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The Method of Moments for Multivariate Random Sums

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Abstract

Multivariate random sums appear in many scienti c elds, most no- tably in actuarial science, where they model both the number of claims and their sizes. Unfortunately, they pose severe inferential problems. For example, their density function is analytically intractable, in the general case, thus preventing likelihood inference. In this paper, we address the problem by the method of moments, under the assumption that the claim size and the claim number have a multivariate skew-normal and a Poisson distribution, respectively. In doing so, we also derive closed-form expres- sions for some fundamental measures of multivariate kurtosis and high- light some limitations of both projection pursuit and invariant coordinate selection.

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  • Javed, Farrukh & Loperfido, Nicola & Mazur, Stepan, 2024. "The Method of Moments for Multivariate Random Sums," Working Papers 2024:6, Örebro University, School of Business.
    • Handle: RePEc:hhs:oruesi:2024_006
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    References listed on IDEAS

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    1. Kollo, Tõnu, 2008. "Multivariate skewness and kurtosis measures with an application in ICA," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2328-2338, November.
    2. Archimbaud, Aurore & Nordhausen, Klaus & Ruiz-Gazen, Anne, 2018. "ICS for multivariate outlier detection with application to quality control," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 184-199.
    3. Peña, Daniel & Prieto, Francisco J. & Viladomat, Júlia, 2010. "Eigenvectors of a kurtosis matrix as interesting directions to reveal cluster structure," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 1995-2007, October.
    4. Pena D. & Prieto F.J., 2001. "Cluster Identification Using Projections," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1433-1445, December.
    5. Ambagaspitiya, Rohana S., 1999. "On the distributions of two classes of correlated aggregate claims," Insurance: Mathematics and Economics, Elsevier, vol. 24(3), pages 301-308, May.
    6. Nicola Loperfido & Stepan Mazur & Krzysztof Podgórski, 2018. "Third cumulant for multivariate aggregate claim models," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2018(2), pages 109-128, February.
    7. Eling, Martin, 2012. "Fitting insurance claims to skewed distributions: Are the skew-normal and skew-student good models?," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 239-248.
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    More about this item

    Keywords

    Fourth cumulant; Kurtosis; Poisson distribution; Skew-normal distribution.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

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