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Aggregate Loss Distribution And Dependence: Composite Models, Copula Functions And Fast Fourier Transform For The Danish Re Insurance Data

Author

Listed:
  • Rocco Roberto Cerchiara
  • Francesco Acri

    (Dipartimento di Economia, Statistica e Finanza, Università della Calabria)

Abstract

Danish fire insurance data has been analyzed in several papers, using different models. In this paper we investigate the improving of the fitting for the Danish fire insurance data according to composite models, including dependence structure by copula functions and Fast Fourier Transform.

Suggested Citation

  • Rocco Roberto Cerchiara & Francesco Acri, 2016. "Aggregate Loss Distribution And Dependence: Composite Models, Copula Functions And Fast Fourier Transform For The Danish Re Insurance Data," Working Papers 201608, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
    • Handle: RePEc:clb:wpaper:201608
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    File URL: http://www.ecostat.unical.it/RePEc/WorkingPapers/WP08_2016.pdf
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    References listed on IDEAS

    as
    1. Weron, Rafał & Burnecki, Krzysztof, 2004. "Modeling the risk process in the XploRe computing environment," Papers 2004,08, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    2. Teodorescu, Sandra & Vernic, Raluca, 2009. "Some Composite ExponentialPareto Models for Actuarial Prediction," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 82-100, December.
    3. Gauss Cordeiro & Saralees Nadarajah & Edwin Ortega, 2012. "The Kumaraswamy Gumbel distribution," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(2), pages 139-168, June.
    4. Guillotte, Simon & Perron, Francois & Segers, Johan, 2011. "Non-parametric Bayesian inference on bivariate extremes," LIDAM Reprints ISBA 2011011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Pigeon, Mathieu & Denuit, Michel, 2011. "Composite Lognormal-Pareto model with random threshold," LIDAM Reprints ISBA 2011020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Esmaeili, Habib & Klüppelberg, Claudia, 2010. "Parameter estimation of a bivariate compound Poisson process," Insurance: Mathematics and Economics, Elsevier, vol. 47(2), pages 224-233, October.
    7. Arthur Charpentier & Abder Oulidi, 2010. "Beta kernel quantile estimators of heavy-tailed loss distributions," Post-Print halshs-00425566, HAL.
    8. Drees, Holger & Müller, Peter, 2008. "Fitting and validation of a bivariate model for large claims," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 638-650, April.
    9. Simon Guillotte & François Perron & Johan Segers, 2011. "Non‐parametric Bayesian inference on bivariate extremes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(3), pages 377-406, June.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Queensley C Chukwudum, 2018. "Extreme Value Theory and Copulas: Reinsurance in the Presence of Dependent Risks," Working Papers hal-01855971, HAL.

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    More about this item

    Keywords

    Composite models; Copula; Fast Fourier Transform;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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