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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.  .

Mathematical analysis. --- 517.1 Mathematical analysis --- Mathematical analysis --- Distribution (Probability theory. --- Finance. --- Mathematics. --- Statistics. --- Probability Theory and Stochastic Processes. --- Quantitative Finance. --- Actuarial Sciences. --- Applications of Mathematics. --- Operations Research, Management Science. --- Statistics for Business, Management, Economics, Finance, Insurance. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Math --- Science --- Funding --- Funds --- Economics --- Currency question --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Probabilities. --- Economics, Mathematical . --- Actuarial science. --- Applied mathematics. --- Engineering mathematics. --- Operations research. --- Management science. --- Statistics . --- Quantitative business analysis --- Management --- Problem solving --- Operations research --- Statistical decision --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Engineering --- Engineering analysis --- Statistics --- Insurance --- Mathematical economics --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Methodology

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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.  .

Quantitative methods (economics) --- Finance --- Economics --- Operational research. Game theory --- Mathematical statistics --- Probability theory --- Mathematics --- Financial analysis --- Planning (firm) --- Business economics --- financieel management --- toegepaste wiskunde --- waarschijnlijkheidstheorie --- stochastische analyse --- economie --- mathematische modellen --- statistiek --- financiële analyse --- econometrie --- wiskunde --- operationeel onderzoek --- kansrekening

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Dieses Lehrbuch bietet eine umfassende, moderne Einführung in die wesentlichen Themen und Anwendungen der Wahrscheinlichkeitstheorie. Es liefert eine sehr gut motivierte, anspruchsvolle und weitreichende Darstellung, bleibt aber dennoch vorlesungsnah und verzichtet auf unnötige formalistische Hürden. Ziel des Autors ist es insbesondere, die Bedeutung und Faszination dieses Gebiets für zentrale Anwendungen spürbar werden zu lassen. Das Buch ermöglicht dem Leser somit, ein hervorragendes Verständnis der Begriffe, Methoden und der Kerninhalte der Wahrscheinlichkeitstheorie sowie der Grundlagen der stochastischen Prozesse und deren Anwendungen zu gewinnen. .

Probabilities. --- Probability Theory and Stochastic Processes.

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The book provides an introduction to advanced topics in stochastic processes and related stochastic analysis, and combines them with a sound presentation of the fundamentals of financial mathematics. It is wide-ranging in content, while at the same time placing much emphasis on good readability, motivation, and explanation of the issues covered. This book is a translation of the original German 1st edition Stochastische Prozesse und Finanzmathematik by Ludger Rüschendorf, published by Springer-Verlag GmbH Germany, part of Springer Nature in 2020. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com) and in a subsequent editing, improved by the author. Springer Nature works continuously to further the development of tools for the production of books and on the related technologies to support the authors. Financial mathematical topics are first introduced in the context of discrete time processes and then transferred to continuous-time models. The basic construction of the stochastic integral and the associated martingale theory provide fundamental methods of the theory of stochastic processes for the construction of suitable stochastic models of financial mathematics, e.g. using stochastic differential equations. Central results of stochastic analysis such as the Itô formula, Girsanov's theorem and martingale representation theorems are of fundamental importance in financial mathematics, e.g. for the risk-neutral valuation formula (Black-Scholes formula) or the question of the hedgeability of options and the completeness of market models. Chapters on the valuation of options in complete and incomplete markets and on the determination of optimal hedging strategies conclude the range of topics. Advanced knowledge of probability theory is assumed, in particular of discrete-time processes (martingales, Markov chains) and continuous-time processes (Brownian motion, Lévy processes, processes with independent increments, Markov processes). The book is thus suitable for advanced students as a companion reading and for instructors as a basis for their own courses. The Author Prof. Dr. Ludger Rüschendorf is professor at the University of Freiburg in the field of mathematical stochastics since 1993. Previously, he taught and conducted research at the universities of Hamburg, Aachen, Freiburg, and Münster.

Stochastic processes. --- Social sciences—Mathematics. --- Stochastic Processes. --- Mathematics in Business, Economics and Finance. --- Random processes --- Probabilities --- Social sciences --- Mathematics. --- Processos estocàstics --- Matemàtica financera

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Marginal distributions --- Congresses