are shown to be as tractable as the Gaussian copula model and to allow efficient calibration to market credit spreads. We demonstrate that the models – even in their simplest versions – can generate highly significant pricing effects such as fat tails and a correlation “skew ” in synthetic CDO tranche prices. When properly calibrated, the skew effect of random recovery is quite minor, but the extension with random factor loadings can produce correlation skews similar to the steep skews observed in the market. We briefly discuss two alternative skew models, one based on the MarshallOlkin copula, the other on a spreaddependent correlation specification for the Gaussian copula.
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 73 (3 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.
Liquidity and credit risk
 Journal of Finance
, 2006
"... We develop a structural bond valuation model to simultaneously capture liquidity and credit risk. Our model implies that renegotiation in financial distress is influenced by the illiquidity of the market for distressed debt. As default becomes more likely, the components of bond yield spreads attrib ..."
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Cited by 64 (0 self)
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We develop a structural bond valuation model to simultaneously capture liquidity and credit risk. Our model implies that renegotiation in financial distress is influenced by the illiquidity of the market for distressed debt. As default becomes more likely, the components of bond yield spreads attributable to illiquidity increase. When we consider finite maturity debt, we find decreasing and convex term structures of liquidity spreads. Using bond price data spanning 15 years, we find evidence of a positive correlation between the illiquidity and default componentsofyieldspreadsaswellassupportfordownwardslopingtermstructuresof liquidity spreads. Credit risk and liquidity risk have long been perceived as two of the main justifications for the existence of yield spreads above benchmark Treasury notes or bonds (see Fisher (1959)). Since Merton (1974), a rapidly growing body of literature has focused on credit risk. 1 However, while concern about market liquidity issues has become increasingly marked since the autumn of 1998, 2 liquidity remains a relatively unexplored topic, in particular, liquidity for defaultable securities. 3 This paper develops a structural bond pricing model with liquidity and credit risk. The purpose is to enhance our understanding of both the interaction between these two sources of risk and their relative contributions to the yield spreads on corporate bonds. Throughout the paper, we define liquidity as the ability to sell a security promptly and at a price close to its value in frictionless markets, that is, we think of an illiquid market as one in which a sizeable discount may have to be incurred to achieve immediacy. We model credit risk in a framework that allows for debt renegotiation as in Fan and Sundaresan (2000). Following François and Morellec (2004), we also introduce
2001, Exploring for the Determinants Of Credit Risk in Credit Default Swap Transaction Data, Working paper
 AMATO, Jeffrey D., “Risk Aversion and Risk Premia in the CDS Market” BIS Quarterly Review
, 2002
"... foundation created in 1996 at the initiative of 21 leading partners of the finance and technology ..."
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Cited by 56 (0 self)
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foundation created in 1996 at the initiative of 21 leading partners of the finance and technology