Modelling Operational Risk Using Bayesian Inference
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Modelling Operational Risk Using Bayesian Inference
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Author : Pavel V. Shevchenko
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-01-19
Modelling Operational Risk Using Bayesian Inference written by Pavel V. Shevchenko and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-19 with Business & Economics categories.
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.
Operational Risk Management
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Author : Ron S. Kenett
language : en
Publisher: John Wiley & Sons
Release Date : 2011-06-20
Operational Risk Management written by Ron S. Kenett and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-20 with Business & Economics categories.
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.
Investment Risk Management
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Author : Harold Kent Baker
language : en
Publisher: Oxford University Press, USA
Release Date : 2015
Investment Risk Management written by Harold Kent Baker and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Business & Economics categories.
Investment Risk Management provides an overview of developments in risk management and a synthesis of research on the subject. The chapters examine ways to alter exposures through measuring and managing risk exposures and provide an understanding of the latest strategies and trends within risk management.
Financial Modeling Actuarial Valuation And Solvency In Insurance
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Author : Mario V. Wüthrich
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-04
Financial Modeling Actuarial Valuation And Solvency In Insurance written by Mario V. Wüthrich and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-04 with Mathematics categories.
Risk management for financial institutions is one of the key topics the financial industry has to deal with. The present volume is a mathematically rigorous text on solvency modeling. Currently, there are many new developments in this area in the financial and insurance industry (Basel III and Solvency II), but none of these developments provides a fully consistent and comprehensive framework for the analysis of solvency questions. Merz and Wüthrich combine ideas from financial mathematics (no-arbitrage theory, equivalent martingale measure), actuarial sciences (insurance claims modeling, cash flow valuation) and economic theory (risk aversion, probability distortion) to provide a fully consistent framework. Within this framework they then study solvency questions in incomplete markets, analyze hedging risks, and study asset-and-liability management questions, as well as issues like the limited liability options, dividend to shareholder questions, the role of re-insurance, etc. This work embeds the solvency discussion (and long-term liabilities) into a scientific framework and is intended for researchers as well as practitioners in the financial and actuarial industry, especially those in charge of internal risk management systems. Readers should have a good background in probability theory and statistics, and should be familiar with popular distributions, stochastic processes, martingales, etc.
Modelling Operational Risk Using A Bayesian Approach To Extreme Value Theory
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Author : María Elena Rivera Mancía
language : en
Publisher:
Release Date : 2014
Modelling Operational Risk Using A Bayesian Approach To Extreme Value Theory written by María Elena Rivera Mancía and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
"Extreme-value theory is concerned with the tail behaviour of probability distributions. In recent years, it has found many applications in areas as diverse as hydrology, actuarial science, and finance, where complex phenomena must often be modelled from a small number of observations.Extreme-value theory can be used to assess the risk of rare events either through the block maxima or peaks-over-threshold method. The choice of threshold is both influential and delicate, as a balance between the bias and variance of the estimates is required. At present, this threshold is often chosen arbitrarily, either graphically or by setting it as some high quantile of the data.Bayesian inference is an alternative to deal with this problem by treating the threshold as a parameter in the model. In addition, a Bayesian approach allows for the incorporation of internal and external observations in combination with expert opinion, thereby providing a natural probabilistic framework to evaluate risk models.This thesis presents a Bayesian inference framework for extremes. We focus on a model proposed by Behrens et al. (2004), where an analysis of extremes is performed using a mixture model that combines a parametric form for the centre and a Generalized Pareto Distribution (GPD) for the tail of the distribution. Our approach accounts for all the information available in making inference about the unknown parameters from both distributions, the threshold included. A Bayesian analysis is then performed by using expert opinions to determine the parameters for prior distributions; posterior inference is carried out through Markov Chain Monte Carlo methods. We apply this methodology to operational risk data to analyze its performance.The contributions of this thesis can be outlined as follows:-Bayesian models have been barely explored in operational risk analysis. In Chapter 3, we show how these models can be adapted to operational risk analysis using fraud data collected by different banks between 2007 and 2010. By combining prior information to the data, we can estimate the minimum capital requirement and risk measures such as the Value-at-Risk (VaR) and the Expected Shortfall (ES) for each bank.-The use of expert opinion plays a fundamental role in operational risk modelling. However, most of time this issue is not addressed properly. In Chapter 4, we consider the context of the problem and show how to construct a prior distribution based on measures that experts are familiar with, including VaR and ES. The purpose is to facilitate prior elicitation and reproduce expert judgement faithfully.-In Section 4.3, we describe techniques for the combination of expert opinions. While this issue has been addressed in other fields, it is relatively recent in our context. We examine how different expert opinions may influence the posterior distribution and how to build a prior distribution in this case. Results are presented on simulated and real data.-In Chapter 5, we propose several new mixture models with Gamma and Generalized Pareto elements. Our models improve upon previous work by Behrens et al. (2004) since the loss distribution is either continuous at a fixed quantile or it has continuous first derivative at the blend point. We also consider the cases when the scaling is arbitrary and when the density is discontinuous.-Finally, we introduce two nonparametric models. The first one is based on the fact that the GPD model can be represented as a Gamma mixture of exponential distributions, while the second uses a Dirichlet process prior on the parameters of the GPD model." --
Quantum Social Science
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Author : Emmanuel Haven
language : en
Publisher: Cambridge University Press
Release Date : 2013-01-17
Quantum Social Science written by Emmanuel Haven and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-17 with Psychology categories.
Written by world experts in the foundations of quantum mechanics, this book shows how elementary quantum mechanical principles can be applied to social sciences problems. Aimed at economists and psychologists, as well as physicists, it explores the exciting field of quantum social science.
E Business Technology And Strategy
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Author : Marzia Zaman
language : en
Publisher: Springer
Release Date : 2010-09-27
E Business Technology And Strategy written by Marzia Zaman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-27 with Business & Economics categories.
The International Conference on E-business Technology & Strategy (CETS) provides a peer-reviewed forum for researchers from across the globe to share contemporary research on developments in the fields of e-business, information technology and business strategy. It seeks to promote effective and vibrant networking among researchers and practitioners from around the world who are concerned about the effective management of information technology in organizations. This network of researchers views fostering the development of emerging scholars in the information technology and e-business fields as its primary task. Consequently the conference is designed to provide a venue for researchers to get substantive and beneficial feedback on their work. There were 134 contributions submitted to CETS 2010. After in-depth discussions, 29 high-quality contributions were selected for publication in this volume. The authors are from Canada, USA, China, Japan, India and Malaysia. We thank all the authors who submitted papers, the Program Committee members, and the external reviewers. We also thank all the local people who were instrumental in making this edition of CETS another very successful event. In particular, we are very grateful to Ying Xie, who was responsible for the local arrangements. Special gratitude goes to the publishing editor, Leonie Kunz, who managed the complexity of information and communication aspects. Furthermore, we thank the many students who volunteered on the organization team, as well as the IT services of Carleton University.
Quantitative Operational Risk Models
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Author : Catalina Bolance
language : en
Publisher: CRC Press
Release Date : 2012-02-15
Quantitative Operational Risk Models written by Catalina Bolance and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-15 with Business & Economics categories.
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
Operational Risk Capital Models
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Author : Rafael Cavestany
language : en
Publisher:
Release Date : 2015
Operational Risk Capital Models written by Rafael Cavestany and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Financial risk management categories.
"Operational Risk Capital Models is a guide for the implementation of state of the art operational risk capital models suitable for regulatory approval. For insurers, Solvency II implementation has created the need, in both highly developed and less developed markets, for the development of these models that help to better understand risks, safe capital and compliance. For the banking industry, regulators in many countries in Africa, Asia and Latin America (as well as Europe) are pressing their local banks to implement advanced operational risk capital models. Banks that have made early implementation are looking to improve their capital models with new advances to match the increasing regulatory requirements. Operational Risk Capital Models enables you to model your operational risk capital to ensure the model meets regulatory standards. It describes the process end to end, from the capture of the required data to the modelling and VaR calculation, as well as the integration of capital results into your institution's daily risk management." --Contratapa.
Enterprise Development In Smes And Entrepreneurial Firms Dynamic Processes
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Author : Ndubisi, Nelson Oly
language : en
Publisher: IGI Global
Release Date : 2013-02-28
Enterprise Development In Smes And Entrepreneurial Firms Dynamic Processes written by Ndubisi, Nelson Oly and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-28 with Business & Economics categories.
In order to increase the economic opportunities available, enterprise development plays a crucial role in the progression of socio-economic development for small and medium enterprises. Enterprise Development in SMEs and Entrepreneurial Firms: Dynamic Processes explores the process of enterprise development and its reconstruction of entrepreneurial identities, critical competencies as well as market turnaround for SMEs. This book aims to be a critical resource in the understanding of enterprise strategies adopted and lessons learned for management development. It is a successful resource for students, researchers and professionals interested in the growth SMEs.