Quantitative Risk Management

Concepts, Techniques, and Tools

Author: Alexander J. McNeil,Rüdiger Frey,Paul Embrechts

Publisher: Princeton University Press

ISBN: 9780691122557

Category: Business & Economics

Page: 538

View: 5619

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The implementation of sound quantitative risk models is a vital concern for all financial institutions, and this trend has accelerated in recent years with regulatory processes such as Basel II. This book provides a comprehensive treatment of the theoretical concepts and modelling techniques of quantitative risk management and equips readers--whether financial risk analysts, actuaries, regulators, or students of quantitative finance--with practical tools to solve real-world problems. The authors cover methods for market, credit, and operational risk modelling; place standard industry approaches on a more formal footing; and describe recent developments that go beyond, and address main deficiencies of, current practice. The book's methodology draws on diverse quantitative disciplines, from mathematical finance through statistics and econometrics to actuarial mathematics. Main concepts discussed include loss distributions, risk measures, and risk aggregation and allocation principles. A main theme is the need to satisfactorily address extreme outcomes and the dependence of key risk drivers. The techniques required derive from multivariate statistical analysis, financial time series modelling, copulas, and extreme value theory. A more technical chapter addresses credit derivatives. Based on courses taught to masters students and professionals, this book is a unique and fundamental reference that is set to become a standard in the field.
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Quantitative Risk Management

Concepts, Techniques and Tools - Revised Edition

Author: Alexander J. McNeil,Rüdiger Frey,Paul Embrechts

Publisher: Princeton University Press

ISBN: 1400866286

Category: Business & Economics

Page: 720

View: 2190

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This book provides the most comprehensive treatment of the theoretical concepts and modelling techniques of quantitative risk management. Whether you are a financial risk analyst, actuary, regulator or student of quantitative finance, Quantitative Risk Management gives you the practical tools you need to solve real-world problems. Describing the latest advances in the field, Quantitative Risk Management covers the methods for market, credit and operational risk modelling. It places standard industry approaches on a more formal footing and explores key concepts such as loss distributions, risk measures and risk aggregation and allocation principles. The book's methodology draws on diverse quantitative disciplines, from mathematical finance and statistics to econometrics and actuarial mathematics. A primary theme throughout is the need to satisfactorily address extreme outcomes and the dependence of key risk drivers. Proven in the classroom, the book also covers advanced topics like credit derivatives. Fully revised and expanded to reflect developments in the field since the financial crisis Features shorter chapters to facilitate teaching and learning Provides enhanced coverage of Solvency II and insurance risk management and extended treatment of credit risk, including counterparty credit risk and CDO pricing Includes a new chapter on market risk and new material on risk measures and risk aggregation
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Quantitative Risk Management: Concepts, Techniques, and Tools

Concepts, Techniques, and Tools

Author: Alexander J. McNeil,Rüdiger Frey,Paul Embrechts

Publisher: Princeton University Press

ISBN: 9781400837571

Category: Business & Economics

Page: 544

View: 6141

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The implementation of sound quantitative risk models is a vital concern for all financial institutions, and this trend has accelerated in recent years with regulatory processes such as Basel II. This book provides a comprehensive treatment of the theoretical concepts and modelling techniques of quantitative risk management and equips readers--whether financial risk analysts, actuaries, regulators, or students of quantitative finance--with practical tools to solve real-world problems. The authors cover methods for market, credit, and operational risk modelling; place standard industry approaches on a more formal footing; and describe recent developments that go beyond, and address main deficiencies of, current practice. The book's methodology draws on diverse quantitative disciplines, from mathematical finance through statistics and econometrics to actuarial mathematics. Main concepts discussed include loss distributions, risk measures, and risk aggregation and allocation principles. A main theme is the need to satisfactorily address extreme outcomes and the dependence of key risk drivers. The techniques required derive from multivariate statistical analysis, financial time series modelling, copulas, and extreme value theory. A more technical chapter addresses credit derivatives. Based on courses taught to masters students and professionals, this book is a unique and fundamental reference that is set to become a standard in the field.
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Innovations in Quantitative Risk Management

TU München, September 2013

Author: Kathrin Glau,Matthias Scherer,Rudi Zagst

Publisher: Springer

ISBN: 331909114X

Category: Mathematics

Page: 438

View: 7296

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Quantitative models are omnipresent –but often controversially discussed– in todays risk management practice. New regulations, innovative financial products, and advances in valuation techniques provide a continuous flow of challenging problems for financial engineers and risk managers alike. Designing a sound stochastic model requires finding a careful balance between parsimonious model assumptions, mathematical viability, and interpretability of the output. Moreover, data requirements and the end-user training are to be considered as well. The KPMG Center of Excellence in Risk Management conference Risk Management Reloaded and this proceedings volume contribute to bridging the gap between academia –providing methodological advances– and practice –having a firm understanding of the economic conditions in which a given model is used. Discussed fields of application range from asset management, credit risk, and energy to risk management issues in insurance. Methodologically, dependence modeling, multiple-curve interest rate-models, and model risk are addressed. Finally, regulatory developments and possible limits of mathematical modeling are discussed.
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Mathematical Risk Analysis

Dependence, Risk Bounds, Optimal Allocations and Portfolios

Author: Ludger Rüschendorf

Publisher: Springer Science & Business Media

ISBN: 364233590X

Category: Mathematics

Page: 408

View: 7533

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The author's particular interest in the area of risk measures is to combine this theory with the analysis of dependence properties. The present volume gives an introduction of basic concepts and methods in mathematical risk analysis, in particular of those parts of risk theory that are of special relevance to finance and insurance. Describing the influence of dependence in multivariate stochastic models on risk vectors is the main focus of the text that presents main ideas and methods as well as their relevance to practical applications. The first part introduces basic probabilistic tools and methods of distributional analysis, and describes their use to the modeling of dependence and to the derivation of risk bounds in these models. In the second, part risk measures with a particular focus on those in the financial and insurance context are presented. The final parts are then devoted to applications relevant to optimal risk allocation, optimal portfolio problems as well as to the optimization of insurance contracts. Good knowledge of basic probability and statistics as well as of basic general mathematics is a prerequisite for comfortably reading and working with the present volume, which is intended for graduate students, practitioners and researchers and can serve as a reference resource for the main concepts and techniques.
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Pricing and Risk Management of Synthetic CDOs

Author: Anna Schlösser

Publisher: Springer Science & Business Media

ISBN: 9783642156090

Category: Business & Economics

Page: 268

View: 1064

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This book considers the one-factor copula model for credit portfolios that are used for pricing synthetic CDO structures as well as for risk management and measurement applications involving the generation of scenarios for the complete universe of risk factors and the inclusion of CDO structures in a portfolio context. For this objective, it is especially important to have a computationally fast model that can also be used in a scenario simulation framework. The well known Gaussian copula model is extended in various ways in order to improve its drawbacks of correlation smile and time inconsistency. Also the application of the large homogeneous cell assumption, that allows to differentiate between rating classes, makes the model convenient and powerful for practical applications. The Crash-NIG extension introduces an important regime-switching feature allowing the possibility of a market crash that is characterized by a high-correlation regime.
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Heavy-Tail Phenomena

Probabilistic and Statistical Modeling

Author: Sidney I. Resnick

Publisher: Springer Science & Business Media

ISBN: 0387242724

Category: Business & Economics

Page: 404

View: 3920

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This comprehensive text gives an interesting and useful blend of the mathematical, probabilistic and statistical tools used in heavy-tail analysis. Heavy tails are characteristic of phenomena where there is a significant probability of a single huge value impacting system behavior. Record-breaking insurance losses, financial returns, sizes of files stored on a server and transmission rates of files are all examples of heavy-tailed phenomena. Prerequisites for the reader include a prior course in stochastic processes and probability, some statistical background, some familiarity with time series analysis, and ability to use (or at least to learn) a statistics package such as R or Splus.
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Copulae and Multivariate Probability Distributions in Finance

Author: Alexandra Dias,Mark Salmon,Chris Adcock

Publisher: Routledge

ISBN: 1317976908

Category: Business & Economics

Page: 208

View: 2274

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Portfolio theory and much of asset pricing, as well as many empirical applications, depend on the use of multivariate probability distributions to describe asset returns. Traditionally, this has meant the multivariate normal (or Gaussian) distribution. More recently, theoretical and empirical work in financial economics has employed the multivariate Student (and other) distributions which are members of the elliptically symmetric class. There is also a growing body of work which is based on skew-elliptical distributions. These probability models all exhibit the property that the marginal distributions differ only by location and scale parameters or are restrictive in other respects. Very often, such models are not supported by the empirical evidence that the marginal distributions of asset returns can differ markedly. Copula theory is a branch of statistics which provides powerful methods to overcome these shortcomings. This book provides a synthesis of the latest research in the area of copulae as applied to finance and related subjects such as insurance. Multivariate non-Gaussian dependence is a fact of life for many problems in financial econometrics. This book describes the state of the art in tools required to deal with these observed features of financial data. This book was originally published as a special issue of the European Journal of Finance.
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Mathematical Methods for Finance

Tools for Asset and Risk Management

Author: Sergio M. Focardi,Frank J. Fabozzi,Turan G. Bali

Publisher: John Wiley & Sons

ISBN: 1118421493

Category: Business & Economics

Page: 320

View: 8300

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The mathematical and statistical tools needed in the rapidlygrowing quantitative finance field With the rapid growth in quantitative finance, practitionersmust achieve a high level of proficiency in math and statistics.Mathematical Methods and Statistical Tools for Finance, partof the Frank J. Fabozzi Series, has been created with this in mind.Designed to provide the tools needed to apply finance theory toreal world financial markets, this book offers a wealth of insightsand guidance in practical applications. It contains applications that are broader in scope from what iscovered in a typical book on mathematical techniques. Most booksfocus almost exclusively on derivatives pricing, the applicationsin this book cover not only derivatives and asset pricing but alsorisk management—including credit risk management—andportfolio management. Includes an overview of the essential math and statisticalskills required to succeed in quantitative finance Offers the basic mathematical concepts that apply to the fieldof quantitative finance, from sets and distances to functions andvariables The book also includes information on calculus, matrix algebra,differential equations, stochastic integrals, and much more Written by Sergio Focardi, one of the world's leading authorsin high-level finance Drawing on the author's perspectives as a practitioner andacademic, each chapter of this book offers a solid foundation inthe mathematical tools and techniques need to succeed in today'sdynamic world of finance.
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