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Approximations of the ruin probability in a discrete time risk model
Volume 7, Issue 3 (2020), pp. 221–243
David J. Santana   Luis Rincón ORCID icon link to view author Luis Rincón details  

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https://doi.org/10.15559/20-VMSTA158
Pub. online: 4 August 2020      Type: Research Article      Open accessOpen Access

Received
2 June 2020
Revised
18 July 2020
Accepted
18 July 2020
Published
4 August 2020

Abstract

Based on a discrete version of the Pollaczeck–Khinchine formula, a general method to calculate the ultimate ruin probability in the Gerber–Dickson risk model is provided when claims follow a negative binomial mixture distribution. The result is then extended for claims with a mixed Poisson distribution. The formula obtained allows for some approximation procedures. Several examples are provided along with the numerical evidence of the accuracy of the approximations.

References

[1] 
Asmussen, S., Albrecher, H.: Ruin Probabilities vol. 14. World scientific Singapore (2010) MR2766220. https://doi.org/10.1142/9789814282536
[2] 
Bowers, N.L., Gerber, H.U., Hickman, J.C., Jones, D.A., Nesbitt, C.J.: Actuarial Mathematics. The Society of Actuaries, Illinois (1997) MR2011229. https://doi.org/10.1080/10920277.1999.10595793
[3] 
Cheng, S., Gerber, H.U., Shiu, E.S.: Discounted probabilities and ruin theory in the compound binomial model. Insur. Math. Econ. 26(2), 239–250 (2000) MR1787839. https://doi.org/10.1016/S0167-6687(99)00053-0
[4] 
Damarackas, J., S˘iaulys, J.: A note on the net profit condition for discrete and classical risk models. Lith. Math. J. 55(4), 465–473 (2015) MR3424708. https://doi.org/10.1007/s10986-015-9292-x
[5] 
Dickson, D.C.: Some comments on the compound binomial model. ASTIN Bull. 24(1), 33–45 (1994)
[6] 
Feller, W.: An Introduction to Probability Theory and Its Applications I. John Wiley and Sons, New York (1968) MR0228020
[7] 
Gerber, H.U.: Mathematical fun with the compound binomial process. ASTIN Bull. 18(2), 161–168 (1988)
[8] 
Grandell, J.: Mixed Poisson Processes. Springer, Dordrecht (1997) MR1463943. https://doi.org/10.1007/978-1-4899-3117-7
[9] 
Karlis, D., Xekalaki, E.: Mixed Poisson distributions. Int. Stat. Rev. 73(1), 35–58 (2005)
[10] 
Li, S.: Distributions of the surplus before ruin, the deficit at ruin and the claim causing ruin in a class of discrete time risk models. Scand. Actuar. J. 2005(4), 271–284 (2005) MR2164047. https://doi.org/10.1080/03461230510009808
[11] 
Li, S., Garrido, J.: On the time value of ruin in the discrete time risk model. Business Economics Series 12, Working Paper 02-18, Universidad Carlos III de Madrid
[12] 
Li, S., Lu, Y., Garrido, J.: A review of discrete-time risk models. Rev. R. Acad. Cienc. Exactas Fís. Nat., Ser. A Mat. 103(2), 321–337 (2009) MR2582636. https://doi.org/10.1007/BF03191910
[13] 
Puri, P.S.., Goldie, C.M.: Poisson mixtures and quasi-infinite divisibility of distributions. J. Appl. Probab. 16(1), 138–153 (1979) MR0520944. https://doi.org/10.2307/3213382
[14] 
Santana, D.J., González-Hernández, J., Rincón, L.: Approximation of the ultimate ruin probability in the classical risk model using Erlang mixtures. Methodol. Comput. Appl. Probab. 19(3), 775–798 (2017) MR3683971. https://doi.org/10.1007/s11009-016-9515-6
[15] 
Shiu, E.: The probability of eventual ruin in the compound binomial model. ASTIN Bull. 19(2), 179–190 (1989)
[16] 
Steutel, F.W., Van Eenige, M.J.A.: Note on the approximation of distributions on Z+ by mixtures of negative binomial distributions. Stoch. Models 13(2), 271–274 (1997) MR1442369. https://doi.org/10.1080/15326349708807426
[17] 
Willmot, G.: On recursive evaluation of mixed Poisson probabilities and related quantities. Scand. Actuar. J. 1993(2), 114–133 (1993) MR1272853
[18] 
Willmot, G., Lin, S.: Risk modeling with the mixed Erlang distribution. Appl. Stoch. Models Bus. Ind. 27(1), 2–16 (2011) MR2752449. https://doi.org/10.1002/asmb.838
[19] 
Willmot, G., Woo, J.K.: On the class of Erlang mixtures with risk theoretic applications. N. Am. Actuar. J. 11(2), 99–115 (2007) MR2380721. https://doi.org/10.1080/10920277.2007.10597450

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Keywords
Ruin probability risk process

MSC2010
91B30 91G99

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