Bayesian Risk Management

A Guide to Model Risk and Sequential Learning in Financial Markets

DOWNLOAD NOW »

Author: Matt Sekerke

Publisher: John Wiley & Sons

ISBN: 1118708601

Category: Business & Economics

Page: 240

View: 5701

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

DOWNLOAD NOW »

Author: David Ardia

Publisher: Springer Science & Business Media

ISBN: 9783540786573

Category: Business & Economics

Page: 206

View: 9094

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

DOWNLOAD NOW »

Author: Norman Fenton,Martin Neil

Publisher: CRC Press

ISBN: 1351978969

Category: Mathematics

Page: 704

View: 5392

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 Management

With Applications from the Offshore Petroleum Industry

DOWNLOAD NOW »

Author: Terje Aven,Jan-Erik Vinnem

Publisher: Springer Science & Business Media

ISBN: 1846286530

Category: Technology & Engineering

Page: 200

View: 719

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.

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

Focused on Computing and Engineering Management

DOWNLOAD NOW »

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

Publisher: Springer

ISBN: 364255122X

Category: Business & Economics

Page: 798

View: 3258

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.

Bayesian Methods in Finance

DOWNLOAD NOW »

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: 5654

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.

Risk Assessment and Decision Making in Business and Industry

A Practical Guide

DOWNLOAD NOW »

Author: Glenn Koller

Publisher: CRC Press

ISBN: 9780849302688

Category: Mathematics

Page: 256

View: 9260

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.

Environmental and Health Risk Assessment and Management

Principles and Practices

DOWNLOAD NOW »

Author: Paolo Ricci

Publisher: Springer Science & Business Media

ISBN: 1402037767

Category: Medical

Page: 480

View: 3526

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.

Environmental Risk Assessment and Management from a Landscape Perspective

DOWNLOAD NOW »

Author: Lawrence A. Kapustka,Wayne G. Landis

Publisher: John Wiley & Sons

ISBN: 9780470593011

Category: Technology & Engineering

Page: 416

View: 3761

An important guide to assessing and managing the environment from a landscape perspective Ecological relationships are nested within the landscape. Identifying the relevant spatial and temporal scales is critical for an effective understanding of ecological functions that human societies depend upon. Moreover, human encroachment into natural areas, or changes in climate, can alter spatial relationships, which in turn can negatively affect vital plant and wildlife patterns—and weaken economic structures needed to sustain human societies. This book is the first to combine multiple disciplines into one cohesive strategy to study these crucial connections, and looks toward building a social paradigm that embraces the dynamics of ecological systems. This book: Integrates landscape ecology, environmental risk assessment, valuation of ecological goods and services, and environmental management decision processes into one single source Includes chapters on quantitative measures, Bayesian modeling,¿economic analysis, and sustainable landscapes Covers marine, forest, agricultural, and pharmaceutical risk assessment Has a chapter on predicting climate change risk to ecosystems Has a companion ftp site with color graphics, animations, and risk assessment tools With material that is accessible across all knowledge levels, Environmental Risk Assessment and Management from a Landscape Perspective moves beyond looking solely at chemical contaminants to diagnose environmental threats, and aims to accomplish practical risk assessment in a manner that supports long-term sustainable management.

Safety, Reliability and Risk Analysis

Theory, Methods and Applications (4 Volumes + CD-ROM)

DOWNLOAD NOW »

Author: Sebastián Martorell,Carlos Guedes Soares,Julie Barnett

Publisher: CRC Press

ISBN: 1482266482

Category: Technology & Engineering

Page: 3510

View: 8589

Safety, Reliability and Risk Analysis. Theory, Methods and Applications contains the papers presented at the joint ESREL (European Safety and Reliability) and SRA-Europe (Society for Risk Analysis Europe) Conference (Valencia, Spain, 22-25 September 2008). The book covers a wide range of topics, including: Accident and Incident Investigation; Crisis and Emergency Management; Decision Support Systems and Software Tools for Safety and Reliability; Dynamic Reliability; Fault Identification and Diagnostics; Human Factors; Integrated Risk Management and Risk-Informed Decision-making; Legislative dimensions of risk management; Maintenance Modelling and Optimisation; Monte Carlo Methods in System Safety and Reliability; Occupational Safety; Organizational Learning; Reliability and Safety Data; Collection and Analysis; Risk and Evidence Based Policy Making; Risk and Hazard Analysis; Risk Control in Complex Environments; Risk Perception and Communication; Safety Culture; Safety Management Systems; Software Reliability; Stakeholder and public involvement in risk governance; Structural Reliability and Design Codes; System Reliability Analysis; Uncertainty and Sensitivity Analysis. Safety, Reliability and Risk Analysis. Theory, Methods and Applications will be of interest for academics and professionals working in a wide range of industrial and governmental sectors, including Aeronautics and Aerospace, Civil Engineering, Electrical and Electronic Engineering, Information Technology and Telecommunications, Insurance and Finance, Manufacturing, Mechanical Engineering, Nuclear Engineering, Policy Making and Public Planning.

Modelling Operational Risk Using Bayesian Inference

DOWNLOAD NOW »

Author: Pavel V. Shevchenko

Publisher: Springer Science & Business Media

ISBN: 9783642159237

Category: Business & Economics

Page: 302

View: 7920

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.

Handbook of Integrated Risk Management in Global Supply Chains

DOWNLOAD NOW »

Author: Panos Kouvelis,Lingxiu Dong,Onur Boyabatli,Rong Li

Publisher: John Wiley & Sons

ISBN: 1118115791

Category: Business & Economics

Page: 624

View: 802

A comprehensive, one-stop reference for cutting-edge research in integrated risk management, modern applications, and best practices In the field of business, the ever-growing dependency on global supply chains has created new challenges that traditional risk management must be equipped to handle. Handbook of Integrated Risk Management in Global Supply Chains uses a multi-disciplinary approach to present an effective way to manage complex, diverse, and interconnected global supply chain risks. Contributions from leading academics and researchers provide an action-based framework that captures real issues, implementation challenges, and concepts emerging from industry studies.The handbook is divided into five parts: Foundations and Overview introduces risk management and discusses the impact of supply chain disruptions on corporate performance Integrated Risk Management: Operations and Finance Interface explores the joint use of operational and financial hedging of commodity price uncertainties Supply Chain Finance discusses financing alternatives and the role of financial services in procurement contracts; inventory management and capital structure; and bank financing of inventories Operational Risk Management Strategies outlines supply risks and challenges in decentralized supply chains, such as competition and misalignment of incentives between buyers and suppliers Industrial Applications presents examples and case studies that showcase the discussed methodologies Each topic's presentation includes an introduction, key theories, formulas, and applications. Discussions conclude with a summary of the main concepts, a real-world example, and professional insights into common challenges and best practices. Handbook of Integrated Risk Management in Global Supply Chains is an essential reference for academics and practitioners in the areas of supply chain management, global logistics, management science, and industrial engineering who gather, analyze, and draw results from data. The handbook is also a suitable supplement for operations research, risk management, and financial engineering courses at the upper-undergraduate and graduate levels.

Coherent Stress Testing

A Bayesian Approach to the Analysis of Financial Stress

DOWNLOAD NOW »

Author: Riccardo Rebonato

Publisher: John Wiley & Sons

ISBN: 0470971487

Category: Business & Economics

Page: 238

View: 1630

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.

Introduction to Bayesian Estimation and Copula Models of Dependence

DOWNLOAD NOW »

Author: Arkady Shemyakin,Alexander Kniazev

Publisher: John Wiley & Sons

ISBN: 1118959019

Category: Mathematics

Page: 352

View: 624

Presents an introduction to Bayesian statistics, presents an emphasis on Bayesian methods (prior and posterior), Bayes estimation, prediction, MCMC,Bayesian regression, and Bayesian analysis of statistical modelsof dependence, and features a focus on copulas for risk management Introduction to Bayesian Estimation and Copula Models of Dependence emphasizes the applications of Bayesian analysis to copula modeling and equips readers with the tools needed to implement the procedures of Bayesian estimation in copula models of dependence. This book is structured in two parts: the first four chapters serve as a general introduction to Bayesian statistics with a clear emphasis on parametric estimation and the following four chapters stress statistical models of dependence with a focus of copulas. A review of the main concepts is discussed along with the basics of Bayesian statistics including prior information and experimental data, prior and posterior distributions, with an emphasis on Bayesian parametric estimation. The basic mathematical background of both Markov chains and Monte Carlo integration and simulation is also provided. The authors discuss statistical models of dependence with a focus on copulas and present a brief survey of pre-copula dependence models. The main definitions and notations of copula models are summarized followed by discussions of real-world cases that address particular risk management problems. In addition, this book includes: • Practical examples of copulas in use including within the Basel Accord II documents that regulate the world banking system as well as examples of Bayesian methods within current FDA recommendations • Step-by-step procedures of multivariate data analysis and copula modeling, allowing readers to gain insight for their own applied research and studies • Separate reference lists within each chapter and end-of-the-chapter exercises within Chapters 2 through 8 • A companion website containing appendices: data files and demo files in Microsoft® Office Excel®, basic code in R, and selected exercise solutions Introduction to Bayesian Estimation and Copula Models of Dependence is a reference and resource for statisticians who need to learn formal Bayesian analysis as well as professionals within analytical and risk management departments of banks and insurance companies who are involved in quantitative analysis and forecasting. This book can also be used as a textbook for upper-undergraduate and graduate-level courses in Bayesian statistics and analysis. ARKADY SHEMYAKIN, PhD, is Professor in the Department of Mathematics and Director of the Statistics Program at the University of St. Thomas. A member of the American Statistical Association and the International Society for Bayesian Analysis, Dr. Shemyakin's research interests include informationtheory, Bayesian methods of parametric estimation, and copula models in actuarial mathematics, finance, and engineering. ALEXANDER KNIAZEV, PhD, is Associate Professor and Head of the Department of Mathematics at Astrakhan State University in Russia. Dr. Kniazev's research interests include representation theory of Lie algebras and finite groups, mathematical statistics, econometrics, and financial mathematics.

Decision Science and Social Risk Management

A Comparative Evaluation of Cost-Benefit Analysis, Decision Analysis, and Other Formal Decision-Aiding Approaches

DOWNLOAD NOW »

Author: M.W Merkhofer

Publisher: Springer Science & Business Media

ISBN: 9400946988

Category: Technology & Engineering

Page: 330

View: 7330

Economists, decision analysts, management scientists, and others have long argued that government should take a more scientific approach to decision making. Pointing to various theories for prescribing and rational izing choices, they have maintained that social goals could be achieved more effectively and at lower costs if government decisions were routinely subjected to analysis. Now, government policy makers are putting decision science to the test. Recent government actions encourage and in some cases require government decisions to be evaluated using formally defined principles 01' rationality. Will decision science pass tbis test? The answer depends on whether analysts can quickly and successfully translate their theories into practical approaches and whether these approaches promote the solution of the complex, highly uncertain, and politically sensitive problems that are of greatest concern to government decision makers. The future of decision science, perhaps even the nation's well-being, depends on the outcome. A major difficulty for the analysts who are being called upon by government to apply decision-aiding approaches is that decision science has not yet evolved a universally accepted methodology for analyzing social decisions involving risk. Numerous approaches have been proposed, including variations of cost-benefit analysis, decision analysis, and applied social welfare theory. Each of these, however, has its limitations and deficiencies and none has a proven track record for application to govern ment decisions involving risk. Cost-benefit approaches have been exten sively applied by the government, but most applications have been for decisions that were largely risk-free.

Flood Risk Management: Research and Practice

Extended Abstracts Volume (332 pages) + full paper CD-ROM (1772 pages)

DOWNLOAD NOW »

Author: Paul Samuels,Stephen Huntington,William Allsop,Jackie Harrop

Publisher: CRC Press

ISBN: 9780203883020

Category: Science

Page: 1772

View: 5765

Floods cause distress and damage wherever and whenever they happen. Flooding from rivers, estuaries and the sea threatens many millions of people worldwide and economic and insurance losses from flooding have increased significantly since 1990. Across the European Union, flood management policy is changing in response to the EU Directive on the assessment and management of flood risks, which requires a move from flood protection and defence to comprehensive flood risk management. Flood Risk Management: Research and Practice includes about 200 contributions from the international conference FLOODrisk 2008 (Oxford, UK, 30 September – 2 October 2008). FLOODrisk 2008 was an initiative of the FLOODsite research project on Integrated Flood Risk Analysis and Management Methodologies. FLOODsite was a major “Integrated Project” in the European Commission Sixth Framework Programme; contract number GOCE-CT-2004-505420. The conference provided a forum for leading researchers, flood risk managers, policy makers and practitioners from government, commercial and research organisations to gain an overview of advances in this important subject. Flood risk management practice crosses several professions and disciplines and these are represented in the breadth of the scope of the conference and these proceedings. The conference covered all aspects of flood risk: the causes of floods, their impacts on people, property and the environment, and portfolios of risk management measuresm, while the principal themes included: climate change, estimation of extremes, flash floods, flood forecasting and warning, inundation modelling, systems analysis, uncertainty, international programmes, flood defence infrastructure and assets, environmental impacts, human and social impacts, vulnerability and resilience, risk sharing, equity and social justice, and, civil contingency planning and emergency management. Flood Risk Management: Research and Practice will be of interest to an international readership, ranging from authorities, consultants and engineers involved in flood management; researchers, post graduate lecturers and students, to policy makers, particularly at national level.

Portfolio Risk Analysis

DOWNLOAD NOW »

Author: Gregory Connor,Lisa R. Goldberg,Robert A. Korajczyk

Publisher: Princeton University Press

ISBN: 9781400835294

Category: Business & Economics

Page: 400

View: 6487

Portfolio risk forecasting has been and continues to be an active research field for both academics and practitioners. Almost all institutional investment management firms use quantitative models for their portfolio forecasting, and researchers have explored models' econometric foundations, relative performance, and implications for capital market behavior and asset pricing equilibrium. Portfolio Risk Analysis provides an insightful and thorough overview of financial risk modeling, with an emphasis on practical applications, empirical reality, and historical perspective. Beginning with mean-variance analysis and the capital asset pricing model, the authors give a comprehensive and detailed account of factor models, which are the key to successful risk analysis in every economic climate. Topics range from the relative merits of fundamental, statistical, and macroeconomic models, to GARCH and other time series models, to the properties of the VIX volatility index. The book covers both mainstream and alternative asset classes, and includes in-depth treatments of model integration and evaluation. Credit and liquidity risk and the uncertainty of extreme events are examined in an intuitive and rigorous way. An extensive literature review accompanies each topic. The authors complement basic modeling techniques with references to applications, empirical studies, and advanced mathematical texts. This book is essential for financial practitioners, researchers, scholars, and students who want to understand the nature of financial markets or work toward improving them.