Monte Carlo stokastik optimizasyonu ile optimal saklama payı seviyesi hesabı

Bu çalmada, son yllarda finans sektöründe yaygn olarak kullanlan riske maruz de#er (Value-at-Risk,VaR) risk ölçüsü ile toplam hasar fazlas reasürans yöntemi altnda beklenen ve standart sapma prim ilkeleriaçsndan sigortacnn maruz kalaca# toplam ödemeyi Monte Carlo stokastik optimizasyon yöntemi ileminimize ederek sigortac için optimal saklama paynn hesaplanmas incelenmitir. Böylece analitikçözümün elde edilemedi#i durumlarda optimal saklama paynn Monte Carlo stokastik optimizasyon yöntemiile elde edilebilece#i gösterilmitir.

Optimal retention limit with Monte Carlo stochastic optimization

In this study, VaR (Value-at-Risk) risk measure which is commonly used in financial sector in recent years, areanalyzed by minimizing cedent’s total risk of exposure using Monte Carlo Stochastic optimization method, withcalculating the optimal retention limit in terms of expected and standart deviation premium principles underthe stop loss reinsurance contract for the cedent. Thus, it is revealed that, in the circumstances, when analyticsolution is not achieved, the optimal retention limit can be achieved by Monte Carlo optimization method.

___

  • A. Balbas, B. Balbas, and A. Heras, 2009, Optimal Reinsurance with General Risk Measures, Insurance: Mathematics and Economics, 44, 374-384.
  • N. L. Bowers, H. U. Gerber, J. C. Hickman, D. A. Jones, C. J. Nesbitt, 1997, Actuarial Mathematics, The Society of Actuaries, USA.
  • J. Cai, and K. S. Tan , 2007, Optimal Retention For a Stop-Loss Reinsurance Under the VaR and CTE Risk Measures, ASTIN Bulletin, 37(1), 93-112.
  • J. Cai, K. S. Tan, C. Weng, and Y. Zhang, 2008, Optimal Reinsurance Under VaR and CTE Risk Measures, Insurance Math. and Econom., 43, 185-196.
  • C. D. Daykin, T. Pentikainen, and M. Pensonen, 1994, Practical Risk Theory for Actuaries, London: Chapman and Hall.
  • B. H. Dickman, and M. J. Gilman, 1987,Monte Carlo optimization, Journal of Optimization Theory and Applications, Tecnical note, Vol. 60, No 1, 149-157.
  • K. Dowd, 2004, Value-at-risk, in Encyclopedia of Actuarial Science, ed. Sundt, B. and Teugels, J. (New York: John Wiley & Sons, Ltd.
  • M.C. Fu, FW Glover, and J. April, Simulation optimization: a review, new developments, and applications, In: M.E. Kuhl, N.M. Steiger, J.A. Joines, editors, Proceedings of the 2005 winter simulation conference, 2005.
  • M.C. Fu, C.H. Chen, and L. Shi, Some topics for simulation optimization, In: S.J. Mason, R.R. Hill, L. Mönch, O. Rose, T. Jefferson, and J.W. Fowler, editors, Proceedings of the 2008 winter simulation conference, 2008.
  • T. Kaas, M. Goovaerts, J. Dhaene, and M. Denuit, 2001, Modern Actuarial Risk Theory, Kluwer Academic Publishers, Boston.
  • J. Mun, 2006, Modeling Risk Applying Monte Carlo Simulation, Real Options Analysis, Forecasting, And Optimization Techniques, New Jersey.
  • K. S. Tan, C. Weng, and Y. Zhang, 2009, VaR and CTE criteria for Optimal Quota-Share and Stop-Loss Reinsurance, The North American Actuarial Journal, Volume 13, No: 4.
  • V. R. Young, 2004, Premium Principles, In Encyclopedia of Actuarial Science, vol. 3, ed. J. Teugels and B. Sundt, pp. 1323-31, John Wiley.