Mathematical Risk Analysis
Dependence, Risk Bounds, Optimal Allocations and Portfolios
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Beschreibung
The author's particular interest in the area of risk measures is to combine this theory with the analysis of dependence properties. The present volume gives an introduction of basic concepts and methods in mathematical risk analysis, in particular of those parts of risk theory that are of special relevance to finance and insurance. Describing the influence of dependence in multivariate stochastic models on risk vectors is the main focus of the text that presents main ideas and methods as well as their relevance to practical applications. The first part introduces basic probabilistic tools and methods of distributional analysis, and describes their use to the modeling of dependence and to the derivation of risk bounds in these models. In the second, part risk measures with a particular focus on those in the financial and insurance context are presented. The final parts are then devoted to applications relevant to optimal risk allocation, optimal portfolio problems as well as to the optimization of insurance contracts.
Good knowledge of basic probability and statistics as well as of basic general mathematics is a prerequisite for comfortably reading and working with the present volume, which is intended for graduate students, practitioners and researchers and can serve as a reference resource for the main concepts and techniques.
The author's particular interest in the area of risk measures is to combine this theory with the analysis of dependence properties. The present volume gives an introduction of basic concepts and methods in mathematical risk analysis, in particular of those parts of risk theory that are of special relevance to finance and insurance. Describing the influence of dependence in multivariate stochastic models on risk vectors is the main focus of the text that presents main ideas and methods as well as their relevance to practical applications. The first part introduces basic probabilistic tools and methods of distributional analysis, and describes their use to the modeling of dependence and to the derivation of risk bounds in these models. In the second, part risk measures with a particular focus on those in the financial and insurance context are presented. The final parts are then devoted to applications relevant to optimal risk allocation, optimal portfolio problems as well as to the optimization of insurance contracts. Good knowledge of basic probability and statistics as well as of basic general mathematics is a prerequisite for comfortably reading and working with the present volume, which is intended for graduate students, practitioners and researchers and can serve as a reference resource for the main concepts and techniques.
Up-to-date treatment of the main concepts and techniques used in mathematical risk analysis Clearly structured guide Gives orientation and help to acquire a solid fundament for working in this area? Includes supplementary material: sn.pub/extras
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Ludger Rüschendorf
Themen in »Mathematical Risk Analysis«
62P05 , 91B30 , 91B28 ,60G70 Fréchet-classes mathematical risk analysis optimal portfolios and insurance contracts risk bounds risk measures quantitative finance
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From the reviews:
“The book contains four parts: stochastic dependence and extremal risk, risk measures and worst case portfolios, optimal risk allocation, and optimal portfolios and extreme risk. … the book will be definitely interesting to researchers and graduate students in the areas of insurance, financial mathematics, risk management, etc., as it gives a clear picture which research directions have been pursued and to what extent.” (Jonas Šiaulys, zbMATH, Vol. 1266, 2013)()