Bayesian Risk Management
DOWNLOAD
Download Bayesian Risk Management PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Bayesian Risk Management book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Bayesian Methods In Finance
DOWNLOAD
Author : Svetlozar T. Rachev
language : en
Publisher: John Wiley & Sons
Release Date : 2008-02-13
Bayesian Methods In Finance written by Svetlozar T. Rachev 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 2008-02-13 with Business & Economics categories.
Bayesian Methods in Finance provides a detailed overview of the theory of Bayesian methods and explains their real-world applications to financial modeling. While the principles and concepts explained throughout the book can be used in financial modeling and decision making in general, the authors focus on portfolio management and market risk management—since these are the areas in finance where Bayesian methods have had the greatest penetration to date.
Coherent Stress Testing
DOWNLOAD
Author : Riccardo Rebonato
language : en
Publisher: John Wiley & Sons
Release Date : 2010-06-10
Coherent Stress Testing written by Riccardo Rebonato 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 2010-06-10 with Business & Economics categories.
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.
Bayesian Decision Analysis
DOWNLOAD
Author : Jim Q. Smith
language : en
Publisher: Cambridge University Press
Release Date : 2010-09-23
Bayesian Decision Analysis written by Jim Q. Smith 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 2010-09-23 with Mathematics categories.
Bayesian decision analysis supports principled decision making in complex domains. This textbook takes the reader from a formal analysis of simple decision problems to a careful analysis of the sometimes very complex and data rich structures confronted by practitioners. The book contains basic material on subjective probability theory and multi-attribute utility theory, event and decision trees, Bayesian networks, influence diagrams and causal Bayesian networks. The author demonstrates when and how the theory can be successfully applied to a given decision problem, how data can be sampled and expert judgements elicited to support this analysis, and when and how an effective Bayesian decision analysis can be implemented. Evolving from a third-year undergraduate course taught by the author over many years, all of the material in this book will be accessible to a student who has completed introductory courses in probability and mathematical statistics.
Bayesian Risk Management
DOWNLOAD
Author : Matt Sekerke
language : en
Publisher: John Wiley & Sons
Release Date : 2015-08-19
Bayesian Risk Management written by Matt Sekerke 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 2015-08-19 with Business & Economics categories.
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.
Scenario Analysis In Risk Management
DOWNLOAD
Author : Bertrand K. Hassani
language : en
Publisher: Springer
Release Date : 2016-10-26
Scenario Analysis In Risk Management written by Bertrand K. Hassani and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-26 with Business & Economics categories.
This book focuses on identifying and explaining the key determinants of scenario analysis in the context of operational risk, stress testing and systemic risk, as well as management and planning. Each chapter presents alternative solutions to perform reliable scenario analysis. The author also provides technical notes and describes applications and key characteristics for each of the solutions. In addition, the book includes a section to help practitioners interpret the results and adjust them to real-life management activities. Methodologies, including those derived from consensus strategies, extreme value theory, Bayesian networks, Neural networks, Fault Trees, frequentist statistics and data mining are introduced in such a way as to make them understandable to readers without a quantitative background. Particular emphasis is given to the added value of the implementation of these methodologies.
Bayesian Networks
DOWNLOAD
Author : Olivier Pourret
language : en
Publisher: John Wiley & Sons
Release Date : 2008-04-30
Bayesian Networks written by Olivier Pourret 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 2008-04-30 with Mathematics categories.
Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.
Risk Assessment And Decision Analysis With Bayesian Networks
DOWNLOAD
Author : Norman Fenton
language : en
Publisher: CRC Press
Release Date : 2012-11-07
Risk Assessment And Decision Analysis With Bayesian Networks written by Norman Fenton and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-07 with Business & Economics categories.
Although many Bayesian Network (BN) applications are now in everyday use, BNs have not yet achieved mainstream penetration. Focusing on practical real-world problem solving and model building, as opposed to algorithms and theory, Risk Assessment and Decision Analysis with Bayesian Networks explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide powerful insights and better decision making. Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, and more Introduces all necessary mathematics, probability, and statistics as needed The book first establishes the basics of probability, risk, and building and using BN models, then goes into the detailed applications. The underlying BN algorithms appear in appendices rather than the main text since there is no need to understand them to build and use BN models. Keeping the body of the text free of intimidating mathematics, the book provides pragmatic advice about model building to ensure models are built efficiently. A dedicated website, www.BayesianRisk.com, contains executable versions of all of the models described, exercises and worked solutions for all chapters, PowerPoint slides, numerous other resources, and a free downloadable copy of the AgenaRisk software.
Analytical Methods For Risk Management
DOWNLOAD
Author : Paul R. Garvey
language : en
Publisher: CRC Press
Release Date : 2008-10-20
Analytical Methods For Risk Management written by Paul R. Garvey and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-20 with Business & Economics categories.
A Text on the Foundation Processes, Analytical Principles, and Implementation Practices of Engineering Risk Management Drawing from the author’s many years of hands-on experience in the field, Analytical Methods for Risk Management: A Systems Engineering Perspectivepresents the foundation processes and analytical practices for identifying, analyzing, measuring, and managing risk in traditional systems, systems-of-systems, and enterprise systems. Balances Risk and Decision Theory with Case Studies and Exercises After an introduction to engineering risk management, the book covers the fundamental axioms and properties of probability as well as key aspects of decision analysis, such as preference theory and risk/utility functions. It concludes with a series of essays on major analytical topics, including how to identify, write, and represent risks; prioritize risks in terms of their potential impacts on a systems project; and monitor progress when mitigating a risk’s potential adverse effects. The author also examines technical performance measures and how they can combine into an index to track an engineering system’s overall performance risk. In addition, he discusses risk management in the context of engineering complex, large-scale enterprise systems. Applies Various Methods to Risk Engineering and Analysis Problems This practical guide enables an understanding of which processes and analytical techniques are valid and how they are best applied to specific systems engineering environments. After reading this book, you will be on your way to managing risk on both traditional and advanced engineering systems.
Credit Risk Analytics
DOWNLOAD
Author : Bart Baesens
language : en
Publisher: John Wiley & Sons
Release Date : 2016-10-03
Credit Risk Analytics written by Bart Baesens 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 2016-10-03 with Business & Economics categories.
The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics. SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models. Understand the general concepts of credit risk management Validate and stress-test existing models Access working examples based on both real and simulated data Learn useful code for implementing and validating models in SAS Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process.
Risk Management In Engineering And Construction
DOWNLOAD
Author : Stephen Ogunlana
language : en
Publisher: Routledge
Release Date : 2019-09-09
Risk Management In Engineering And Construction written by Stephen Ogunlana and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-09 with Technology & Engineering categories.
Today’s businesses are driven by customer ‘pull’ and technological ‘push’. To remain competitive in this dynamic business world, engineering and construction organizations are constantly innovating with new technology tools and techniques to improve process performance in their projects. Their management challenge is to save time, reduce cost and increase quality and operational efficiency. Risk management has recently evolved as an effective method of managing both projects and operations. Risk is inherent in any project, as managers need to plan projects with minimal knowledge and information, but its management helps managers to become proactive rather than reactive. Hence, it not only increases the chance of project achievement, but also helps ensure better performance throughout its operations phase. Various qualitative and quantitative tools are researched extensively by academics and routinely deployed by practitioners for managing risk. These have tremendous potential for wider applications. Yet the current literature on both the theory and practice of risk management is widely scattered. Most of the books emphasize risk management theory but lack practical demonstrations and give little guidance on the application of those theories. This book showcases a number of effective applications of risk management tools and techniques across product and service life in a way useful for practitioners, graduate students and researchers. It also provides an in-depth understanding of the principles of risk management in engineering and construction.