The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists.
Stochastic Processes for Insurance and Finance offers a thorough yet accessible reference for researchers and practitioners of insurance mathematics. Building on recent and rapid developments in applied probability the authors describe in general terms models based on Markov processes, martingales and various types of point processes.
Discussing frequently asked insurance questions, the authors present a coherent overview of this subject and specifically address:
- the principle concepts of insurance and finance
- practical examples with real life data
- numerical and algorithmic procedures essential for modern insurance practices
Assuming competence in probability calculus, this book will provide a rigorous treatment of insurance risk theory recommended for researchers and students interested in applied probability as well as practitioners of actuarial sciences.
‚An excellent text.‘
— Australian & New Zealand Journal of Statistics
Inhaltsverzeichnis
Table of Contents:
Concepts from Insurance and Finance.
Probability Distributions.
Premiums and Ordering of Risks.
Distributions of Aggregate Claim Amount.
Risk Processes.
Renewal Processes and Random Walks.
Markov Chains.
Continuous-Time Markov Models.
Martingale Techniques I.
Martingale Techniques II.
Piecewise Deterministic Markov Processes.
Point Processes.
Diffusion Models.
Distribution Tables.
References.
Index.
Über den Autor
Tomasz Rolski, Mathematical Institute, University of Wroclaw, Poland.
Hanspeter Schmidli, Department of Theoretical Statistics, Aarhus University, Denmark.
Volker Schmidt, Faculty of Mathematics and Economics, University of Ulm, Germany.
Jozef Teugels, Department of Mathematics, Catholic University of Leuven, Belgium.
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