Bidimensional discrete-time risk models based on bivariate claim count time series

被引:0
作者
Dongxing Ma
Dehui Wang
Jianhua Cheng
机构
[1] Jilin University,Institute of Mathematics
[2] Jilin University,School of Mathematics
来源
Journal of Inequalities and Applications | / 2015卷
关键词
bidimensional discrete-time risk model; adjustment coefficient; bivariate Poisson ; bivariate Poisson ; large deviations; ruin probability; value-at-risk;
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摘要
In this paper, we consider a class of bidimensional discrete-time risk models, which are based on the assumptions that the claim counts obey some specific bivariate integer-valued time series such as bivariate Poisson MA (BPMA) and the bivariate Poisson AR (BPAR) processes. We derive the moment generating functions (m.g.f.’s) for these processes, and we present their explicit expressions for the adjustment coefficient functions. The asymptotic approximations (upper bounds) to three different types of ruin probabilities are discussed, and the marginal value-at-risk (VaR) for each model is obtained. Numerical examples are provided to compute the adjustment coefficients discussed in the paper.
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