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Author: Constantinos Artikis
Publisher: Springer
ISBN: 3319142569
Category : Technology & Engineering
Languages : en
Pages : 329
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Book Description
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.
Author: Constantinos Artikis
Publisher: Springer
ISBN: 3319142569
Category : Technology & Engineering
Languages : en
Pages : 329
Get Book
Book Description
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.
Author: Matthew J. Hassett
Publisher: ACTEX Publications
ISBN: 156698548X
Category : Business & Economics
Languages : en
Pages : 448
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Book Description
Author: Giovanni De Luca
Publisher: Springer Nature
ISBN: 3030425800
Category : Business & Economics
Languages : en
Pages : 84
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Book Description
This concise book for practitioners presents the statistical analysis of operational risk, which is considered the most relevant source of bank risk, after market and credit risk. The book shows that a careful statistical analysis can improve the results of the popular loss distribution approach. The authors identify the risk classes by applying a pooling rule based on statistical tests of goodness-of-fit, use the theory of the mixture of distributions to analyze the loss severities, and apply copula functions for risk class aggregation. Lastly, they assess operational risk data in order to estimate the so-called capital-at-risk that represents the minimum capital requirement that a bank has to hold. The book is primarily intended for quantitative analysts and risk managers, but also appeals to graduate students and researchers interested in bank risks.
Author: Tim Bedford
Publisher: Cambridge University Press
ISBN: 9780521773201
Category : Mathematics
Languages : en
Pages : 228
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Book Description
A graduate level textbook on probabilistic risk analysis, aimed at statisticians, operations researchers and engineers.
Author: I. Moosa
Publisher: Springer
ISBN: 0230591485
Category : Business & Economics
Languages : en
Pages : 255
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Book Description
Written by an experienced academic and practitioner, Operational Risk Management fills a gap in the information available on the Basel 2 Accord and offers valuable insights into the nature of operational risk.
Author: Catalina Bolance
Publisher: CRC Press
ISBN: 1439895937
Category : Business & Economics
Languages : en
Pages : 236
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Book Description
Using real-life examples from the banking and insurance industries, Quantitative Operational Risk Models details how internal data can be improved based on external information of various kinds. Using a simple and intuitive methodology based on classical transformation methods, the book includes real-life examples of the combination of internal dat
Author: Mohammad Modarres
Publisher: CRC Press
ISBN: 1420003496
Category : Mathematics
Languages : en
Pages : 408
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Book Description
Based on the author's 20 years of teaching, Risk Analysis in Engineering: Techniques, Tools, and Trends presents an engineering approach to probabilistic risk analysis (PRA). It emphasizes methods for comprehensive PRA studies, including techniques for risk management. The author assumes little or no prior knowledge of risk analysis on the p
Author: Ron S. Kenett
Publisher: John Wiley & Sons
ISBN: 1119956722
Category : Business & Economics
Languages : en
Pages : 339
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Book Description
Models and methods for operational risks assessment and mitigation are gaining importance in financial institutions, healthcare organizations, industry, businesses and organisations in general. This book introduces modern Operational Risk Management and describes how various data sources of different types, both numeric and semantic sources such as text can be integrated and analyzed. The book also demonstrates how Operational Risk Management is synergetic to other risk management activities such as Financial Risk Management and Safety Management. Operational Risk Management: a practical approach to intelligent data analysis provides practical and tested methodologies for combining structured and unstructured, semantic-based data, and numeric data, in Operational Risk Management (OpR) data analysis. Key Features: The book is presented in four parts: 1) Introduction to OpR Management, 2) Data for OpR Management, 3) OpR Analytics and 4) OpR Applications and its Integration with other Disciplines. Explores integration of semantic, unstructured textual data, in Operational Risk Management. Provides novel techniques for combining qualitative and quantitative information to assess risks and design mitigation strategies. Presents a comprehensive treatment of "near-misses" data and incidents in Operational Risk Management. Looks at case studies in the financial and industrial sector. Discusses application of ontology engineering to model knowledge used in Operational Risk Management. Many real life examples are presented, mostly based on the MUSING project co-funded by the EU FP6 Information Society Technology Programme. It provides a unique multidisciplinary perspective on the important and evolving topic of Operational Risk Management. The book will be useful to operational risk practitioners, risk managers in banks, hospitals and industry looking for modern approaches to risk management that combine an analysis of structured and unstructured data. The book will also benefit academics interested in research in this field, looking for techniques developed in response to real world problems.
Author: Panagiotis T. Artikis
Publisher: Springer Nature
ISBN: 3030956911
Category : Technology & Engineering
Languages : en
Pages : 295
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Book Description
This book contributes to the area of ongoing global risks and the area of forthcoming global risks, particularly necessary for the implementation of very important interdisciplinary research activities. Global risks are defined in this study as having a global geographical scope, an inter-industrial presence, and exceptionally critical stages of economic and social participation that necessitate a major multi-stakeholder input. In addition, global risks demand an extremely extensive priority in decision-making allowance. The theoretical and practical results of this work are strongly connected to several quite useful factors. The present work mainly concentrates on the contribution of probability theory in the advancement of the practical applicability of global risk governance. More precisely, the work introduces structural stochastic concepts and fundamental stochastic results for the formulation of stochastic models of various global risk governance operations particularly valuable in proactive treatment of several groups of global risks.
Author: Terje Aven
Publisher: John Wiley & Sons
ISBN: 1119966973
Category : Mathematics
Languages : en
Pages : 245
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Book Description
Foundations of Risk Analysis presents the issues core to risk analysis – understanding what risk means, expressing risk, building risk models, addressing uncertainty, and applying probability models to real problems. The author provides the readers with the knowledge and basic thinking they require to successfully manage risk and uncertainty to support decision making. This updated edition reflects recent developments on risk and uncertainty concepts, representations and treatment. New material in Foundations of Risk Analysis includes: An up to date presentation of how to understand, define and describe risk based on research carried out in recent years. A new definition of the concept of vulnerability consistent with the understanding of risk. Reflections on the need for seeing beyond probabilities to measure/describe uncertainties. A presentation and discussion of a method for assessing the importance of assumptions (uncertainty factors) in the background knowledge that the subjective probabilities are based on A brief introduction to approaches that produce interval (imprecise) probabilities instead of exact probabilities. In addition the new version provides a number of other improvements, for example, concerning the use of cost-benefit analyses and the As Low As Reasonably Practicable (ALARP) principle. Foundations of Risk Analysis provides a framework for understanding, conducting and using risk analysis suitable for advanced undergraduates, graduates, analysts and researchers from statistics, engineering, finance, medicine and the physical sciences, as well as for managers facing decision making problems involving risk and uncertainty.
