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The Order-Statistic Claim Process With Dependent Claim Frequencies and Severities

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Abstract

Assuming that insurance claims arrive according to a general order-statistic (OS) point process, we explore ways for calculating the first two moments of the aggregate claim, thus facilitating the calculation of, and statistical inference for, quantities of actuarial interest such as the standard-deviation risk measure. We allow the OS process to govern claim sizes via claim arrival or, alternatively, claim interarrival times, which is a practically important feature. Given these general dependence structures and the underlying OS process, the herein obtained results extend and generalize a number of those in the literature.

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References

  • Albrecher, H., and J. T. Teugels. 2006. Exponential behaviour in the presence of dependence in risk theory. J. Appl. Probability, 43, 257–273.

    Article  MathSciNet  Google Scholar 

  • Asmussen, S., and H. Albrecher. 2010. Ruin probabilities, 2nd ed. Hackensack, NJ, World Scientific Publishing.

    Book  Google Scholar 

  • Bebbington, M., and D. Harte, 2001. On the statistics of the linked stress release model. J. Appl. Probability, 38A, 176–187.

    Article  MathSciNet  Google Scholar 

  • Bebbington, M. 2008. Incorporating the eruptive history in a stochastic model for volcanic eruptions. J. Volcanol. Geothermal Res., 175, 325–3338.

    Article  Google Scholar 

  • Bebbington, M. 2011. Volcanic eruptions: stochastic models of occurrence patterns. In Extreme environmental events: Complexity in forecasting and early warning, ed. R. A. Meyers, 1104–1134. New York, Springer.

    Chapter  Google Scholar 

  • Bebbington, M. S., and W. Marzocchi. 2011. Stochastic models for earthquake triggering of volcanic eruptions. J. Geophys. Res., 116, B05204. doi:10.1029/2010JB008114

    Article  Google Scholar 

  • Bowers, N. L., H. U. Gerber, J. C. Hickman, D. A. Jones, and C. J. Nesbitt. 1997. Actuarial mathematics, 2nd ed. Schaumburg, IL, Society of Actuaries.

    MATH  Google Scholar 

  • Berg, M., and F. Spizzichino. 2000. Time-lagged point processes with the order-statistics property. Math. Methods Operations Res., 51, 301–314.

    Article  MathSciNet  Google Scholar 

  • Boudreault, M., H. Cossette, D. Landriault, and E. Marceau. 2006. On a risk model with dependence between interclaim arrivals and claim sizes. Scand. Actuarial J., 5, 256–285.

    MathSciNet  MATH  Google Scholar 

  • Cerqueti, R., R. Foschi, and F. Spizzichino. 2009. A spatial mixed Poisson framework for combination of excess-of-loss and proportional reinsurance contracts. Insurance Math. Econ., 45, 59–64.

    Article  MathSciNet  Google Scholar 

  • Crump, K. S. 1975. On point processes having an order statistic structure. Sankhyā Ser. A, 37, 396–404.

    MathSciNet  MATH  Google Scholar 

  • Das, K. P., A. K. M. S. Islam, and P. Chiou. 2011. A skew-normal approximation of the distribution of aggregate claims. J. Probability Stat. Sci., 9, 93–104.

    MathSciNet  Google Scholar 

  • David, H. A., and H. N. Nagaraja. 2003. Order statistics, 3rd ed. Hoboken, NJ, Wiley.

    Book  Google Scholar 

  • Debrabant, B. 2008. Point processes with a generalized order statistic property. Berlin, Logos.

    MATH  Google Scholar 

  • Deffner, A., and E. Haeusler. 1985. A characterization of order statistic point processes that are mixed Poisson processes and mixed sample processes simultaneously. J. Appl. Probability, 22, 314–323.

    Article  MathSciNet  Google Scholar 

  • Denuit, M., J. Dhaene, M. Goovaerts, and R. Kaas. 2005. Actuarial theory for dependent risks: Measures, orders and models. Chichester, UK: Wiley.

    Book  Google Scholar 

  • Dickson, D. C. M. 2005. Insurance risk and ruin. Cambridge, UK, Cambridge University Press.

    Book  Google Scholar 

  • Embrechts, P., C. Klüppelberg, and T. Mikosch. 1997. Modelling extremal events: For insurance and finance. Berlin, Springer.

    Book  Google Scholar 

  • Feigin, P. D. 1979. On the characterization of point processes with the order statistic property. J. Appl. Probability, 16, 297–304.

    Article  MathSciNet  Google Scholar 

  • Garrido, J., and Y. Lu. 2004. On double periodic non-homogeneous Poisson processes. Bull. Assoc. Swiss Actuaries, 2, 195–212.

    MathSciNet  MATH  Google Scholar 

  • Grandell, J. 1997. Mixed Poisson processes. London, UK, Chapman and Hall.

    Book  Google Scholar 

  • Huang, W. J. 1990. On the characterization of point processes with the exchangeable and Markov properties. Sankhyā Ser. A, 52, 16–27.

    MathSciNet  MATH  Google Scholar 

  • Huang, W. J., and J. M. Shoung. 1994. On a study of some properties of point processes. Sankhyā Ser. A, 56, 67–76.

    MathSciNet  MATH  Google Scholar 

  • Huang, W. J., and J. C. Su. 1999. On certain problems involving order statisticsa unified approach through order statistics property of point processes. Sankhyā Ser. A, 61, 36–49.

    MathSciNet  MATH  Google Scholar 

  • Kallenberg, O. 1976. Random measures. London, UK, Academic Press.

    MATH  Google Scholar 

  • Klugman, S. A., H. H. Panjer, and G. E. Willmot. 2008. Loss models: From data to decisions. 3rd ed. Hoboken, NJ, Wiley.

    Book  Google Scholar 

  • Léveillé, G., J. Garrido, and Y. F. Wang. 2010. Moment generating functions of compound renewal sums with discounted claims. Scand. Actuarial J., 3, 165–184.

    Article  MathSciNet  Google Scholar 

  • Li, S. 2008. Discussion on “On the Laplace transform of the aggregate discounted claims with Markovian arrivals.” North Am. Actuarial J., 4, 443–445.

    Article  Google Scholar 

  • Liberman, U. 1985. An order statistic characterization of the Poisson renewal process. J. Appl. Probability, 22, 717–722.

    Article  MathSciNet  Google Scholar 

  • Lu, Y., and J. Garrido, 2005. Doubly periodic non-homogeneous Poisson models for hurricane data. Stat. Methodol., 2, 17–35.

    Article  MathSciNet  Google Scholar 

  • Lu, Y., and J. Garrido. 2006. Regime-switching periodic non-homogeneous Poisson processes. North Am. Actuarial J., 10 (4), 235–248.

    Article  MathSciNet  Google Scholar 

  • McNeil, A. J., R. Frey, and P. Embrechts. 2005. Quantitative risk management: Concepts, techniques, and tools. Princeton, NJ, Princeton University Press.

    MATH  Google Scholar 

  • Nawrotzki, K. 1962. Ein Grenzwertsatz für homogene zufällige Punktfolgen (Verallgemeinerung eines Satzes von A. Rényi). Math. Nachricht., 24, 201–217

    Article  Google Scholar 

  • Nelsen, R. B. 2006. An introduction to copulas, 2nd ed. New York, Springer.

    MATH  Google Scholar 

  • Parzen, E. 1962. Stochastic processes. San Francisco, CA, Holden-Day.

    MATH  Google Scholar 

  • Puri, P. S. 1982. On the characterization of point processes with the order statistic property without the moment condition. J. Appl. Probability, 19, 39–51.

    Article  MathSciNet  Google Scholar 

  • Ren, J. 2008. On the Laplace transform of the aggregate discounted claims with Markovian arrivals. North Am. Actuarial J., 2, 198–207.

    Article  MathSciNet  Google Scholar 

  • Rolski, T., H. Schmidli, V. Schmidt, and J. Teugels. 1999. Stochastic processes for insurance and finance. Chichester, UK, Wiley.

    Book  Google Scholar 

  • Shaked, M., F. Spizzichino, and F. Suter. 2004. Uniform order statistics property and l -spherical densities. Probability Eng. Informational Sci., 18, 275–297.

    MathSciNet  MATH  Google Scholar 

  • Teugels, J. L., and P. Vynckier. 1996. The structure distribution in a mixed Poisson process. J. Appl. Math. Stochastic Anal., 9, 489–496.

    Article  MathSciNet  Google Scholar 

  • Westcott, M. 1973. Some remarks on a property of the Poisson process. Sankhyā Ser. A, 35, 29–34.

    MathSciNet  MATH  Google Scholar 

  • Willmot, G. E. 1989. The total claims distribution under inflationary conditions. Scand. Actuarial J., 1989, 1–12.

    Article  MathSciNet  Google Scholar 

  • Young, V. R. 2004. Premium principles. In Encyclopedia of actuarial science, ed. J. Teugels and B. Sundt, 1322–1331. New York, Wiley.

    Google Scholar 

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Correspondence to Kristina P. Sendova.

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Sendova, K.P., Zitikis, R. The Order-Statistic Claim Process With Dependent Claim Frequencies and Severities. J Stat Theory Pract 6, 597–620 (2012). https://doi.org/10.1080/15598608.2012.719736

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  • DOI: https://doi.org/10.1080/15598608.2012.719736

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