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A Multivariate Analysis of Intercompany Loss Triangles

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  • Peng Shi

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  • Peng Shi, 2017. "A Multivariate Analysis of Intercompany Loss Triangles," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(2), pages 717-737, June.
    • Handle: RePEc:bla:jrinsu:v:84:y:2017:i:2:p:717-737
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    File URL: http://hdl.handle.net/10.1111/jori.12102
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    1. Crainiceanu, Ciprian M. & Ruppert, David & Wand, Matthew P., 2005. "Bayesian Analysis for Penalized Spline Regression Using WinBUGS," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i14).
    2. Peters, Gareth W. & Shevchenko, Pavel V. & Wüthrich, Mario V., 2009. "Model Uncertainty in Claims Reserving within Tweedie's Compound Poisson Models," ASTIN Bulletin, Cambridge University Press, vol. 39(1), pages 1-33, May.
    3. Gareth W. Peters & Pavel V. Shevchenko & Mario V. Wuthrich, 2009. "Model uncertainty in claims reserving within Tweedie's compound Poisson models," Papers 0904.1483, arXiv.org.
    4. Merz, Michael & Wüthrich, Mario V., 2010. "Paid-incurred chain claims reserving method," Insurance: Mathematics and Economics, Elsevier, vol. 46(3), pages 568-579, June.
    5. Braun, Christian, 2004. "The Prediction Error of the Chain Ladder Method Applied to Correlated Run-off Triangles," ASTIN Bulletin, Cambridge University Press, vol. 34(2), pages 399-423, November.
    6. Yanwei Zhang & Vanja Dukic, 2013. "Predicting Multivariate Insurance Loss Payments Under the Bayesian Copula Framework," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(4), pages 891-919, December.
    7. Katrien Antonio & Jan Beirlant, 2008. "Issues in Claims Reserving and Credibility: A Semiparametric Approach With Mixed Models," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 75(3), pages 643-676, September.
    8. Jewell, William S., 1990. "Predicting IBNYR Events and Delays II. Discrete Time," ASTIN Bulletin, Cambridge University Press, vol. 20(1), pages 93-111, April.
    9. de Alba, Enrique & Nieto-Barajas, Luis E., 2008. "Claims reserving: A correlated Bayesian model," Insurance: Mathematics and Economics, Elsevier, vol. 43(3), pages 368-376, December.
    10. Zhang, Yanwei, 2010. "A general multivariate chain ladder model," Insurance: Mathematics and Economics, Elsevier, vol. 46(3), pages 588-599, June.
    11. Hess, Klaus Th. & Schmidt, Klaus D. & Zocher, Mathias, 2006. "Multivariate loss prediction in the multivariate additive model," Insurance: Mathematics and Economics, Elsevier, vol. 39(2), pages 185-191, October.
    12. Verrall, R.J., 1990. "Bayes and Empirical Bayes Estimation for the Chain Ladder Model," ASTIN Bulletin, Cambridge University Press, vol. 20(2), pages 217-243, November.
    13. Verrall, Richard, 1996. "Claims reserving and generalised additive models," Insurance: Mathematics and Economics, Elsevier, vol. 19(1), pages 31-43, December.
    14. Jewell, William S., 1989. "Predicting Ibnyr Events and Delays: I. Continuous Time," ASTIN Bulletin, Cambridge University Press, vol. 19(1), pages 25-55, April.
    15. Shi, Peng & Frees, Edward W., 2011. "Dependent Loss Reserving using Copulas," ASTIN Bulletin, Cambridge University Press, vol. 41(2), pages 449-486, November.
    16. Antonio, Katrien & Frees, Edward W. & Valdez, Emiliano A., 2010. "A Multilevel Analysis of Intercompany Claim Counts," ASTIN Bulletin, Cambridge University Press, vol. 40(1), pages 151-177, May.
    17. Shi, Peng, 2014. "A Copula Regression For Modeling Multivariate Loss Triangles And Quantifying Reserving Variability," ASTIN Bulletin, Cambridge University Press, vol. 44(1), pages 85-102, January.
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    Cited by:

    1. Karthik Sriram & Peng Shi, 2021. "Stochastic loss reserving: A new perspective from a Dirichlet model," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(1), pages 195-230, March.
    2. Anas Abdallah & Lan Wang, 2023. "Rank-Based Multivariate Sarmanov for Modeling Dependence between Loss Reserves," Risks, MDPI, vol. 11(11), pages 1-37, October.
    3. Benjamin Avanzi & Xingyun Tan & Greg Taylor & Bernard Wong, 2023. "On the evolution of data breach reporting patterns and frequency in the United States: a cross-state analysis," Papers 2310.04786, arXiv.org, revised Jun 2024.

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