Burnecki, Krzysztof and Weron, Rafal
(2010):
*Simulation of Risk Processes.*

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## Abstract

This paper is intended as a guide to simulation of risk processes. A typical model for insurance risk, the so-called collective risk model, treats the aggregate loss as having a compound distribution with two main components: one characterizing the arrival of claims and another describing the severity (or size) of loss resulting from the occurrence of a claim. The collective risk model is often used in health insurance and in general insurance, whenever the main risk components are the number of insurance claims and the amount of the claims. It can also be used for modeling other non-insurance product risks, such as credit and operational risk. In this paper we present efficient simulation algorithms for several classes of claim arrival processes.

Item Type: | MPRA Paper |
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Original Title: | Simulation of Risk Processes |

Language: | English |

Keywords: | Risk process; Claim arrival process; Homogeneous Poisson process (HPP); Non-homogeneous Poisson process (NHPP); Mixed Poisson process; Cox process; Renewal process. |

Subjects: | C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C24 - Truncated and Censored Models ; Switching Regression Models ; Threshold Regression Models G - Financial Economics > G3 - Corporate Finance and Governance > G32 - Financing Policy ; Financial Risk and Risk Management ; Capital and Ownership Structure ; Value of Firms ; Goodwill C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General |

Item ID: | 25444 |

Depositing User: | Rafal Weron |

Date Deposited: | 27 Sep 2010 03:22 |

Last Modified: | 27 Sep 2019 12:40 |

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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/25444 |