An Introduction to Credit Risk Modeling

By Christian Bluhm, Ludger Overbeck, C. Wagner. 2002

526 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/1ffa2c16a3289b027e7a494dfba4c5766938ba62

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Citations in the corpus

AN AXIOMATIC APPROACH TO CAPITAL ALLOCATION (2005, unknown): “This technique for allocating portfolio VaR has been proposed in a number of papers, for instance in Overbeck (2000) and Bluhm, Overbeck, and Wagner (2002).”
Credit risk modeling with affine processes (2007, background): “Arvanitis and Gregory [2001], Bielecki and Rutkowski [2002], Bluhm, Overbeck, and Wagner [2003] , Duffie and Singleton [2002], Lando [2004], and Sch¨onbucher [2003a].”
Systematic Risk in Recovery Rates: An Empirical Analysis of Us Corporate Credit Exposures (2004, unknown): “10Assuming that the portfolio is large and well diversified, this is implied by the law of large numbers, see e. g. Bluhm et al. (2003), pp. 70–71.”
Integrated risk modelling (2004, background): “The beta distribution is a crude approximation, and alternatives like the Vasicek distribution (Bluhm et al., 2002; Overbeck and Wagner, 2000) should be explored.”
On comparing the accuracy of default predictions in the rating industry (2006, unknown): “…of default are what is needed in modern capital allocation models and in setting reserves in the banking industry, so there is an enormous interest in correctly mapping letter grades into probabilities (Falkenstein 2000, Carey and Hrycay 2001, Carey 2002, Bluhm et al. 2003 11 and many others).”
Sensible and Efficient Capital Allocation for Credit Portfolios (2003, background): “1 Straightforward Monte Carlo simulation The efficient computation of expected shortfall (4) and expected shortfall contributions (5) is a challenging task for realistic portfolios.”
Credit Risk Modeling Using Time-Changed Brownian Motion (2009, methodology): “The one factor model can be interpreted as a generalized Bernoulli mixing model, in the sense of [8] and [28], where the mixing random variable is Gt.”
Discriminatory Power - An Obsolete Validation Criterion? (2008, unknown): “…events, the probability mass function for the number of defaults in rating class i (allowing for default correlation) is defined by a generalized Bernoulli mixture model (see e.g. Schoenbucher, 2000 or Bluhm et al., 2003) and thus given by: Page 26 ( ) ( )∫ ∞+ ∞− − ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎣ ⎡ ⎟ ⎟ ⎠ ⎞ ⎜ ⎜…”