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Multivariate Claim Count Model for Applications in Insurance

Bag om Multivariate Claim Count Model for Applications in Insurance

This monograph presents a time-dynamic model for multivariate claim counts in actuarial applications.Inspired by real-world claim arrivals, the model balances interesting stylized facts (such as dependence across the components, over-dispersion and the clustering of claims) with a high level of mathematical tractability (including estimation, sampling and convergence results for large portfolios) and can thus be applied in various contexts (such as risk management and pricing of (re-)insurance contracts). The authors provide a detailed analysis of the proposed probabilistic model, discussing its relation to the existing literature, its statistical properties, different estimation strategies as well as possible applications and extensions. Actuaries and researchers working in risk management and premium pricing will find this book particularly interesting. Graduate-level probability theory, stochastic analysis and statistics are required.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783319928678
  • Indbinding:
  • Hardback
  • Sideantal:
  • 158
  • Udgivet:
  • 18. september 2018
  • Udgave:
  • 12018
  • Størrelse:
  • 158x241x17 mm.
  • Vægt:
  • 434 g.
Leveringstid: 2-3 uger
Forventet levering: 29. november 2024

Beskrivelse af Multivariate Claim Count Model for Applications in Insurance

This monograph presents a time-dynamic model for multivariate claim counts in actuarial applications.Inspired by real-world claim arrivals, the model balances interesting stylized facts (such as dependence across the components, over-dispersion and the clustering of claims) with a high level of mathematical tractability (including estimation, sampling and convergence results for large portfolios) and can thus be applied in various contexts (such as risk management and pricing of (re-)insurance contracts). The authors provide a detailed analysis of the proposed probabilistic model, discussing its relation to the existing literature, its statistical properties, different estimation strategies as well as possible applications and extensions. Actuaries and researchers working in risk management and premium pricing will find this book particularly interesting. Graduate-level probability theory, stochastic analysis and statistics are required.

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