Common Poisson Shock Models: Applications to Insurance and Credit Risk Modelling

By Filip Lindskog, Alexander J. McNeil. ASTIN Bulletin: The Journal of the International Actuarial Association, 2003

272 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/8b915090f347aa82aa91357ee172212ad5e1d0ea

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Citations in the corpus

Quantitative models for operational risk: Extremes, dependence and aggregation (2006, background): “There is a flurry of mathematical research ongoing on this topic; beyond the references already given, see also the common shock model by Lindskog and McNeil (2003) or Bäuerle and Grübel (2005).”
On a reduced form credit risk model with common shock and regime switching (2012, background): “…copula models such as Schonbucher and Schubert (2001), Hull and White (2004), the interacting intensities models such as Davis and Lo (2001), Yu (2007), the conditionally independent default models such as Duffie and Garleanu (2001), and the common shock models such as Lindskog and McNeil (2003).”
A Comparative Analysis of CDO Pricing Models under the Factor Copula Framework (2009, background): “recently, Elouerkhaoui [2003a, b], Giesecke [2003], and Lindskog and McNeil [2003] considered the use of such models. We present here the simplest form of the model corresponding to a single fatal shock.15 We consider some latent variables Vi = min(Y, zi), i = 1, ..., n where Y, zi, i = 1, ..., n ar”
Chapter 8 – Modelling Dependence with Copulas and Applications to Risk Management (2003, methodology): “For more details on this model, see Lindskog and McNeil (2001).”
Calibration of CDO Tranches with the Dynamical Generalized-Poisson Loss Model (2007, methodology): “S 0 := E0 [ ∫ Tb 0 D(0, t)dL̄ t ] − U 0 E0 [∑b i=1 δiD(0, Ti)(1− L̄ Ti ) ] (13)”
Lévy Processes in Finance: Inverse Problems and Dependence Modelling (2004, background): “In finite activity models, a more accurate modelling of dependence may be achieved by specifying directly the dependence of individual jumps in one-dimensional compound Poisson processes (see [65]).”
Copulas: A Personal View (2009, unknown): “If you have mastered the basic theory above, you may venture out into the exciting land of copula–exotics; an interesting paper for instance giving you a guided walk through the copula country ruled by Archimedes is McNeil and Nešlehová [32].”
TVaR-based capital allocation for multivariate compound distributions with positive continuous claim amounts (2012, background): “Multivariate compound Poisson distribution We assume that (M1, . . . ,Mn) follows a multivariate Poisson distribution which is defined with a common shock as explained in e.g. Johnson et al. (1997) and Lindskog and McNeil (2003).”