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Survival probabilities in a discrete semi-Markov risk model

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  • Chen, Mi
  • Yuen, Kam Chuen
  • Guo, Junyi

Abstract

In this paper, we consider the survival probability for a discrete semi-Markov risk model, which assumes individual claims are influenced by a Markov chain with finite state space and there is autocorrelation among consecutive claim sizes. Our semi-Markov risk model is similar to the one studied in Reinhard and Snoussi (2001,2002) [1,2] without the restriction imposed on the distributions of the claims. In particular, the model of study includes several existing risk models such as the compound binomial model (with time-correlated claims) and the compound Markov binomial model (with time-correlated claims) as special cases. The main purpose of the paper is to develop a recursive method for computing the survival probability in the two-state model, and present some numerical examples to illustrate the application of our results.

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  • Chen, Mi & Yuen, Kam Chuen & Guo, Junyi, 2014. "Survival probabilities in a discrete semi-Markov risk model," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 205-215.
    • Handle: RePEc:eee:apmaco:v:232:y:2014:i:c:p:205-215
    DOI: 10.1016/j.amc.2014.01.057
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    1. Lu, Yi & Li, Shuanming, 2005. "On the probability of ruin in a Markov-modulated risk model," Insurance: Mathematics and Economics, Elsevier, vol. 37(3), pages 522-532, December.
    2. Willmot, Gordon E., 1993. "Ruin probabilities in the compound binomial model," Insurance: Mathematics and Economics, Elsevier, vol. 12(2), pages 133-142, April.
    3. J.M. Reinhard, & Snoussi, M., 2001. "On the Distribution of the Surplus Prior to Ruin in a Discrete Semi-Markov Risk Model," ASTIN Bulletin, Cambridge University Press, vol. 31(2), pages 255-273, November.
    4. Cheng, Shixue & Gerber, Hans U. & Shiu, Elias S. W., 2000. "Discounted probabilities and ruin theory in the compound binomial model," Insurance: Mathematics and Economics, Elsevier, vol. 26(2-3), pages 239-250, May.
    5. Lu, Yi & Li, Shuanming, 2009. "The Markovian regime-switching risk model with a threshold dividend strategy," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 296-303, April.
    6. Diko, Peter & Usábel, Miguel, 2011. "A numerical method for the expected penalty-reward function in a Markov-modulated jump-diffusion process," Insurance: Mathematics and Economics, Elsevier, vol. 49(1), pages 126-131, July.
    7. Gerber, Hans U., 1988. "Mathematical Fun with the Compound Binomial Process," ASTIN Bulletin, Cambridge University Press, vol. 18(2), pages 161-168, November.
    8. Ng, Andrew C.Y. & Yang, Hailiang, 2006. "On the joint distribution of surplus before and after ruin under a Markovian regime switching model," Stochastic Processes and their Applications, Elsevier, vol. 116(2), pages 244-266, February.
    9. Zhu, Jinxia & Yang, Hailiang, 2008. "Ruin theory for a Markov regime-switching model under a threshold dividend strategy," Insurance: Mathematics and Economics, Elsevier, vol. 42(1), pages 311-318, February.
    10. Xin Zhang, 2008. "On the Ruin Problem in a Markov-Modulated Risk Model," Methodology and Computing in Applied Probability, Springer, vol. 10(2), pages 225-238, June.
    11. Albrecher, Hansjorg & Boxma, Onno J., 2005. "On the discounted penalty function in a Markov-dependent risk model," Insurance: Mathematics and Economics, Elsevier, vol. 37(3), pages 650-672, December.
    12. Shiu, Elias S.W., 1989. "The Probability of Eventual Ruin in the Compound Binomial Model," ASTIN Bulletin, Cambridge University Press, vol. 19(2), pages 179-190, November.
    13. Gerber, Hans U. & Shiu, Elias S.W. & Yang, Hailiang, 2010. "An elementary approach to discrete models of dividend strategies," Insurance: Mathematics and Economics, Elsevier, vol. 46(1), pages 109-116, February.
    14. Xiao, Yuntao & Guo, Junyi, 2007. "The compound binomial risk model with time-correlated claims," Insurance: Mathematics and Economics, Elsevier, vol. 41(1), pages 124-133, July.
    15. Janssen, Jacques & Reinhard, Jean-Marie, 1985. "Probabilités de Ruine pour une Classe de Modèles de Risque Semi-Markoviens," ASTIN Bulletin, Cambridge University Press, vol. 15(2), pages 123-133, November.
    16. Eric Cheung & David Landriault, 2009. "Analysis of a Generalized Penalty Function in a Semi-Markovian Risk Model," North American Actuarial Journal, Taylor & Francis Journals, vol. 13(4), pages 497-513.
    17. Dickson,David C. M., 2005. "Insurance Risk and Ruin," Cambridge Books, Cambridge University Press, number 9780521846400.
    18. Yuen, K. C. & Guo, J. Y., 2001. "Ruin probabilities for time-correlated claims in the compound binomial model," Insurance: Mathematics and Economics, Elsevier, vol. 29(1), pages 47-57, August.
    19. Cossette, Helene & Landriault, David & Marceau, Etienne, 2004. "Exact expressions and upper bound for ruin probabilities in the compound Markov binomial model," Insurance: Mathematics and Economics, Elsevier, vol. 34(3), pages 449-466, June.
    20. Tan, Jiyang & Yang, Xiangqun, 2006. "The compound binomial model with randomized decisions on paying dividends," Insurance: Mathematics and Economics, Elsevier, vol. 39(1), pages 1-18, August.
    21. Zhu, Jinxia & Yang, Hailiang, 2009. "On differentiability of ruin functions under Markov-modulated models," Stochastic Processes and their Applications, Elsevier, vol. 119(5), pages 1673-1695, May.
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    3. Jingchao Li & Bihao Su & Zhenghong Wei & Ciyu Nie, 2022. "A Multinomial Approximation Approach for the Finite Time Survival Probability Under the Markov-modulated Risk Model," Methodology and Computing in Applied Probability, Springer, vol. 24(3), pages 2169-2194, September.
    4. Bihao Su & Chenglong Xu & Jingchao Li, 2022. "A Deep Neural Network Approach to Solving for Seal’s Type Partial Integro-Differential Equation," Mathematics, MDPI, vol. 10(9), pages 1-21, May.

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