Loss Models: From Data to Decisions, 2nd edition

By Stuart A. Klugman, H. Panjer, Gordon E. Willmot. 2004

116 citations recorded by the source corpus.

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Citations in the corpus

Planning algorithms (2006, background): “For a thorough introduction to constructing cost models for decision making, see [542].”
Hierarchical Insurance Claims Modeling (2008, methodology): “This distribution is well known in actuarial modeling of univariate loss distributions (see, e.g., Klugman et al. 2004).”
Robust fitting of claim severity distributions and the method of trimmed moments (2009, methodology): “For details on parametric loss models as well as for methods of classifying and creating distributions, we refer to Kleiber and Kotz (2003), Klugman et al. (2004), and references therein.”
Multivariate models for operational risk (2010, methodology): “In general, Gt( )—and thus also OpVaR—cannot be analytically calculated so that one depends on techniques like Panjer recursion, Monte Carlo simulation, and fast Fourier transform (FFT) (see, e.g. Klugman et al. 2004).”
Optimal non-proportional reinsurance control and stochastic differential games (2011, unknown): “The corresponding diffusion approximation for this process (see Klugman et al. (2004)) is dX (t) = µ(ν(t))dt+ σ(ν(t))dW (t), (1) where µ(a) = p− λπ(Z − g(Z; a))− λE[g(Z; a)], σ(a) = √ λE[g(Z; a)2], a ∈ Θ.”
fitdistrplus: An R Package for Fitting Distributions (2015, methodology): “In this numerical experiment, we choose classic actuarial distributions for loss modelling: the lognormal distribution and the Pareto type II distribution (Klugman et al., 2009).”
Flexible dependence modeling of operational risk losses and its impact on total capital requirements (2014, methodology): “distributions for each BL and ET by Monte Carlo simulation with 100 000 samples (see Klugman et al. (2008)).”
The compound Poisson risk model with a threshold dividend strategy (2006, result): “Part of its derivation relies on results obtained in Lin and Willmot (1999) and Lin et al.”