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Probability Distributions in Risk Management Operations

This book is about the formulations, theoretical investigations, and practical applications of new stochastic models for fundamental concepts and operations of the discipline of risk management. It also examines how these models can be useful in the descriptions, measurements, evaluations, and treatments of risks threatening various modern organizations. Moreover, the book makes clear that such stochastic models constitute very strong analytical tools which substantially facilitate strategic thinking and strategic decision making in many significant areas of risk management. In particular the incorporation of fundamental probabilistic concepts such as the sum, minimum, and maximum of a random number of continuous, positive, independent, and identically distributed random variables in the mathematical structure of stochastic models significantly supports the suitability of these models in the developments, investigations, selections, and implementations of proactive and reactive risk management operations. The book makes extensive use of integral and differential equations of characteristic functions, mainly corresponding to important classes of mixtures of probability distributions, as powerful analytical tools for investigating the behavior of new stochastic models suitable for the descriptions and implementations of fundamental risk control and risk financing operations. These risk treatment operations very often arise in a wide variety of scientific disciplines of extreme practical importance.

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Series Title
Series Title Intelligent Systems Reference Library
Call Number
519.2 ART p
Publisher
Piraeus, Greece : Springer International Publishing.,
Collation
-
Language
English
ISBN/ISSN
978-3-319-14256-2
Classification
519.2
Content Type
text
Media Type
computer
Carrier Type
online resource
Edition
1
Subject(s)
Probabilitas
Specific Detail Info
-
Statement of Responsibility
Other Information
Cataloger
Erwin
Source
https://link.springer.com/10.1007/978-3-319-14256-2
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