Analysis of Ruin Probability in Insurance Companies Using the Cramer-Lundberg Model with Variations in Claim Distributions
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H. Albrecher, M. Bladt, and E. Vatamidou, “Efficient Simulation of Ruin Probabilities when claims are mixtures of heavy and light tails”, Methodology and Computing in Applied Probability, vol.23, pp. 1237-1255, 2021. https://doi.org/10.1007/s11009-020-09799-6
J. Dhaene, R. J. A. Laeven, and Y. Zhang, “Systemic risk: Conditinal distortion risk measures”, Insurance: Mathematics and Economics, vol.103, pp 126-145, 2022.
https://doi.org/10.1016/j.insmatheco.2021.12.002
A. Kuznetsov and Z. Palmowski, “Ruin probability in the classical Cramer-Lundberg model with investments,” Insurance: Mathematics and Economics, vol. 108, pp 189-205, 2023. https://doi.org/10.1016/j.insmatheco.2022.12.004
Z. Cheng, and Y. Seol, “Diffusion Approximation of a Risk Model with Non-Stationary Hawkes Arrivals of Claims”, Methodology Computing Appllied Probability, vol. 22, pp 555-571, 2020. https://doi.org/10.1007/s11009-019-09722-8
A. Bazyari, “Analysis of a Dependent Perturbed Renewal Risk Model with Heavy-tailed Distributions”, Lobachevskii Journal of Mathematics, vol. 44, pp 4610-4629, 2023. https://doi.org/10.1134/S1995080223110057
A. Bazyari, “On the ruin probabilities for a general perturbed renewal risk process,” Journal of Statistical Planning and Inference, vol. 227, pp 1-17, 2023. https://doi.org/10.1016/j.jspi.2023.02.005
O. Melnikov, and J. Milz, “Randomized Quasi-Monte Carlo Methods for Risk-Averse Stochastic Optimization”, Journal of Optimization Theory and Applications, vol. 206, pp 14, 2025. https://doi.org/10.1007/s10957-025-02693-6
M. Tomita, K. Takaoka, and M, Ishizaka, “Some mathematical properties of the premium function and ruin probability of a generalized Cramer-Lundberg model driven by mixed poisson processes”, Japan Journal of Industrial and Applied Mathematics, vol. 41, pp 1389-1412, 2024. https://doi.org/10.1007/s13160-024-00656-4
Swiss Re Institute, “Advanced Risk Modelling for Reinsurance Strategies”, Swiss Re, 2022. [Online]. Available: https://www.swissre.com/institute
A. Alfonsi, A. Cherchali, J. A. I. Acevedom, “ Multilevel Monte Carlo for computing the SCR with the standard formula and other stress tests,” Insurance: Mathematics and Economics, vol.100, pp 235-260, 2021. https://doi.org/10.1016/j.insmatheco.2021.05.005
F. Perla, S. Scognamiglio, A. Spadaro, and P. Zanetti, “Explainable Least Square Monte Carlo for Solvency Capital Requirement Evaluation,” North Americal Actuarial Journal, 2025. https://doi.org/10.1080/10920277.2025.2519542
S. Graf, and R. Korn, “A guide to Monte Carlo simulation concepts for assessment of risk-return profiles for regulatory purposes,” European Actuarial Journal, vol.10, pp 273-293, 2020. https://doi.org/10.1007/s13385-020-00232-3
S. A. Klugman, H. H. Panjer, and G. E. Willmot, Loss Models: From Data to Decisions, 4th ed. Hoboken, NJ: Wiley, 2012. http://dx.doi.org/10.1002/9780470391341.index
G. Willmot and J. K. Woo, Surplus Analysis of Sparre Andersen Insurance Risk Processes. Springer, New York, 2017. https://doi.org/10.1007/978-3-319-71362-5
T. Dimitrakopoulou, A. Karagrigoriou, A. Makrides, I. Vonta, “Competing Risks Modelling via Multistate Sysem Methodology under a Generalized Family of Distributions,” Methodology and Computing in Applied Probability, vol. 27:41, 2025. https://doi.org/10.1007/s11009-025-10169-3
D. Gaigall, “Test for Changes in The Modeled Solvency Capital Requirement of An Internal Risk Model”, Journal of the IAA, vol. 51, pp 813-837, 2021. https://doi.org/10.1017/asb.2021.20
Y. K. Tse, “Basic Monte Carlo Methods,” Nonlife Actuarial Models, Singapore Management University, pp 370-401, 2023. https://doi.org/10.1017/9781009315067.014
J. Tom, The Cramer-Lundberg Model and Copulas, Eindhoven University of Technology, Thesis, 2021.
M. C. Fu, Simulation and the Monte Carlo Method, 3rd ed., Hoboken, NJ: Wiley, 2023. https://doi.org/10.1002/9781118631980
M. Mandjes and O. Boxma, The Cramer-Lundberg model and its variants, Spinger Nature, 2023. https://doi.org/10.1007/978-3-031-39105-7
T. M. Tovstik, and D. S. Bulgakova, “An Insurance Company Model with Random Premium and Claims”, Vestnik St.Petersb Univ.Math, vol. 58, pp 79-91, 2025. https://doi.org/10.1134/S1063454125700098
EIOPA, “Solvency II: 2023 Insurance Stress Test Report,” European Insurance and Occupational Pensions Authority, 2023. [Online]. Available: https://www.eiopa.europa.eu
Society of Actuaries, “Monte Carlo Simulation Application in Insurance Risk Management”, SOA Research Report, 2024. [Online]. Available: https://www.soa.org/resources/research-reports/2024/monte-carlo-simulation-insurance-risk
D. C. M. Dickson, M. R. Hardy, dan H. R. Waters, Actuarial Mathematics for Life Contingent Risks, 2nd ed., Cambridge: Cambrige University Press, 2013. https://doi.org/10.1017/9781108784184
J. Grandell, Aspects of Risk Theory, Springer Science & Business Media, 2012. https://doi.org/10.1007/978-1-4613-9058-9
DOI: http://dx.doi.org/10.30829/zero.v9i2.25581
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