IDEAS home Printed from https://ideas.repec.org/a/spr/testjl/v34y2025i3d10.1007_s11749-025-00970-0.html
   My bibliography  Save this article

Measuring Bayesian sensitivity in the compound Poisson process

Author

Listed:
  • F. Ruggeri

    (CNR Istituto di Matematica Applicata e Tecnologie Informatiche)

  • M. Sánchez-Sánchez

    (Universidad de Cádiz)

  • A. Suárez-Llorens

    (Universidad de Cádiz)

Abstract

Bayesian methods are widely used to determine insurance premiums, though they are sometimes criticized for the arbitrariness in selecting prior distributions. To mitigate this issue, classes of priors incorporating expert knowledge have been proposed, allowing for the analysis of uncertainty through upper and lower bounds on Bayesian premiums. In this paper, we employ a recently introduced class of priors based on stochastic orders, where the induced order on prior distributions is preserved in the corresponding posterior distributions. Uncertainty around a prior is captured through weighted functions, and the extremal elements of the class define premium bounds. We also show how dependence among parameters can be integrated using suitable weight functions. Our approach is developed within the framework of the compound Poisson process, a fundamental model for claim frequency and severity in car insurance. Additionally, we present a sensitivity analysis method for a bonus–malus system (BMS).

Suggested Citation

  • F. Ruggeri & M. Sánchez-Sánchez & A. Suárez-Llorens, 2025. "Measuring Bayesian sensitivity in the compound Poisson process," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 34(3), pages 509-529, September.
    • Handle: RePEc:spr:testjl:v:34:y:2025:i:3:d:10.1007_s11749-025-00970-0
    DOI: 10.1007/s11749-025-00970-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11749-025-00970-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11749-025-00970-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Lemaire, Jean, 1979. "How to Define a Bonus-Malus System with an Exponential Utility Function," ASTIN Bulletin, Cambridge University Press, vol. 10(3), pages 274-282, December.
    2. James Berger & Elías Moreno & Luis Pericchi & M. Bayarri & José Bernardo & Juan Cano & Julián Horra & Jacinto Martín & David Ríos-Insúa & Bruno Betrò & A. Dasgupta & Paul Gustafson & Larry Wasserman &, 1994. "An overview of robust Bayesian analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 3(1), pages 5-124, June.
    3. Karlin, Samuel & Rinott, Yosef, 1980. "Classes of orderings of measures and related correlation inequalities II. Multivariate reverse rule distributions," Journal of Multivariate Analysis, Elsevier, vol. 10(4), pages 499-516, December.
    4. Karlin, Samuel & Rinott, Yosef, 1980. "Classes of orderings of measures and related correlation inequalities. I. Multivariate totally positive distributions," Journal of Multivariate Analysis, Elsevier, vol. 10(4), pages 467-498, December.
    5. Sánchez-Sánchez, M. & Sordo, M.A. & Suárez-Llorens, A. & Gómez-Déniz, E., 2019. "Deriving Robust Bayesian Premiums Under Bands Of Prior Distributions With Applications," ASTIN Bulletin, Cambridge University Press, vol. 49(1), pages 147-168, January.
    6. Belzunce, Felix & Ortega, Eva-Maria & Pellerey, Franco & Ruiz, Jose M., 2006. "Variability of total claim amounts under dependence between claims severity and number of events," Insurance: Mathematics and Economics, Elsevier, vol. 38(3), pages 460-468, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Agata Boratyńska, 2021. "Robust Bayesian insurance premium in a collective risk model with distorted priors under the generalised Bregman loss," Statistics in Transition New Series, Polish Statistical Association, vol. 22(3), pages 123-140, September.
    2. Boratyńska Agata, 2021. "Robust Bayesian insurance premium in a collective risk model with distorted priors under the generalised Bregman loss," Statistics in Transition New Series, Statistics Poland, vol. 22(3), pages 123-140, September.
    3. Chi, Chang Koo & Murto, Pauli & Valimaki, Juuso, 2017. "All-Pay Auctions with Affiliated Values," MPRA Paper 80799, University Library of Munich, Germany.
    4. Vikram Krishnamurthy & Udit Pareek, 2015. "Myopic Bounds for Optimal Policy of POMDPs: An Extension of Lovejoy’s Structural Results," Operations Research, INFORMS, vol. 63(2), pages 428-434, April.
    5. Müller, Alfred & Scarsini, Marco, 2005. "Archimedean copulæ and positive dependence," Journal of Multivariate Analysis, Elsevier, vol. 93(2), pages 434-445, April.
    6. Barmalzan, Ghobad & Akrami, Abbas & Balakrishnan, Narayanaswamy, 2020. "Stochastic comparisons of the smallest and largest claim amounts with location-scale claim severities," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 341-352.
    7. Junbo Son & Yeongin Kim & Shiyu Zhou, 2022. "Alerting patients via health information system considering trust-dependent patient adherence," Information Technology and Management, Springer, vol. 23(4), pages 245-269, December.
    8. Jian Yang, 2023. "A Partial Order for Strictly Positive Coalitional Games and a Link from Risk Aversion to Cooperation," Papers 2304.10652, arXiv.org.
    9. Battey, H.S. & Cox, D.R., 2022. "Some aspects of non-standard multivariate analysis," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    10. Ligtvoet, R., 2015. "A test for using the sum score to obtain a stochastic ordering of subjects," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 136-139.
    11. Huang, Wen-Tao & Xu, Bing, 2002. "Some maximal inequalities and complete convergences of negatively associated random sequences," Statistics & Probability Letters, Elsevier, vol. 57(2), pages 183-191, April.
    12. Saghafian, Soroush, 2018. "Ambiguous partially observable Markov decision processes: Structural results and applications," Journal of Economic Theory, Elsevier, vol. 178(C), pages 1-35.
    13. Francesco Bartolucci, 2002. "A recursive algorithm for Markov random fields," Biometrika, Biometrika Trust, vol. 89(3), pages 724-730, August.
    14. Li, Benchong & Li, Yang, 2017. "A note on faithfulness and total positivity," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 168-172.
    15. Burkett, Justin, 2015. "Endogenous budget constraints in auctions," Journal of Economic Theory, Elsevier, vol. 158(PA), pages 1-20.
    16. Ori Davidov & Amir Herman, 2011. "Multivariate Stochastic Orders Induced by Case-Control Sampling," Methodology and Computing in Applied Probability, Springer, vol. 13(1), pages 139-154, March.
    17. Rudy Ligtvoet, 2015. "Remarks and a Correction of Ligtvoet’s Treatment of the Isotonic Partial Credit Model," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 514-515, June.
    18. Fosgerau, Mogens & Lindberg, Per Olov & Mattsson, Lars-Göran & Weibull, Jörgen, 2015. "Invariance of the distribution of the maximum," MPRA Paper 63529, University Library of Munich, Germany.
    19. Colangelo, Antonio & Scarsini, Marco & Shaked, Moshe, 2006. "Some positive dependence stochastic orders," Journal of Multivariate Analysis, Elsevier, vol. 97(1), pages 46-78, January.
    20. Bezgina, E. & Burkschat, M., 2019. "On total positivity of exchangeable random variables obtained by symmetrization, with applications to failure-dependent lifetimes," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 95-109.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:testjl:v:34:y:2025:i:3:d:10.1007_s11749-025-00970-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.