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Solvency capital requirement for a temporal dependent losses in insurance

Author

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  • Araichi, Sawssen
  • Peretti, Christian de
  • Belkacem, Lotfi

Abstract

This article addresses the appropriate modeling of losses for the insurance sector. In fact, solvency 2 framework has suggested some formulas to evaluate losses and solvency capital using an internal approach. However, these formulas where derived under the assumption of independent losses. Thus, the amount of capital may be inaccurate when losses are dependent, which is the case in practice. The aim of this paper is to investigate temporal dependence structure among claim amounts (losses). For that, a novel model named autoregressive conditional amount (ACA) model handling the dynamic behavior of claim amounts in insurance companies is proposed. Results show that ACA models allow to predict accurately the future claims. Moreover, a measure of risk namely value at risk (VaR) ACA that could hedge daily dependent losses is provided. By backtesting techniques, empirical results show that the new VaR ACA can efficiently evaluate the coverage amount of risks.

Suggested Citation

  • Araichi, Sawssen & Peretti, Christian de & Belkacem, Lotfi, 2016. "Solvency capital requirement for a temporal dependent losses in insurance," Economic Modelling, Elsevier, vol. 58(C), pages 588-598.
  • Handle: RePEc:eee:ecmode:v:58:y:2016:i:c:p:588-598
    DOI: 10.1016/j.econmod.2016.03.007
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    References listed on IDEAS

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    Cited by:

    1. Araichi, Sawssen & Peretti, Christian de & Belkacem, Lotfi, 2017. "Reserve modelling and the aggregation of risks using time varying copula models," Economic Modelling, Elsevier, vol. 67(C), pages 149-158.
    2. Eling, Martin & Jung, Kwangmin, 2018. "Copula approaches for modeling cross-sectional dependence of data breach losses," Insurance: Mathematics and Economics, Elsevier, vol. 82(C), pages 167-180.
    3. Li, Xuelian & Lin, Panpan & Lin, Jyh-Horng, 2020. "COVID-19, insurer board utility, and capital regulation," Finance Research Letters, Elsevier, vol. 36(C).
    4. Saker Sabkha & Christian Peretti & Dorra Hmaied, 2019. "On the informational market efficiency of the worldwide sovereign credit default swaps," Journal of Asset Management, Palgrave Macmillan, vol. 20(7), pages 581-608, December.
    5. Kartik Sethi & Siddhartha P. Chakrabarty, 2021. "Modeling premiums of non-life insurance companies in India," Papers 2106.02446, arXiv.org.

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    More about this item

    Keywords

    Claim amounts; Temporal dependence; Generalized extreme value model; Value at risk; Backtesting;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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