On the Dependence Between Default Risk and Recovery Rates in Structural Models

2020 ◽  
Author(s):  
Jean-David Fermanian
Keyword(s):  
Default Risk ◽  
Structural Models ◽  
Recovery Rates

Internal Default Risk Model: Simulation of Default Times And Recovery Rates within the New FRTB Framework

2018 ◽  
Author(s):  
Andrea Bertagna ◽  
Deliu Dragos ◽  
Luca Lopez ◽  
Aldo Nassigh ◽  
Michele Pioppi ◽  
...  
Keyword(s):  
Default Risk ◽  
Risk Model ◽  
Model Simulation ◽  
Recovery Rates

Banks’ Risk Dynamics and Distance to Default

2019 ◽  
Vol 33 (6) ◽  
pp. 2421-2467 ◽  
Author(s):  
Stefan Nagel ◽  
Amiyatosh Purnanandam
Keyword(s):  
Default Risk ◽  
Structural Models ◽  
Return Volatility ◽  
Usual Assumption ◽  
Asset Volatility ◽  
Risk Dynamics ◽  
Asset Values ◽  
Distance To Default ◽  
Bank Equity ◽  
Risky Debt

Abstract We adapt structural models of default risk to take into account the special nature of bank assets. The usual assumption of lognormally distributed asset values is not appropriate for banks. Typical bank assets are risky debt claims with concave payoffs. Because of the payoff nonlinearity, bank asset volatility rises following negative shocks to borrower asset values. As a result, standard structural models with constant asset volatility can severely understate banks’ default risk in good times when asset values are high. Additionally, bank equity return volatility is much more sensitive to negative shocks to asset values than in standard structural models.

scholarly journals Can Structural Models Price Default Risk? Evidence from Bond and Credit Derivative Markets

2015 ◽  
Vol 05 (03) ◽  
pp. 1550007 ◽  
Author(s):  
Jan Ericsson ◽  
Joel Reneby ◽  
Hao Wang
Keyword(s):  
Default Risk ◽  
Structural Models ◽  
Credit Default Swap ◽  
Corporate Bond ◽  
Credit Default ◽  
Credit Derivative ◽  
Risk Free Rate ◽  
Derivative Markets ◽  
Bond Spreads ◽  
Free Rate

Using a set of structural models, we evaluate the price of default protection for a sample of US corporations. In contrast to previous evidence from corporate bond data, credit default swap (CDS) premia are not systematically underestimated. In fact, one of our studied models has little difficulty on average in predicting their level. For robustness, we perform the same exercise for bond spreads by the same issuers on the same trading date. As expected, bond spreads relative to the treasury curve are systematically underestimated. This is not the case when the swap curve is used as a benchmark, suggesting that previously documented underestimation results may be sensitive to the choice of risk-free rate.

Understanding the Role of Recovery in Default Risk Models : Empirical Comarisons and Implied Recovery Rates

2001 ◽  
Vol 2001 (37) ◽  
pp. 1-37 ◽  
Author(s):  
Gurdip Bakshi ◽  
◽  
Dilip B. Madan ◽  
Frank X. Zhang
Keyword(s):  
Default Risk ◽  
Risk Models ◽  
Recovery Rates

Validation of the Short Dark Triad in a German Sample

2020 ◽  
pp. 1-12
Author(s):  
Caroline Wehner ◽  
Ulrike Maaß ◽  
Marius Leckelt ◽  
Mitja D. Back ◽  
Matthias Ziegler
Keyword(s):  
Sensation Seeking ◽  
Factor Model ◽  
Structural Models ◽  
Self Esteem ◽  
Dark Triad ◽  
Fit Indices ◽  
Nomological Network ◽  
Competitive Test ◽  
Three Factor ◽  
Behavioral Criteria

Abstract. The structure, correlates, and assessment of the Dark Triad are widely discussed in several fields of psychology. Based on the German version of the Short Dark Triad (SDT), we add to this by (a) providing a competitive test of existing structural models, (b) testing the nomological network, and (c) proposing an ultrashort 9-item version of the SDT (uSDT). A sample of N = 969 participants provided data on the SDT and a range of further measures. Our competitive test of five structural models revealed that fit indices and nomological network assumptions were best met in a three-factor model, with separate factors for psychopathy, Machiavellianism, and narcissism. The results provided an extensive overview of the raw, unique, and shared associations of Dark Triad dimensions with narcissism facets, sadism, impulsivity, self-esteem, sensation seeking, the Big Five, maladaptive personality traits, sociosexual orientation, and behavioral criteria. Finally, the uSDT exhibited satisfactory psychometric properties. The highest overlap in expected relations between SDT and uSDT, and convergent and discriminant measures was also found for the three-factor model. Our study underlines the utility of a three-factor model of the Dark Triad, extends findings on its nomological network, and provides an ultrashort instrument.

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