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Rethinking Risk Measurement And Reporting Uncertainty Bayesian Analysis And Expert Judgement
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Book Synopsis Rethinking Risk Measurement and Reporting: Uncertainty, Bayesian analysis and expert judgement by : Klaus Böcker
Download or read book Rethinking Risk Measurement and Reporting: Uncertainty, Bayesian analysis and expert judgement written by Klaus Böcker and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a thorough and rigorous introduction to Bayesian analysis and expert judgment, before moving to more technical content focusing on including stress testing and risk aggregation. A final section is devoted to fundamentals, issues of risk management, such as the nature of risk and cognitive aspects of uncertainty.
Book Synopsis Rethinking Risk Measurement and Reporting by : Klaus Böcker
Download or read book Rethinking Risk Measurement and Reporting written by Klaus Böcker and published by . This book was released on 2010 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Bayesian Theory and Applications by : Paul Damien
Download or read book Bayesian Theory and Applications written by Paul Damien and published by OUP Oxford. This book was released on 2013-01-24 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics. This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on the concept. Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and developments, and who may be looking for ideas that could spawn new research. Hence, the audience for this unique book would likely include academicians/practitioners, and could likely be required reading for undergraduate and graduate students in statistics, medicine, engineering, scientific computation, business, psychology, bio-informatics, computational physics, graphical models, neural networks, geosciences, and public policy. The book honours the contributions of Sir Adrian F. M. Smith, one of the seminal Bayesian researchers, with his papers on hierarchical models, sequential Monte Carlo, and Markov chain Monte Carlo and his mentoring of numerous graduate students -the chapters are authored by prominent statisticians influenced by him. Bayesian Theory and Applications should serve the dual purpose of a reference book, and a textbook in Bayesian Statistics.
Book Synopsis Uncertain Judgements by : Anthony O'Hagan
Download or read book Uncertain Judgements written by Anthony O'Hagan and published by John Wiley & Sons. This book was released on 2006-08-30 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elicitation is the process of extracting expert knowledge about some unknown quantity or quantities, and formulating that information as a probability distribution. Elicitation is important in situations, such as modelling the safety of nuclear installations or assessing the risk of terrorist attacks, where expert knowledge is essentially the only source of good information. It also plays a major role in other contexts by augmenting scarce observational data, through the use of Bayesian statistical methods. However, elicitation is not a simple task, and practitioners need to be aware of a wide range of research findings in order to elicit expert judgements accurately and reliably. Uncertain Judgements introduces the area, before guiding the reader through the study of appropriate elicitation methods, illustrated by a variety of multi-disciplinary examples. This is achieved by: Presenting a methodological framework for the elicitation of expert knowledge incorporating findings from both statistical and psychological research. Detailing techniques for the elicitation of a wide range of standard distributions, appropriate to the most common types of quantities. Providing a comprehensive review of the available literature and pointing to the best practice methods and future research needs. Using examples from many disciplines, including statistics, psychology, engineering and health sciences. Including an extensive glossary of statistical and psychological terms. An ideal source and guide for statisticians and psychologists with interests in expert judgement or practical applications of Bayesian analysis, Uncertain Judgements will also benefit decision-makers, risk analysts, engineers and researchers in the medical and social sciences.
Book Synopsis Expert Judgement in Risk and Decision Analysis by : Anca M. Hanea
Download or read book Expert Judgement in Risk and Decision Analysis written by Anca M. Hanea and published by Springer Nature. This book was released on 2021-02-19 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book pulls together many perspectives on the theory, methods and practice of drawing judgments from panels of experts in assessing risks and making decisions in complex circumstances. The book is divided into four parts: Structured Expert Judgment (SEJ) current research fronts; the contributions of Roger Cooke and the Classical Model he developed; process, procedures and education; and applications. After an Introduction by the Editors, the first part presents chapters on expert elicitation of parameters of multinomial models; the advantages of using performance weighting by advancing the “random expert” hypothesis; expert elicitation for specific graphical models; modelling dependencies between experts’ assessments within a Bayesian framework; preventive maintenance optimization in a Bayesian framework; eliciting life time distributions to parametrize a Dirichlet process; and on an adversarial risk analysis approach for structured expert judgment studies. The second part includes Roger Cooke’s oration from 1995 on taking up his chair at Delft University of Technology; one of the editors reflections on the early decade of the Classical Model development and use; a current overview of the theory of the Classical Model, providing a deep and comprehensive perspective on its foundations and its application; and an interview with Roger Cooke. The third part starts with an interview with Professor Dame Anne Glover, who served as the Chief Scientific Advisor to the President of the European Commission. It then presents chapters on the characteristics of good elicitations by reviewing those advocated and applied; the design and development of a training course for SEJ; and on specific experiences with SEJ protocols with the intention of presenting the challenges and insights collected during these journeys. Finally, the fourth (and largest) part begins with some reflections from Willy Aspinall on his many experiences in applying the Classical Model in several application domains; it continues with related reflections on imperfect elicitations; and then it presents chapters with applications on medicines policy and management, supply chain cyber risk management, geo-political risks, terrorism and the risks facing businesses looking to internationalise.
Book Synopsis Bayesian Risk Management by : Matt Sekerke
Download or read book Bayesian Risk Management written by Matt Sekerke and published by John Wiley & Sons. This book was released on 2015-08-19 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: A risk measurement and management framework that takes model risk seriously Most financial risk models assume the future will look like the past, but effective risk management depends on identifying fundamental changes in the marketplace as they occur. Bayesian Risk Management details a more flexible approach to risk management, and provides tools to measure financial risk in a dynamic market environment. This book opens discussion about uncertainty in model parameters, model specifications, and model-driven forecasts in a way that standard statistical risk measurement does not. And unlike current machine learning-based methods, the framework presented here allows you to measure risk in a fully-Bayesian setting without losing the structure afforded by parametric risk and asset-pricing models. Recognize the assumptions embodied in classical statistics Quantify model risk along multiple dimensions without backtesting Model time series without assuming stationarity Estimate state-space time series models online with simulation methods Uncover uncertainty in workhorse risk and asset-pricing models Embed Bayesian thinking about risk within a complex organization Ignoring uncertainty in risk modeling creates an illusion of mastery and fosters erroneous decision-making. Firms who ignore the many dimensions of model risk measure too little risk, and end up taking on too much. Bayesian Risk Management provides a roadmap to better risk management through more circumspect measurement, with comprehensive treatment of model uncertainty.
Book Synopsis Portfolio Management under Stress by : Riccardo Rebonato
Download or read book Portfolio Management under Stress written by Riccardo Rebonato and published by Cambridge University Press. This book was released on 2013 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: A rigorous presentation of a novel methodology for asset allocation in financial portfolios under conditions of market distress.
Book Synopsis Coherent Stress Testing by : Riccardo Rebonato
Download or read book Coherent Stress Testing written by Riccardo Rebonato and published by John Wiley & Sons. This book was released on 2010-06-10 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Coherent Stress Testing: A Bayesian Approach, industry expert Riccardo Rebonato presents a groundbreaking new approach to this important but often undervalued part of the risk management toolkit. Based on the author's extensive work, research and presentations in the area, the book fills a gap in quantitative risk management by introducing a new and very intuitively appealing approach to stress testing based on expert judgement and Bayesian networks. It constitutes a radical departure from the traditional statistical methodologies based on Economic Capital or Extreme-Value-Theory approaches. The book is split into four parts. Part I looks at stress testing and at its role in modern risk management. It discusses the distinctions between risk and uncertainty, the different types of probability that are used in risk management today and for which tasks they are best used. Stress testing is positioned as a bridge between the statistical areas where VaR can be effective and the domain of total Keynesian uncertainty. Part II lays down the quantitative foundations for the concepts described in the rest of the book. Part III takes readers through the application of the tools discussed in part II, and introduces two different systematic approaches to obtaining a coherent stress testing output that can satisfy the needs of industry users and regulators. In part IV the author addresses more practical questions such as embedding the suggestions of the book into a viable governance structure.
Book Synopsis Rethinking Risk Measurement and Reporting: Examples and applications from finance by : Klaus Böcker
Download or read book Rethinking Risk Measurement and Reporting: Examples and applications from finance written by Klaus Böcker and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A broad spectrum of financial applications are discussed, with practical examples, by risk type (market, credit and operational risk). Volume II builds on the foundations of the first volume, providing a higher degree and intensity of technical content.
Book Synopsis Statistical Rethinking by : Richard McElreath
Download or read book Statistical Rethinking written by Richard McElreath and published by CRC Press. This book was released on 2018-01-03 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.
Book Synopsis Uncertainty in Risk Assessment by : Terje Aven
Download or read book Uncertainty in Risk Assessment written by Terje Aven and published by John Wiley & Sons. This book was released on 2014-02-03 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores methods for the representation and treatment of uncertainty in risk assessment In providing guidance for practical decision-making situations concerning high-consequence technologies (e.g., nuclear, oil and gas, transport, etc.), the theories and methods studied in Uncertainty in Risk Assessment have wide-ranging applications from engineering and medicine to environmental impacts and natural disasters, security, and financial risk management. The main focus, however, is on engineering applications. While requiring some fundamental background in risk assessment, as well as a basic knowledge of probability theory and statistics, Uncertainty in Risk Assessment can be read profitably by a broad audience of professionals in the field, including researchers and graduate students on courses within risk analysis, statistics, engineering, and the physical sciences. Uncertainty in Risk Assessment: Illustrates the need for seeing beyond probability to represent uncertainties in risk assessment contexts. Provides simple explanations (supported by straightforward numerical examples) of the meaning of different types of probabilities, including interval probabilities, and the fundamentals of possibility theory and evidence theory. Offers guidance on when to use probability and when to use an alternative representation of uncertainty. Presents and discusses methods for the representation and characterization of uncertainty in risk assessment. Uses examples to clearly illustrate ideas and concepts.
Book Synopsis Investment Risk Management by : Harold Kent Baker
Download or read book Investment Risk Management written by Harold Kent Baker and published by Oxford University Press, USA. This book was released on 2015 with total page 709 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Foundations of Risk Analysis by : Terje Aven
Download or read book Foundations of Risk Analysis written by Terje Aven and published by John Wiley & Sons. This book was released on 2012-02-02 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Bayesian Methods in Pharmaceutical Research by : Emmanuel Lesaffre
Download or read book Bayesian Methods in Pharmaceutical Research written by Emmanuel Lesaffre and published by CRC Press. This book was released on 2020-04-15 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the early 2000s, there has been increasing interest within the pharmaceutical industry in the application of Bayesian methods at various stages of the research, development, manufacturing, and health economic evaluation of new health care interventions. In 2010, the first Applied Bayesian Biostatistics conference was held, with the primary objective to stimulate the practical implementation of Bayesian statistics, and to promote the added-value for accelerating the discovery and the delivery of new cures to patients. This book is a synthesis of the conferences and debates, providing an overview of Bayesian methods applied to nearly all stages of research and development, from early discovery to portfolio management. It highlights the value associated with sharing a vision with the regulatory authorities, academia, and pharmaceutical industry, with a view to setting up a common strategy for the appropriate use of Bayesian statistics for the benefit of patients. The book covers: Theory, methods, applications, and computing Bayesian biostatistics for clinical innovative designs Adding value with Real World Evidence Opportunities for rare, orphan diseases, and pediatric development Applied Bayesian biostatistics in manufacturing Decision making and Portfolio management Regulatory perspective and public health policies Statisticians and data scientists involved in the research, development, and approval of new cures will be inspired by the possible applications of Bayesian methods covered in the book. The methods, applications, and computational guidance will enable the reader to apply Bayesian methods in their own pharmaceutical research.
Download or read book Risk Analysis written by Terje Aven and published by John Wiley & Sons. This book was released on 2008-04-30 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: Everyday we face decisions that carry an element of risk anduncertainty. The ability to analyze, predict, and prepare for thelevel of risk entailed by these decisions is, therefore, one of themost constant and vital skills needed for analysts, scientists andmanagers. Risk analysis can be defined as a systematic use of informationto identify hazards, threats and opportunities, as well as theircauses and consequences, and then express risk. In order tosuccessfully develop such a systematic use of information, thoseanalyzing the risk need to understand the fundamental concepts ofrisk analysis and be proficient in a variety of methods andtechniques. Risk Analysis adopts a practical, predictiveapproach and guides the reader through a number ofapplications. Risk Analysis: Provides an accessible and concise guide to performing riskanalysis in a wide variety of fields, with minimal prior knowledgerequired. Adopts a broad perspective on risk, with focus on predictionsand highlighting uncertainties beyond expected values andprobabilities, allowing a more flexible approach than traditionalstatistical analysis. Acknowledges that expected values and probabilities couldproduce poor predictions - surprises may occur. Emphasizes the planning and use of risk analyses, rather thanjust the risk analysis methods and techniques, including thestatistical analysis tools. Features many real-life case studies from a variety ofapplications and practical industry problems, including areas suchas security, business and economy, transport, oil & gas and ICT(Information and Communication Technology). Forms an ideal companion volume to Aven’s previous Wileytext Foundations of Risk Analysis. Professor Aven’s previous book Foundations of RiskAnalysis presented and discussed several risk analysisapproaches and recommended a predictive approach. This new textexpands upon this predictive approach, exploring further the riskanalysis principles, concepts, methods and models in an appliedformat. This book provides a useful and practical guide todecision-making, aimed at professionals within the risk analysisand risk management field.
Book Synopsis Bayesian Risk Management by : Matt Sekerke
Download or read book Bayesian Risk Management written by Matt Sekerke and published by John Wiley & Sons. This book was released on 2015-09-15 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: A risk measurement and management framework that takes model risk seriously Most financial risk models assume the future will look like the past, but effective risk management depends on identifying fundamental changes in the marketplace as they occur. Bayesian Risk Management details a more flexible approach to risk management, and provides tools to measure financial risk in a dynamic market environment. This book opens discussion about uncertainty in model parameters, model specifications, and model-driven forecasts in a way that standard statistical risk measurement does not. And unlike current machine learning-based methods, the framework presented here allows you to measure risk in a fully-Bayesian setting without losing the structure afforded by parametric risk and asset-pricing models. Recognize the assumptions embodied in classical statistics Quantify model risk along multiple dimensions without backtesting Model time series without assuming stationarity Estimate state-space time series models online with simulation methods Uncover uncertainty in workhorse risk and asset-pricing models Embed Bayesian thinking about risk within a complex organization Ignoring uncertainty in risk modeling creates an illusion of mastery and fosters erroneous decision-making. Firms who ignore the many dimensions of model risk measure too little risk, and end up taking on too much. Bayesian Risk Management provides a roadmap to better risk management through more circumspect measurement, with comprehensive treatment of model uncertainty.
Book Synopsis Bayesian Inference for Probabilistic Risk Assessment by : Dana Kelly
Download or read book Bayesian Inference for Probabilistic Risk Assessment written by Dana Kelly and published by Springer Science & Business Media. This book was released on 2011-08-30 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Inference for Probabilistic Risk Assessment provides a Bayesian foundation for framing probabilistic problems and performing inference on these problems. Inference in the book employs a modern computational approach known as Markov chain Monte Carlo (MCMC). The MCMC approach may be implemented using custom-written routines or existing general purpose commercial or open-source software. This book uses an open-source program called OpenBUGS (commonly referred to as WinBUGS) to solve the inference problems that are described. A powerful feature of OpenBUGS is its automatic selection of an appropriate MCMC sampling scheme for a given problem. The authors provide analysis “building blocks” that can be modified, combined, or used as-is to solve a variety of challenging problems. The MCMC approach used is implemented via textual scripts similar to a macro-type programming language. Accompanying most scripts is a graphical Bayesian network illustrating the elements of the script and the overall inference problem being solved. Bayesian Inference for Probabilistic Risk Assessment also covers the important topics of MCMC convergence and Bayesian model checking. Bayesian Inference for Probabilistic Risk Assessment is aimed at scientists and engineers who perform or review risk analyses. It provides an analytical structure for combining data and information from various sources to generate estimates of the parameters of uncertainty distributions used in risk and reliability models.
