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A Risk Model with Renewal Shot-Noise Cox Process

id: 2267 Date: 20160218 Times:
Magazines   65 (2015) 55–65
AuthorAngelos Dassios, Jiwook Jang, Hongbiao Zhao
ContentIn this paper we generalise the risk models beyond the ordinary framework of affine processes or Markov processes and study a risk process where the claim arrivals are driven by a Cox process with renewal shot-noise intensity. The upper bounds of the finite-horizon and infinite-horizon ruin probabilities are investigated and an efficient and exact Monte Carlo simulation algorithm for this new process is developed. A more efficient estimation method for the infinite-horizon ruin probability based on importance sampling via a suitable change of probability measure is also provided; illustrative numerical examples are also provided.
JEL-CodesG22 C10 C60
KeywordsRisk model Ruin probability Renewal shot-noise Cox process Piecewise-deterministic Markov process Martingale method Importance sampling Change of probability measure Rare-event simulation
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