Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries

Acharya, Viral V.; Bharath, Sreedhar T.; Srinivasan, Anand

doi:10.1016/j.jfineco.2006.05.011

Cited by 619 publications

(461 citation statements)

References 32 publications

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“…This is in contrast with the empirical literature on corporate CDS spreads which documents a positive correlation between PDs and LGDs, see Acharya, Bharath, and Srinivasan (2007) and Altman, Brady, Resti, and Sironi (2005).…”

Section: Parameter Estimationcontrasting

confidence: 86%

Market perception of sovereign credit risk in the euro area during the financial crisis

Camba-Méndez

Serwa

2016

The North American Journal of Economics and Finance

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may AbstractWe study market perception of sovereign credit risk in the euro area during the financial crisis. In our analysis we use a parsimonious CDS pricing model to estimate the probability of default (PD) and the loss given default (LGD) as perceived by financial markets. We find that separate identification of PD and LGD appears empirically tractable for a number of euro area countries. In our empirical results the estimated LGDs perceived by financial markets stay comfortably below 40% in most of the samples. We also find that macroeconomic and institutional developments were only weakly correlated with the market perception of sovereign credit risk, whereas financial contagion appears to have exerted a non-negligible effect.JEL-Classification: C11, C32, G01, G12, G15. Keywords: sovereign credit risk, CDS spreads, euro area, probability of default, loss given default.ECB Working Paper 1710, August 2014 1 Executive summaryThe aim of this paper is to study market perception of sovereign credit risk in the euro area during the financial crisis. Understanding the factors that influence changes in market perception of sovereign credit risk is a question of special interest for economists, investors, and financial regulators. Similarly to a number of recent studies, we also monitor the market perception of sovereign risk by using information derived from CDS spreads.In studying market perceptions of sovereign credit risk, one of the aims of this paper is to estimate measures of the probability of default (PD) as perceived by financial markets and the loss given default (LGD), also as perceived by financial markets, embedded in the CDS spreads. Earlier studies of the euro area sovereign debt crisis usually employed the CDS spreads alone and thus were not able to separately identify changes in the valuation of risk stemming from either increases of potential losses or a growing likelihood of default.Yet, in the pricing framework of 'fractional recovery of face value', the factors governing the dynamics of the PD and LGD play very distinct roles in the derivation of the price of the CDS contract, thus suggesting that PD and LGD can indeed, at least in theory, be separately identified. However, what is conceptually true may not always hold empirically, and to date the separate identification of PD and LGD remains challenging.The second aim of this paper is to shed some light on the key drivers of the market perception of ...

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Section: Parameter Estimationcontrasting

confidence: 86%

Market perception of sovereign credit risk in the euro area during the financial crisis

Camba-Méndez

Serwa

2016

The North American Journal of Economics and Finance

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“…Empirical support in favor of this idea has been provided by Pulvino (1998) for the airline industry, and especially by Acharya, Bharath, and Srinivasan (2007) who look at the entire universe of defaulted firms in the US over the period 1981 to 1999; see also Berger, Ofek, and Swary (1996) and Stromberg (2000). We adopt the definition of asset specificity that has been employed in the latter three papers: asset specificity is measured by the Book Value of Machinery and Equipment divided by the Book Value of Assets.…”

Section: Empirical Analysismentioning

confidence: 99%

Cross-country variations in capital structures: The role of bankruptcy codes

Acharya

Sundaram

John

2011

Journal of Financial Intermediation

Self Cite

114

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We investigate the impact of bankruptcy codes on firms' capital-structure choices. We develop a theoretical model to identify how firm characteristics may interact with the bankruptcy code in determining optimal capital structures. A novel and sharp empirical implication emerges from this model: that the difference in leverage choices under a relatively equity-friendly bankruptcy code (such as the US's) and one that is relatively more debt-friendly (such as the UK's) should be a decreasing function of the anticipated liquidation value of the firm's assets. Using data on the US and the UK over the period 1990 to 2002, we subject this prediction to both parametric and nonparametric tests, using different proxies for liquidation values and different measures of leverage. In support for the theory, we find that our proxies for liquidation value are both statistically and economically significant in explaining leverage differences across the two countries. In contrast, many of the other factors that are known to affect within-country leverage (e.g., size) cannot explain differences in leverage across countries.

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“…the fraction of defaulting firms in the economy) and average recovery rates are negatively correlated (see e.g. Altman et al (2005); Acharya et al (2007)). Both variables also seem to be driven by the same common factor that is persistent over time and clearly related to the business cycle: in recessions or industry downturns, default rates are high and recovery rates are low (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

“…On the basis of a static model which is unrelated to their regressions, into which they substitute guessed parameter values, they claim that the 99% VaR for a representative portfolio might increase from a percentage loss of about 3.8% to 4.9% when moving from a model in which recovery rates are constant to one in which there is negative dependence between recovery rates and default probabilities. Acharya et al (2007) take an argument by Shleifer and Vishny (1992) as a starting point: Suppose an industry is in distress and firms in this industry default. If the assets of the defaulting firms consist of industry-specific assets, the firms best able to put these assets to good use might also be experiencing problems, and hence might be unable to buy the assets.…”

Section: Introductionmentioning

confidence: 99%

Recovery rates, default probabilities, and the credit cycle

Bruche

González-Aguado

2010

Journal of Banking & Finance

179

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In recessions, the number of defaulting firms rises. On top of this, the average amount recovered on the bonds of defaulting firms tends to decrease. This paper proposes an econometric model in which this joint time-variation in default rates and recovery rate distributions is driven by an unobserved Markov chain, which we interpret as the "credit cycle". This model is shown to fit better than models in which this joint time-variation is driven by observed macroeconomic variables. We use the model to quantitatively assess the importance of allowing for systematic time-variation in recovery rates, which is often ignored in risk management and pricing models.JEL classifications: G21, G28, G33

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Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries

Cited by 619 publications

References 32 publications

Market perception of sovereign credit risk in the euro area during the financial crisis

Market perception of sovereign credit risk in the euro area during the financial crisis

Cross-country variations in capital structures: The role of bankruptcy codes

Recovery rates, default probabilities, and the credit cycle

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