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Applications of Fuzzy Regression in Actuarial Analysis

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Listed author(s):
  • Jorge de Andrés Sánchez
  • Antonio Terceño Gómez
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    Abstract

    In this article, we propose several applications of fuzzy regression techniques for actuarial problems. Our main analysis is motivated, on the one hand, by the fact that several articles in the financial and actuarial literature suggest using fuzzy numbers to model interest rate uncertainty but do not explain how to quantify these rates with fuzzy numbers. Likewise, actuarial literature has recently focused some of its attention in analyzing the Term Structure of Interest Rates (TSIR) because this is a key instrument for pricing insurance contracts. With these two ideas in mind, we show that fuzzy regression is suitable for adjusting the TSIR and discuss how to apply a fuzzy TSIR when pricing life insurance contracts and property-liability policies. Finally, we reflect on other actuarial applications of fuzzy regression and develop with this technique the "London Chain Ladder Method" for obtaining Incurred But Not Reported Reserves. Copyright The Journal of Risk and Insurance.

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    File URL: http://www.blackwell-synergy.com/doi/abs/10.1046/j.0022-4367.2003.00070.x
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    Article provided by The American Risk and Insurance Association in its journal The Journal of Risk and Insurance.

    Volume (Year): 70 (2003)
    Issue (Month): 4 ()
    Pages: 665-699

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    Handle: RePEc:bla:jrinsu:v:70:y:2003:i:4:p:665-699
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    Cited by:

    1. Apaydin, Aysen & Baser, Furkan, 2010. "Hybrid fuzzy least-squares regression analysis in claims reserving with geometric separation method," Insurance: Mathematics and Economics, Elsevier, vol. 47(2), pages 113-122, October.
    2. Koissi, Marie-Claire & Shapiro, Arnold F., 2006. "Fuzzy formulation of the Lee-Carter model for mortality forecasting," Insurance: Mathematics and Economics, Elsevier, vol. 39(3), pages 287-309, December.
    3. Morillas, Antonio & Díaz, Bárbara, 2007. "Qualitative Answering Surveys And Soft Computing," Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 0(1), pages 3-19, May.
    4. Smimou, Kamal, 2006. "Estimation of Canadian commodity market risk premiums under price limits: Two-phase fuzzy approach," Omega, Elsevier, vol. 34(5), pages 477-491, October.
    5. Heberle, Jochen & Thomas, Anne, 2014. "Combining chain-ladder claims reserving with fuzzy numbers," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 96-104.
    6. de Andres-Sanchez, Jorge, 2007. "Claim reserving with fuzzy regression and Taylor's geometric separation method," Insurance: Mathematics and Economics, Elsevier, vol. 40(1), pages 145-163, January.
    7. Shapiro, Arnold F., 2004. "Fuzzy logic in insurance," Insurance: Mathematics and Economics, Elsevier, vol. 35(2), pages 399-424, October.
    8. Berry-Stölzle, Thomas R. & Koissi, Marie-Claire & Shapiro, Arnold F., 2010. "Detecting fuzzy relationships in regression models: The case of insurer solvency surveillance in Germany," Insurance: Mathematics and Economics, Elsevier, vol. 46(3), pages 554-567, June.
    9. Mbairadjim Moussa, A. & Sadefo Kamdem, J. & Shapiro, A.F. & Terraza, M., 2014. "CAPM with fuzzy returns and hypothesis testing," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 40-57.

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