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Thonhauser, Stefan , Enzi, Lea , Pojer, Simon ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.3217/d0wqe-01a38

The collection of files consists of Mathematica and R Code which was created for the purpose of illustrating the theoretical results presented in the publications by means of numerical examples. The files in this record are associated to publications in the following way: *** Exact asymptotics of ruin probabilities with linear Hawkes arrivals (Palmowski, Pojer, Thonhauser), Stochastic Processes and their Applications 182 MonteCarlo_Hawkes.nb, simulation_hawkes_slow_butexact.nb *** The Markovian shot-noise risk model: a numerical method for Gerber-Shiu functions (Pojer, Thonhauser), Methodology and Computing in Applied Probability 25 (1), 17&Ruin probabilities in a Markovian shot-noise environment (Pojer, Thonhauser), Journal of Applied Probability 60 (2), 542-556 Simulation_GS_Function.nb, mc_bounded_process.nb, MC_simply_lambda.nb, MonteCarlo_ShotNoise_ruinprobability.nb, Numerical_Method_Gerber_Shiu_Shot_Noise.nb, Plots.nb *** Optimal reinsurance in a competitive market (Enzi, Thonhauser) Mathematical Methods of Operations Research 2025 Excess of Loss_Exponential.R, Excess of Loss_Pareto.R, Proportional_ExponentialClaims.R *** Numerical Computation of Risk Functionals in PDMP Risk Models (Enzi, Thonhauser) Monte Carlo and Quasi-Monte Carlo Methods: MCQMC 2022 MC Ruin probability.nb, QMC.nb, Quantization.nb *** Regularity of a best-of option's payoff (Nachbagauer, Thonhauser) In: Problèmes diophantiens: déterminisme, aléa et applications: Panoramas et Synthèses Illustrations_BestOfOption6dMinVar.nb and the additional Sobol point sets containd in the files Sobol6d30.csv -- Sobol6d100.csv. ***

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Monte Carlo method Applied probability Computation Sobol sequence Computer science Applied mathematics Stochastic game Markov process Reinsurance Mathematics Point (geometry) Numerical analysis Conditional probability Probability theory Algorithm Mathematical optimization Markov chain Monte Carlo Code (set theory) Markov chain Stochastic process Scope (computer science) Probability distribution

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DOI: https://doi.org/10.3217/d0wqe-01a38

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Title: Complementary Material for "Risk Modelling: Analysis, Simulation and Optimization"

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Publication year: 2025

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Publication date: 2025-11-15

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Authors: Thonhauser, Stefan, Enzi, Lea, Pojer, Simon

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Concepts: Monte Carlo method, Applied probability, Computation, Sobol sequence, Computer science, Applied mathematics, Stochastic game, Markov process, Reinsurance, Mathematics, Point (geometry), Numerical analysis, Conditional probability, Probability theory, Algorithm, Mathematical optimization, Markov chain Monte Carlo, Code (set theory), Markov chain, Stochastic process, Scope (computer science), Probability distribution

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