IDEAS home Printed from https://ideas.repec.org/a/eee/insuma/v74y2017icp78-83.html

Nonparametric estimation of the claim amount in the strong stability analysis of the classical risk model

Author

Listed:
  • Touazi, A.
  • Benouaret, Z.
  • Aissani, D.
  • Adjabi, S.

Abstract

This paper presents an extension of the strong stability analysis in risk models using nonparametric kernel density estimation for the claim amounts. First, we detail the application of the strong stability method in risk models realized by V. Kalashnikov in 2000. In particular, we investigate the conditions and the approximation error of the real model, in which the probability distribution of the claim amounts is not known, by the classical risk model with exponentially distributed claim sizes. Using the nonparametric approach, we propose different kernel estimators for the density of claim amounts in the real model. A simulation study is performed to numerically compare between the approximation errors (stability bounds) obtained using the different proposed kernel densities.

Suggested Citation

  • Touazi, A. & Benouaret, Z. & Aissani, D. & Adjabi, S., 2017. "Nonparametric estimation of the claim amount in the strong stability analysis of the classical risk model," Insurance: Mathematics and Economics, Elsevier, vol. 74(C), pages 78-83.
  • Handle: RePEc:eee:insuma:v:74:y:2017:i:c:p:78-83
    DOI: 10.1016/j.insmatheco.2017.02.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167668716300737
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.insmatheco.2017.02.007?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. Bernd Heidergott & Arie Hordijk & Nicole Leder, 2010. "Series Expansions for Continuous-Time Markov Processes," Operations Research, INFORMS, vol. 58(3), pages 756-767, June.
    2. Loisel, Stéphane & Mazza, Christian & Rullière, Didier, 2008. "Robustness analysis and convergence of empirical finite-time ruin probabilities and estimation risk solvency margin," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 746-762, April.
    3. Marceau, Etienne & Rioux, Jacques, 2001. "On robustness in risk theory," Insurance: Mathematics and Economics, Elsevier, vol. 29(2), pages 167-185, October.
    4. repec:hum:wpaper:sfb649dp2012-047 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jorge Wilson Euphasio Junior & João Vinícius França Carvalho, 2022. "Resseguro e Capital de Solvência: Atenuantes da Probabilidade de Ruína de SeguradorasReinsurance and Solvency Capital: Mitigating Insurance Companies’ Ruin Probability," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 26(1), pages 200191-2001.
    2. Aicha Bareche & Mouloud Cherfaoui, 2019. "Sensitivity of the Stability Bound for Ruin Probabilities to Claim Distributions," Methodology and Computing in Applied Probability, Springer, vol. 21(4), pages 1259-1281, December.

    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. Loisel, Stéphane & Mazza, Christian & Rullière, Didier, 2009. "Convergence and asymptotic variance of bootstrapped finite-time ruin probabilities with partly shifted risk processes," Insurance: Mathematics and Economics, Elsevier, vol. 45(3), pages 374-381, December.
    2. Joost Berkhout & Bernd F. Heidergott, 2019. "Analysis of Markov Influence Graphs," Operations Research, INFORMS, vol. 67(3), pages 892-904, May.
    3. Claude Lefèvre & Stéphane Loisel, 2009. "Finite-Time Ruin Probabilities for Discrete, Possibly Dependent, Claim Severities," Methodology and Computing in Applied Probability, Springer, vol. 11(3), pages 425-441, September.
    4. Loisel, Stéphane & Mazza, Christian & Rullière, Didier, 2008. "Robustness analysis and convergence of empirical finite-time ruin probabilities and estimation risk solvency margin," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 746-762, April.
    5. Claude Lefèvre & Stéphane Loisel, 2008. "On Finite-Time Ruin Probabilities for Classical Risk Models," Post-Print hal-00168958, HAL.
    6. Badredine Issaadi & Karim Abbas & Djamil Aïssani, 2017. "Perturbation Analysis of the GI/M/s Queue," Methodology and Computing in Applied Probability, Springer, vol. 19(3), pages 819-841, September.
    7. Stéphane Loisel & Nicolas Privault, 2009. "Sensitivity analysis and density estimation for finite-time ruin probabilities," Post-Print hal-00201347, HAL.
    8. Brazauskas, Vytaras, 2003. "Influence functions of empirical nonparametric estimators of net reinsurance premiums," Insurance: Mathematics and Economics, Elsevier, vol. 32(1), pages 115-133, February.
    9. Li Qin & Susan M. Pitts, 2012. "Nonparametric Estimation of the Finite-Time Survival Probability with Zero Initial Capital in the Classical Risk Model," Methodology and Computing in Applied Probability, Springer, vol. 14(4), pages 919-936, December.
    10. Romain Biard & Stéphane Loisel & Claudio Macci & Noel Veraverbeke, 2010. "Asymptotic behavior of the finite-time expected time-integrated negative part of some risk processes and optimal reserve allocation," Post-Print hal-00372525, HAL.
    11. Henry Lam, 2016. "Robust Sensitivity Analysis for Stochastic Systems," Mathematics of Operations Research, INFORMS, vol. 41(4), pages 1248-1275, November.
    12. Asimit, Alexandru V. & Badescu, Alexandru M. & Verdonck, Tim, 2013. "Optimal risk transfer under quantile-based risk measurers," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 252-265.
    13. Roman Adillon & Lambert Jorba & Maite Mármol, 2025. "An Extension of Interval Probabilities using Modal Interval Theory and its Application to Non-life Insurance," Methodology and Computing in Applied Probability, Springer, vol. 27(2), pages 1-17, June.

    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:eee:insuma:v:74:y:2017:i:c:p:78-83. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505554 .

    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.