Saddlepoint Approximations to the Probability of Ruin in Finite Time for the Compound Poisson Risk Process Perturbed by Diffusion

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作者
Riccardo Gatto
Benjamin Baumgartner
机构
[1] University of Bern,Institute of Mathematical Statistics and Actuarial Science
关键词
Conditional distribution; cumulant generating function; Gerber-Shiu function; Importance sampling; Laplace transform; Large deviations techniques; Monte Carlo simulation; Relative error; 60G51; 41A60; 65C05;
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摘要
A large deviations type approximation to the probability of ruin within a finite time for the compound Poisson risk process perturbed by diffusion is derived. This approximation is based on the saddlepoint method and generalizes the approximation for the non-perturbed risk process by Barndorff-Nielsen and Schmidli (Scand Actuar J 1995(2):169–186, 1995). An importance sampling approximation to this probability of ruin is also provided. Numerical illustrations assess the accuracy of the saddlepoint approximation using importance sampling as a benchmark. The relative deviations between saddlepoint approximation and importance sampling are very small, even for extremely small probabilities of ruin. The saddlepoint approximation is however substantially faster to compute.
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页码:217 / 235
页数:18
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