| 杂志 | Insurance: Mathematics and Eco
65,55-65, 2015 |
| 作者 | Angelos Dassios, Hongbiao Zhao |
| 正文 | In 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-Codes： | G22; C10; C60 |
| 关键词： | Risk model; Ruin probability; Renewal shot-noise Cox process; Piecewise-deterministic Markov process; Martingale method; Importance sampling; Change of probability measure; Rare-event simulation |
