NDLI: Simulating ruin probabilities in insurance risk processes with subexponential claims

Content Provider	IEEE Xplore Digital Library
Author	Nam Kyoo Boots Shahabuddin, P.
Copyright Year	2001
Description	Author affiliation: Dept. of Econ. & Bus. Adm., Vrije Univ., Amsterdam, Netherlands (Nam Kyoo Boots)
Abstract	We describe a fast simulation framework for simulating small ruin probabilities in insurance risk processes with subexponential claims. Naive simulation is inefficient since the event of interest is rare, and special simulation techniques like importance sampling need to be used. An importance sampling change of measure known as sub-exponential twisting has been found useful for some rare event simulations in the subexponential context. We describe conditions that are sufficient to ensure that the infinite horizon probability can be estimated in a (work-normalized) large set asymptotically optimal manner, using this change of measure. These conditions are satisfied for some large classes of insurance risk processes - e.g., processes with Markov-modulated claim arrivals and claim sizes - where the heavy tails are of the 'Weibull type'. We also give much weaker conditions for the estimation of the finite horizon ruin probability. Finally, we present experiments supporting our results.
Starting Page	468
Ending Page	476
File Size	868983
Page Count	9
File Format	PDF
ISBN	0780373073
DOI	10.1109/WSC.2001.977326
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-12-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Winter Simulation Conf. Board of Dir.
Subject Keyword	Insurance Discrete event simulation Infinite horizon Monte Carlo methods Context modeling Tail Industrial engineering Operations research Stochastic processes Steady-state
Content Type	Text
Resource Type	Article

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