Ruin theory in a hidden Markov-modulated risk model

Robert J. Elliott; Tak Kuen Siu; Hailiang Yang

doi:10.1080/15326349.2011.593408

Ruin theory in a hidden Markov-modulated risk model

Robert J. Elliott^*, Tak Kuen Siu, Hailiang Yang

^*Corresponding author for this work

Department of Applied Finance

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

We discuss ruin theory when the insurance risk process is described by a hidden Markov, regime-switching diffusion process. The innovations approach to filtering theory is used to transform the partially observed modeling framework into one with complete observations. (Robust) filters for the hidden states of the chain are given. A partial differential equation for the ruin probability is derived in the filtered model.

Original language	English
Pages (from-to)	474-489
Number of pages	16
Journal	Stochastic Models
Volume	27
Issue number	3
DOIs	https://doi.org/10.1080/15326349.2011.593408
Publication status	Published - Jul 2011

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10.1080/15326349.2011.593408

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abstract = "We discuss ruin theory when the insurance risk process is described by a hidden Markov, regime-switching diffusion process. The innovations approach to filtering theory is used to transform the partially observed modeling framework into one with complete observations. (Robust) filters for the hidden states of the chain are given. A partial differential equation for the ruin probability is derived in the filtered model.",

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AB - We discuss ruin theory when the insurance risk process is described by a hidden Markov, regime-switching diffusion process. The innovations approach to filtering theory is used to transform the partially observed modeling framework into one with complete observations. (Robust) filters for the hidden states of the chain are given. A partial differential equation for the ruin probability is derived in the filtered model.

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Ruin theory in a hidden Markov-modulated risk model

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