Bayesian Risk Management

A Guide to Model Risk and Sequential Learning in Financial Markets

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Author: Matt Sekerke

Publisher: John Wiley & Sons

ISBN: 1118708601

Category: Business & Economics

Page: 240

View: 783

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.

Financial Risk Management with Bayesian Estimation of GARCH Models

Theory and Applications

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Author: David Ardia

Publisher: Springer Science & Business Media

ISBN: 9783540786573

Category: Business & Economics

Page: 206

View: 1077

This book presents in detail methodologies for the Bayesian estimation of sing- regime and regime-switching GARCH models. These models are widespread and essential tools in n ancial econometrics and have, until recently, mainly been estimated using the classical Maximum Likelihood technique. As this study aims to demonstrate, the Bayesian approach o ers an attractive alternative which enables small sample results, robust estimation, model discrimination and probabilistic statements on nonlinear functions of the model parameters. The author is indebted to numerous individuals for help in the preparation of this study. Primarily, I owe a great debt to Prof. Dr. Philippe J. Deschamps who inspired me to study Bayesian econometrics, suggested the subject, guided me under his supervision and encouraged my research. I would also like to thank Prof. Dr. Martin Wallmeier and my colleagues of the Department of Quantitative Economics, in particular Michael Beer, Roberto Cerratti and Gilles Kaltenrieder, for their useful comments and discussions. I am very indebted to my friends Carlos Ord as Criado, Julien A. Straubhaar, J er ^ ome Ph. A. Taillard and Mathieu Vuilleumier, for their support in the elds of economics, mathematics and statistics. Thanks also to my friend Kevin Barnes who helped with my English in this work. Finally, I am greatly indebted to my parents and grandparents for their support and encouragement while I was struggling with the writing of this thesis.

Risk Assessment and Decision Analysis with Bayesian Networks, Second Edition

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Author: Norman Fenton,Martin Neil

Publisher: CRC Press

ISBN: 1351978969

Category: Mathematics

Page: 704

View: 1605

Since the first edition of this book published, Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams, learning from data, value of information, cybersecurity, debunking bad statistics, and much more. Focusing on practical real-world problem-solving and model building, as opposed to algorithms and theory, it explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide more powerful insights and better decision making than is possible from purely data-driven solutions. Features 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, forensics, cybersecurity and more Introduces all necessary mathematics, probability, and statistics as needed Establishes the basics of probability, risk, and building and using Bayesian network models, before going into the detailed applications A dedicated website contains exercises and worked solutions for all chapters along with numerous other resources. The AgenaRisk software contains a model library with executable versions of all of the models in the book. Lecture slides are freely available to accredited academic teachers adopting the book on their course.

Risk Assessment and Decision Analysis with Bayesian Networks

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Author: Norman Fenton,Martin Neil

Publisher: CRC Press

ISBN: 1439809119

Category: Business & Economics

Page: 524

View: 7169

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.

Risk Management

With Applications from the Offshore Petroleum Industry

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Author: Terje Aven,Jan-Erik Vinnem

Publisher: Springer Science & Business Media

ISBN: 1846286530

Category: Technology & Engineering

Page: 200

View: 9903

This book presents a risk management framework designed to achieve better decisions and more desirable outcomes. It presents an in-depth discussion of some fundamental principles of risk management related to the use of expected values, uncertainty handling, and risk acceptance criteria. Several examples from the offshore petroleum industry are included to illustrate the use of the framework, but it can also be applied in other areas.

Risk Assessment and Decision Making in Business and Industry

A Practical Guide

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Author: Glenn Koller

Publisher: CRC Press

ISBN: 9780849302688

Category: Mathematics

Page: 256

View: 5559

Risk Assessment and Decision Making in Business and Industry: A Practical Guide presents an accessible treatment of the procedures and technologies involved in designing and building risk-assessment processes and models. Areas examined include: brokerage-house portfolio management legal decision making construction oil/gas exploration environmental assessments engineering marketing government manufacturing The entire volume is presented as a narrative, keeping statistical jargon to a minimum and explaining all concepts, techniques, and processes in a straightforward manner. The author emphasizes that the technical aspects of a risk-assessment and decision-making effort are secondary to the cultural, organizational, and interpersonal facets of establishing a framework. "Practical" is the operative term throughout the text. Risk Assessment and Decision Making in Business and Industry: A Practical Guide enables readers who are not risk experts to effect an easy execution of the risk model building effort.

Bayesian Methods in Finance

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Author: Svetlozar T. Rachev,John S. J. Hsu,Biliana S. Bagasheva,Frank J. Fabozzi

Publisher: John Wiley & Sons

ISBN: 9780470249246

Category: Business & Economics

Page: 352

View: 2325

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.

Environmental and Health Risk Assessment and Management

Principles and Practices

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Author: Paolo Ricci

Publisher: Springer Science & Business Media

ISBN: 1402037767

Category: Medical

Page: 480

View: 3029

This book is about the legal, economical, and practical assessment and management of risky activities arising from routine, catastrophic environmental and occupational exposures to hazardous agents. It includes a discussion of aspects of US and European Union law concerning risky activities, and then develops the economic analyses that are relevant to implementing choices within a supply and demand framework. The book also discusses exposure-response and time-series models used in assessing air and water pollution, as well as probabilistic cancer models, including toxicological compartmental, pharmaco-kinetic models and epidemiological relative risks and odds ratios-based models. Statistical methods to measure agreement, correlation and discordance are also developed. The methods and criteria of decision-analysis, including several measures of value of information (VOI) conclude the expositions. This book is an excellent text for students studying risk assessment and management.

Proceedings of the Eighth International Conference on Management Science and Engineering Management

Focused on Computing and Engineering Management

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Author: Jiuping Xu,Virgílio António Cruz-Machado,Benjamin Lev,Stefan Nickel

Publisher: Springer

ISBN: 364255122X

Category: Business & Economics

Page: 798

View: 7005

This is the Proceedings of the Eighth International Conference on Management Science and Engineering Management (ICMSEM) held from July 25 to 27, 2014 at Universidade Nova de Lisboa, Lisbon, Portugal and organized by International Society of Management Science and Engineering Management (ISMSEM), Sichuan University (Chengdu, China) and Universidade Nova de Lisboa (Lisbon, Portugal). The goals of the conference are to foster international research collaborations in Management Science and Engineering Management as well as to provide a forum to present current findings. A total number of 138 papers from 14 countries are selected for the proceedings by the conference scientific committee through rigorous referee review. The selected papers in the second volume are focused on Computing and Engineering Management covering areas of Computing Methodology, Project Management, Industrial Engineering and Information Technology.