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Hardcover. Condizione: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less.
Lingua: Inglese
Editore: Springer-Verlag Publishing, 2011
ISBN 10: 3642159222 ISBN 13: 9783642159220
Da: Salish Sea Books, Bellingham, WA, U.S.A.
Condizione: Like New. Fine/As New; Hardcover; Covers are still glossy with "sharp" edge-corners; Unblemished textblock edges; The endpapers and all text pages are bright and unmarked; Binding is tight with a straight spine; This book will be shipped in a sturdy cardboard box with foam padding; Medium Format (8.5" - 9.75" tall); Yellow and purple covers with title in blue lettering; 2011, Springer-Verlag Publishing; 319 pages; "Modelling Operational Risk Using Bayesian Inference," by Pavel V. Shevchenko.
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Aggiungi al carrelloCondizione: New. KlappentextrnrnAn ageing population is a major challenge for every country in the world arising from the declining fertility rate and increasing life expectancy. A longevity risk (the adverse outcome of people living longer than expected) exacer.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware - An ageing population is a major challenge for every country in the world arising from the declining fertility rate and increasing life expectancy. A longevity risk (the adverse outcome of people living longer than expected) exacerbated by declining equity returns coupled with the record low interest rate environments has significant implications for societies and manifests as a systematic risk for providers of retirement income products. The aim of this special issue is to highlight advances in quantitative modelling of risks related to ageing population problems. It is aimed at practitioners and regulators in insurance, banking and pension industries; academic researchers; and advanced graduate students in the area.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Modelling Operational Risk Using Bayesian Inference | Pavel V. Shevchenko | Taschenbuch | xvii | Englisch | 2014 | Springer | EAN 9783642423536 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Aggiungi al carrelloHardcover. Condizione: Brand New. 302 pages. 9.00x6.25x1.00 inches. In Stock.
Lingua: Inglese
Editore: Springer Berlin Heidelberg, 2014
ISBN 10: 3642423531 ISBN 13: 9783642423536
Da: AHA-BUCH GmbH, Einbeck, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The management of operational risk in the banking industry has undergone explosive changes over the last decade due to substantial changes in the operational environment. Globalization, deregulation, the use of complex financial products, and changes in information technology have resulted in exposure to new risks which are very different from market and credit risks. In response, the Basel Committee on Banking Supervision has developed a new regulatory framework for capital measurement and standards for the banking sector. This has formally defined operational risk and introduced corresponding capital requirements.Many banks are undertaking quantitative modelling of operational risk using the Loss Distribution Approach (LDA) based on statistical quantification of the frequency and severity of operational risk losses. There are a number of unresolved methodological challenges in the LDA implementation. Overall, the area of quantitative operational risk is very new and different methods are under hot debate.This book is devoted to quantitative issues in LDA. In particular, the use of Bayesian inference is the main focus. Though it is very new in this area, the Bayesian approach is well suited for modelling operational risk, as it allows for a consistent and convenient statistical framework for quantifying the uncertainties involved. It also allows for the combination of expert opinion with historical internal and external data in estimation procedures. These are critical, especially for low-frequency/high-impact operational risks.This book is aimed at practitioners in risk management, academic researchers in financial mathematics, banking industry regulators and advanced graduate students in the area. It is a must-read for anyone who works, teaches or does research in the area of financial risk.
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The management of operational risk in the banking industry has undergone explosive changes over the last decade due to substantial changes in the operational environment. Globalization, deregulation, the use of complex financial products, and changes in information technology have resulted in exposure to new risks which are very different from market and credit risks. In response, the Basel Committee on Banking Supervision has developed a new regulatory framework for capital measurement and standards for the banking sector. This has formally defined operational risk and introduced corresponding capital requirements.Many banks are undertaking quantitative modelling of operational risk using the Loss Distribution Approach (LDA) based on statistical quantification of the frequency and severity of operational risk losses. There are a number of unresolved methodological challenges in the LDA implementation. Overall, the area of quantitative operational risk is very new and different methods are under hot debate.This book is devoted to quantitative issues in LDA. In particular, the use of Bayesian inference is the main focus. Though it is very new in this area, the Bayesian approach is well suited for modelling operational risk, as it allows for a consistent and convenient statistical framework for quantifying the uncertainties involved. It also allows for the combination of expert opinion with historical internal and external data in estimation procedures. These are critical, especially for low-frequency/high-impact operational risks.This book is aimed at practitioners in risk management, academic researchers in financial mathematics, banking industry regulators and advanced graduate students in the area. It is a must-read for anyone who works, teaches or does research in the area of financial risk.