Probabilistic Risk Analysis

Probabilistic Risk Analysis PDF Author: Tim Bedford
Publisher: Cambridge University Press
ISBN: 9780521773201
Category : Mathematics
Languages : en
Pages : 228

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Book Description
Probabilistic risk analysis aims to quantify the risk caused by high technology installations. Increasingly, such analyses are being applied to a wider class of systems in which problems such as lack of data, complexity of the systems, uncertainty about consequences, make a classical statistical analysis difficult or impossible. The authors discuss the fundamental notion of uncertainty, its relationship with probability, and the limits to the quantification of uncertainty. Drawing on extensive experience in the theory and applications of risk analysis, the authors focus on the conceptual and mathematical foundations underlying the quantification, interpretation and management of risk. They cover standard topics as well as important new subjects such as the use of expert judgement and uncertainty propagation. The relationship of risk analysis with decision making is highlighted in chapters on influence diagrams and decision theory. Finally, the difficulties of choosing metrics to quantify risk, and current regulatory frameworks are discussed.

Probabilistic Risk Analysis

Probabilistic Risk Analysis PDF Author: Tim Bedford
Publisher: Cambridge University Press
ISBN: 9780521773201
Category : Mathematics
Languages : en
Pages : 228

Get Book Here

Book Description
Probabilistic risk analysis aims to quantify the risk caused by high technology installations. Increasingly, such analyses are being applied to a wider class of systems in which problems such as lack of data, complexity of the systems, uncertainty about consequences, make a classical statistical analysis difficult or impossible. The authors discuss the fundamental notion of uncertainty, its relationship with probability, and the limits to the quantification of uncertainty. Drawing on extensive experience in the theory and applications of risk analysis, the authors focus on the conceptual and mathematical foundations underlying the quantification, interpretation and management of risk. They cover standard topics as well as important new subjects such as the use of expert judgement and uncertainty propagation. The relationship of risk analysis with decision making is highlighted in chapters on influence diagrams and decision theory. Finally, the difficulties of choosing metrics to quantify risk, and current regulatory frameworks are discussed.

Guidelines for Managing Geotechnical Risks in Design-build Projects

Guidelines for Managing Geotechnical Risks in Design-build Projects PDF Author: Douglas D. Gransberg
Publisher:
ISBN: 9780309390606
Category : Engineering geology
Languages : en
Pages : 53

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Book Description


Market Risk Analysis, Boxset

Market Risk Analysis, Boxset PDF Author: Carol Alexander
Publisher: John Wiley & Sons
ISBN: 0470997990
Category : Business & Economics
Languages : en
Pages : 1691

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Book Description
Market Risk Analysis is the most comprehensive, rigorous and detailed resource available on market risk analysis. Written as a series of four interlinked volumes each title is self-contained, although numerous cross-references to other volumes enable readers to obtain further background knowledge and information about financial applications. Volume I: Quantitative Methods in Finance covers the essential mathematical and financial background for subsequent volumes. Although many readers will already be familiar with this material, few competing texts contain such a complete and pedagogical exposition of all the basic quantitative concepts required for market risk analysis. There are six comprehensive chapters covering all the calculus, linear algebra, probability and statistics, numerical methods and portfolio mathematics that are necessary for market risk analysis. This is an ideal background text for a Masters course in finance. Volume II: Practical Financial Econometrics provides a detailed understanding of financial econometrics, with applications to asset pricing and fund management as well as to market risk analysis. It covers equity factor models, including a detailed analysis of the Barra model and tracking error, principal component analysis, volatility and correlation, GARCH, cointegration, copulas, Markov switching, quantile regression, discrete choice models, non-linear regression, forecasting and model evaluation. Volume III: Pricing, Hedging and Trading Financial Instruments has five very long chapters on the pricing, hedging and trading of bonds and swaps, futures and forwards, options and volatility as well detailed descriptions of mapping portfolios of these financial instruments to their risk factors. There are numerous examples, all coded in interactive Excel spreadsheets, including many pricing formulae for exotic options but excluding the calibration of stochastic volatility models, for which Matlab code is provided. The chapters on options and volatility together constitute 50% of the book, the slightly longer chapter on volatility concentrating on the dynamic properties the two volatility surfaces the implied and the local volatility surfaces that accompany an option pricing model, with particular reference to hedging. Volume IV: Value at Risk Models builds on the three previous volumes to provide by far the most comprehensive and detailed treatment of market VaR models that is currently available in any textbook. The exposition starts at an elementary level but, as in all the other volumes, the pedagogical approach accompanied by numerous interactive Excel spreadsheets allows readers to experience the application of parametric linear, historical simulation and Monte Carlo VaR models to increasingly complex portfolios. Starting with simple positions, after a few chapters we apply value-at-risk models to interest rate sensitive portfolios, large international securities portfolios, commodity futures, path dependent options and much else. This rigorous treatment includes many new results and applications to regulatory and economic capital allocation, measurement of VaR model risk and stress testing.

Science and Decisions

Science and Decisions PDF Author: National Research Council
Publisher: National Academies Press
ISBN: 0309120462
Category : Political Science
Languages : en
Pages : 422

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Book Description
Risk assessment has become a dominant public policy tool for making choices, based on limited resources, to protect public health and the environment. It has been instrumental to the mission of the U.S. Environmental Protection Agency (EPA) as well as other federal agencies in evaluating public health concerns, informing regulatory and technological decisions, prioritizing research needs and funding, and in developing approaches for cost-benefit analysis. However, risk assessment is at a crossroads. Despite advances in the field, risk assessment faces a number of significant challenges including lengthy delays in making complex decisions; lack of data leading to significant uncertainty in risk assessments; and many chemicals in the marketplace that have not been evaluated and emerging agents requiring assessment. Science and Decisions makes practical scientific and technical recommendations to address these challenges. This book is a complement to the widely used 1983 National Academies book, Risk Assessment in the Federal Government (also known as the Red Book). The earlier book established a framework for the concepts and conduct of risk assessment that has been adopted by numerous expert committees, regulatory agencies, and public health institutions. The new book embeds these concepts within a broader framework for risk-based decision-making. Together, these are essential references for those working in the regulatory and public health fields.

Risk Analysis

Risk Analysis PDF Author: John J. Cohrssen
Publisher: DIANE Publishing
ISBN: 0788149989
Category :
Languages : en
Pages : 420

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Book Description
Designed for consumers of risk information, this book offers a balance between the technical and nontechnical literature. The discipline of risk analysis has developed into an organized body of knowledge and methods only within the past 20 years. The passage of federal laws to protect public health and the environment has generated rapid growth in risk analysis in numerous fields. Statements of risk need to be understood to be useful to the public and environmental managers. This guidebook provides a tool for understanding risk analysis. Chapters: overview of risk analysis; hazard identification; risk assessment; and risk communication.

Risk Analysis

Risk Analysis PDF Author: David Vose
Publisher: John Wiley & Sons
ISBN: 0470512849
Category : Business & Economics
Languages : en
Pages : 754

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Book Description
Risk Analysis concerns itself with the quantification of risk, the modeling of identified risks and how to make decisions from those models. Quantitative risk analysis (QRA) using Monte Carlo simulation offers a powerful and precise method for dealing with the uncertainty and variability of a problem. By providing the building blocks the author guides the reader through the necessary steps to produce an accurate risk analysis model and offers general and specific techniques to cope with most modeling problems. A wide range of solved problems is used to illustrate these techniques and how they can be used together to solve otherwise complex problems.

Accident Precursor Analysis and Management

Accident Precursor Analysis and Management PDF Author: National Academy of Engineering
Publisher: National Academies Press
ISBN: 0309092167
Category : Technology & Engineering
Languages : en
Pages : 221

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Book Description
In the aftermath of catastrophes, it is common to find prior indicators, missed signals, and dismissed alerts that, had they been recognized and appropriately managed before the event, could have resulted in the undesired event being averted. These indicators are typically called "precursors." Accident Precursor Analysis and Management: Reducing Technological Risk Through Diligence documents various industrial and academic approaches to detecting, analyzing, and benefiting from accident precursors and examines public-sector and private-sector roles in the collection and use of precursor information. The book includes the analysis, findings and recommendations of the authoring NAE committee as well as eleven individually authored background papers on the opportunity of precursor analysis and management, risk assessment, risk management, and linking risk assessment and management.

International Convergence of Capital Measurement and Capital Standards

International Convergence of Capital Measurement and Capital Standards PDF Author:
Publisher: Lulu.com
ISBN: 9291316695
Category : Bank capital
Languages : en
Pages : 294

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Book Description


Advanced Credit Risk Analysis and Management

Advanced Credit Risk Analysis and Management PDF Author: Ciby Joseph
Publisher: John Wiley & Sons
ISBN: 111860489X
Category : Business & Economics
Languages : en
Pages : 454

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Book Description
Credit is essential in the modern world and creates wealth, provided it is used wisely. The Global Credit Crisis during 2008/2009 has shown that sound understanding of underlying credit risk is crucial. If credit freezes, almost every activity in the economy is affected. The best way to utilize credit and get results is to understand credit risk. Advanced Credit Risk Analysis and Management helps the reader to understand the various nuances of credit risk. It discusses various techniques to measure, analyze and manage credit risk for both lenders and borrowers. The book begins by defining what credit is and its advantages and disadvantages, the causes of credit risk, a brief historical overview of credit risk analysis and the strategic importance of credit risk in institutions that rely on claims or debtors. The book then details various techniques to study the entity level credit risks, including portfolio level credit risks. Authored by a credit expert with two decades of experience in corporate finance and corporate credit risk, the book discusses the macroeconomic, industry and financial analysis for the study of credit risk. It covers credit risk grading and explains concepts including PD, EAD and LGD. It also highlights the distinction with equity risks and touches on credit risk pricing and the importance of credit risk in Basel Accords I, II and III. The two most common credit risks, project finance credit risk and working capital credit risk, are covered in detail with illustrations. The role of diversification and credit derivatives in credit portfolio management is considered. It also reflects on how the credit crisis develops in an economy by referring to the bubble formation. The book links with the 2008/2009 credit crisis and carries out an interesting discussion on how the credit crisis may have been avoided by following the fundamentals or principles of credit risk analysis and management. The book is essential for both lenders and borrowers. Containing case studies adapted from real life examples and exercises, this important text is practical, topical and challenging. It is useful for a wide spectrum of academics and practitioners in credit risk and anyone interested in commercial and corporate credit and related products.

Machine Learning and Data Science in the Oil and Gas Industry

Machine Learning and Data Science in the Oil and Gas Industry PDF Author: Patrick Bangert
Publisher: Gulf Professional Publishing
ISBN: 0128209143
Category : Science
Languages : en
Pages : 290

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Book Description
Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value. - Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful - Gain practical understanding of machine learning used in oil and gas operations through contributed case studies - Learn change management skills that will help gain confidence in pursuing the technology - Understand the workflow of a full-scale project and where machine learning benefits (and where it does not)