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Coherent Stress Testing

Author: Riccardo Rebonato
Publisher: John Wiley & Sons
ISBN: 0470971487
Size: 68.10 MB
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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.

Coherent Stress Testing

Author: Riccardo Rebonato
Publisher: Wiley
ISBN: 0470667362
Size: 10.47 MB
Format: PDF, ePub
View: 729
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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.

Portfolio Management Under Stress

Author: Riccardo Rebonato
Publisher: Cambridge University Press
ISBN: 1107048117
Size: 58.21 MB
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A rigorous presentation of a novel methodology for asset allocation in financial portfolios under conditions of market distress.

Elements Of Financial Risk Management

Author: Peter F. Christoffersen
Publisher: Academic Press
ISBN: 0123744482
Size: 27.25 MB
Format: PDF, ePub, Docs
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The Second Edition of this best-selling book expands its advanced approach to financial risk models by covering market, credit, and integrated risk. With new data that cover the recent financial crisis, it combines Excel-based empirical exercises at the end of each chapter with online exercises so readers can use their own data. Its unified GARCH modeling approach, empirically sophisticated and relevant yet easy to implement, sets this book apart from others. Four new chapters and updated end-of-chapter questions and exercises, as well as Excel-solutions manual and PowerPoint slides, support its step-by-step approach to choosing tools and solving problems. Examines market risk, credit risk, and operational risk Provides exceptional coverage of GARCH models Features online Excel-based empirical exercises

Bayesian Risk Management

Author: Matt Sekerke
Publisher: John Wiley & Sons
ISBN: 1118747453
Size: 49.16 MB
Format: PDF, Mobi
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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 Decision Making Using Computational Intelligence

Author: Michael Doumpos
Publisher: Springer Science & Business Media
ISBN: 1461437733
Size: 23.38 MB
Format: PDF, ePub
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The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides an arsenal of particularly useful techniques. These techniques include new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems. Computational intelligence has also evolved rapidly over the past few years and it is now one of the most active fields in operations research and computer science. This volume presents the recent advances of the use of computation intelligence in financial decision making. The book covers all the major areas of computational intelligence and a wide range of problems in finance, such as portfolio optimization, credit risk analysis, asset valuation, financial forecasting, and trading.

Risk Management And Financial Institutions

Author: John C. Hull
Publisher: John Wiley & Sons
ISBN: 1118955951
Size: 75.93 MB
Format: PDF, Kindle
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The most complete, up to date guide to risk management in finance Risk Management and Financial Institutions explains all aspects of financial risk and financial institution regulation, helping readers better understand the financial markets and potential dangers. This new fourth edition has been updated to reflect the major developments in the industry, including the finalization of Basel III, the fundamental review of the trading book, SEFs, CCPs, and the new rules affecting derivatives markets. There are new chapters on enterprise risk management and scenario analysis. Readers learn the different types of risk, how and where they appear in different types of institutions, and how the regulatory structure of each institution affects risk management practices. Comprehensive ancillary materials include software, practice questions, and all necessary teaching supplements, facilitating more complete understanding and providing an ultimate learning resource. All financial professionals need a thorough background in risk and the interlacing connections between financial institutions to better understand the market, defend against systemic dangers, and perform their jobs. This book provides a complete picture of the risk management industry and practice, with the most up to date information. Understand how risk affects different types of financial institutions Learn the different types of risk and how they are managed Study the most current regulatory issues that deal with risk Risk management is paramount with the dangers inherent in the financial system, and a deep understanding is essential for anyone working in the finance industry; today, risk management is part of everyone's job. For complete information and comprehensive coverage of the latest industry issues and practices, Risk Management and Financial Institutions is an informative, authoritative guide.

Plight Of The Fortune Tellers

Author: Riccardo Rebonato
Publisher: Princeton University Press
ISBN: 9781400836390
Size: 16.44 MB
Format: PDF, Docs
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Today's top financial professionals have come to rely on ever-more sophisticated mathematics in their attempts to come to grips with financial risk. But this excessive reliance on quantitative precision is misleading--and puts everyone at risk. In Plight of the Fortune Tellers, Riccardo Rebonato forcefully argues that we must restore genuine decision making to our financial planning. Presenting a financial model that uses probability, experimental psychology, and decision theory, Rebonato challenges us to rethink the standard wisdom about risk management. He offers a radical yet surprisingly commonsense solution: managing risk comes down to real people making decisions under uncertainty. Plight of the Fortune Tellers is a must-read for anyone concerned about how today's financial markets are run. In a new preface, Rebonato explains how the ideas presented in this book fit into the context of the global financial crisis that followed its original publication. He argues that risk managers are still stuck in a probabilistic rut, and need to engage with the structural causes of real events.

Mathematics And Statistics For Financial Risk Management

Author: Michael B. Miller
Publisher: John Wiley & Sons
ISBN: 1118757645
Size: 42.55 MB
Format: PDF, Kindle
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Mathematics and Statistics for Financial Risk Management is a practical guide to modern financial risk management for both practitioners and academics. Now in its second edition with more topics, more sample problems and more real world examples, this popular guide to financial risk management introduces readers to practical quantitative techniques for analyzing and managing financial risk. In a concise and easy-to-read style, each chapter introduces a different topic in mathematics or statistics. As different techniques are introduced, sample problems and application sections demonstrate how these techniques can be applied to actual risk management problems. Exercises at the end of each chapter and the accompanying solutions at the end of the book allow readers to practice the techniques they are learning and monitor their progress. A companion Web site includes interactive Excel spreadsheet examples and templates. Mathematics and Statistics for Financial Risk Management is an indispensable reference for today’s financial risk professional.