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Non-Life Insurance Mathematics
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Non-Life Insurance Mathematics

Non-Life Insurance Mathematics

An Introduction with Stochastic Processes

Thomas Mikosch

236 pages, parution le 01/12/2003

Résumé

This book offers a mathematical introduction to non-life insurance and, at the same time, to a multitude of applied stochastic processes. It gives detailed discussions of the fundamental models for claim sizes, claim arrivals, the total claim amount, and their probabilistic properties. Throughout the book the language of stochastic processes is used for describing the dynamics of an insurance portfolio in claim size space and time. In addition to the standard actuarial notions, the reader learns about the basic models of modern non-life insurance mathematics: the Poisson, compound Poisson and renewal processes in collective risk theory and heterogeneity and Bühlmann models in experience rating. The reader gets to know how the underlying probabilistic structures allow one to determine premiums in a portfolio or in an individual policy. Special emphasis is given to the phenomena which are caused by large claims in these models. What makes this book special are more than 100 figures and tables illustrating and visualizing the theory. Every section ends with extensive exercises. They are an integral part of this course since they support the access to the theory.
The book can serve either as a text for an undergraduate/graduate course on non-life insurance mathematics or applied stochastic processes. Its content is in agreement with the European "Group Consultatif" standards. An extensive bibliography, annotated by various comments sections with references to more advanced relevant literature, make the book broadly and easiliy accessible.

Written for:
Students and lecturers of actuarial mathematics, mathematics, economics, physics, statistics, econometrics

Contents

  • Part I Collective Risk Models
    • The Basic Model
    • Models for the Claim Number Process
    • The Total Claim Amount
    • Ruin Theory
  • Part II Experience Rating
    • Bayes Estimation
    • Linear Bayes Estimation
    • References
    • Index

Caractéristiques techniques

  PAPIER
Éditeur(s) Springer
Auteur(s) Thomas Mikosch
Parution 01/12/2003
Nb. de pages 236
Format 15,5 x 23,5
Couverture Broché
Poids 395g
Intérieur Noir et Blanc
EAN13 9783540406501

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