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. Series: Wiley Series in Probability and Statistics. Num Pages: 674 pages, black & white illustrations. BIC Classification: KFF; PB. Category: (P) Professional & Vocational. Dimension: 157 x 231 x 40. Weight in Grams: 970. . 2009. 1st Edition. Paperback. . . . . Books ship from the US and Ireland.

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Bibliographic Details

Title: Stochastic Processes for Insurance and Finance
Publisher: John Wiley & Sons Inc
Publication Date: 2009
Language: English
ISBN 10: 0470743638
ISBN 13: 9780470743638
Binding: Soft cover
Condition: New

About this title

Synopsis

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

About the Author

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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