Risk models based on time series for count random variables
AbstractIn this paper, we generalize the classical discrete time risk model by introducing a dependence relationship in time between the claim frequencies. The models used are the Poisson autoregressive model and the Poisson moving average model. In particular, the aggregate claim amount and related quantities such as the stop-loss premium, value at risk and tail value at risk are discussed within this framework.
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Bibliographic InfoArticle provided by Elsevier in its journal Insurance: Mathematics and Economics.
Volume (Year): 48 (2011)
Issue (Month): 1 (January)
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Web page: http://www.elsevier.com/locate/inca/505554
Discrete time risk model Dependence Poisson MA(1) process Poisson MA(q) process Poisson AR(1) process;
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Promislow, S. David, 1991. "The probability of ruin in a process with dependent increments," Insurance: Mathematics and Economics, Elsevier, Elsevier, vol. 10(2), pages 99-107, July.
- Gerber, Hans U., 1982. "Ruin theory in the linear model," Insurance: Mathematics and Economics, Elsevier, Elsevier, vol. 1(3), pages 213-217, July.
- Zhao, Xiaobing & Zhou, Xian, 2012. "Copula models for insurance claim numbers with excess zeros and time-dependence," Insurance: Mathematics and Economics, Elsevier, Elsevier, vol. 50(1), pages 191-199.
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