A Practical Guide to Heavy Tails

A Practical Guide to Heavy Tails

Emphasis is placed on developments in handling the numerical problems associated with stable distribution (a main technical difficulty until recently). No index. Annotation copyrighted by Book News, Inc., Portland, OR

Author: Robert Adler

Publisher: Springer Science & Business Media

ISBN: 0817639519

Category: Mathematics

Page: 534

View: 102

Twenty-four contributions, intended for a wide audience from various disciplines, cover a variety of applications of heavy-tailed modeling involving telecommunications, the Web, insurance, and finance. Along with discussion of specific applications are several papers devoted to time series analysis, regression, classical signal/noise detection problems, and the general structure of stable processes, viewed from a modeling standpoint. Emphasis is placed on developments in handling the numerical problems associated with stable distribution (a main technical difficulty until recently). No index. Annotation copyrighted by Book News, Inc., Portland, OR
Categories: Mathematics

Handbook of Heavy Tailed Distributions in Finance

Handbook of Heavy Tailed Distributions in Finance

A Practical Guide to Heavy Tails. Birkhäuser, Boston, MA. Chambers, J.M., Mallows, C., Stuck, B.W., 1976. A method for simulating stable random variables. JASA 71, 340–344. Cheng, B.N., Rachev, S.T., 1995.

Author: S.T Rachev

Publisher: Elsevier

ISBN: 0080557732

Category: Business & Economics

Page: 704

View: 414

The Handbooks in Finance are intended to be a definitive source for comprehensive and accessible information in the field of finance. Each individual volume in the series should present an accurate self-contained survey of a sub-field of finance, suitable for use by finance and economics professors and lecturers, professional researchers, graduate students and as a teaching supplement. The goal is to have a broad group of outstanding volumes in various areas of finance. The Handbook of Heavy Tailed Distributions in Finance is the first handbook to be published in this series. This volume presents current research focusing on heavy tailed distributions in finance. The contributions cover methodological issues, i.e., probabilistic, statistical and econometric modelling under non- Gaussian assumptions, as well as the applications of the stable and other non -Gaussian models in finance and risk management.
Categories: Business & Economics

Risk Theory A Heavy Tail Approach

Risk Theory  A Heavy Tail Approach

In: Adler, R., Feldman, R. and Taqqu, M.S. (Eds.) A Practical Guide to Heavy Tails: Statistical Techniques for Analysing Heavy-Tailed Distributions, 435–459. Haan, L. de (1970) On Regular Variation and Its Application to Weak ...

Author: Konstantinides Dimitrios George

Publisher: #N/A

ISBN: 9789813223165

Category: Mathematics

Page: 508

View: 991

This book is written to help graduate students and young researchers to enter quickly into the subject of Risk Theory. It can also be used by actuaries and financial practitioners for the optimization of their decisions and further by regulatory authorities for the stabilization of the insurance industry. The topic of extreme claims is especially presented as a crucial feature of the modern ruin probability.
Categories: Mathematics

Handbook Of Heavy tailed Distributions In Asset Management And Risk Management

Handbook Of Heavy tailed Distributions In Asset Management And Risk Management

A Practical Guide to Heavy Tails: Statistical Techniques and Applications. Birkhäuser, Boston, 1998. A. Akgiray and G. Booth. The stable-law model of stock returns. Journal of Business and Economic Statistics, 6:51–57, 1988.

Author: Stoyan V Stoyanov

Publisher: World Scientific

ISBN: 9789813276215

Category: Business & Economics

Page: 600

View: 913

The study of heavy-tailed distributions allows researchers to represent phenomena that occasionally exhibit very large deviations from the mean. The dynamics underlying these phenomena is an interesting theoretical subject, but the study of their statistical properties is in itself a very useful endeavor from the point of view of managing assets and controlling risk. In this book, the authors are primarily concerned with the statistical properties of heavy-tailed distributions and with the processes that exhibit jumps. A detailed overview with a Matlab implementation of heavy-tailed models applied in asset management and risk managements is presented. The book is not intended as a theoretical treatise on probability or statistics, but as a tool to understand the main concepts regarding heavy-tailed random variables and processes as applied to real-world applications in finance. Accordingly, the authors review approaches and methodologies whose realization will be useful for developing new methods for forecasting of financial variables where extreme events are not treated as anomalies, but as intrinsic parts of the economic process.
Categories: Business & Economics

Nonparametric Analysis of Univariate Heavy Tailed Data

Nonparametric Analysis of Univariate Heavy Tailed Data

Feller, W. (1968) An Introduction to Probability Theory and Its Applications I, II, 3rd edition. ... R. Feldman and M.S. Taqqu (eds), A Practical Guide to Heavy Tails: Statistical Techniques for Analysing Heavy Tailed Distributions, pp.

Author: Natalia Markovich

Publisher: John Wiley & Sons

ISBN: 0470723599

Category: Mathematics

Page: 336

View: 226

Heavy-tailed distributions are typical for phenomena in complex multi-component systems such as biometry, economics, ecological systems, sociology, web access statistics, internet traffic, biblio-metrics, finance and business. The analysis of such distributions requires special methods of estimation due to their specific features. These are not only the slow decay to zero of the tail, but also the violation of Cramer’s condition, possible non-existence of some moments, and sparse observations in the tail of the distribution. The book focuses on the methods of statistical analysis of heavy-tailed independent identically distributed random variables by empirical samples of moderate sizes. It provides a detailed survey of classical results and recent developments in the theory of nonparametric estimation of the probability density function, the tail index, the hazard rate and the renewal function. Both asymptotical results, for example convergence rates of the estimates, and results for the samples of moderate sizes supported by Monte-Carlo investigation, are considered. The text is illustrated by the application of the considered methodologies to real data of web traffic measurements.
Categories: Mathematics

The Fundamentals of Heavy Tails

The Fundamentals of Heavy Tails

In R. J. Adler, R. E. Feldman, and M. S. Taqqu, eds., A practical guide to heavy tails: statistical techniques and applications, pages 435–459. Birkhäuser, 1998. [102] C. M. Goldie. Implicit renewal theory and tails of solutions of ...

Author: Jayakrishnan Nair

Publisher: Cambridge University Press

ISBN: 9781316511732

Category: Business & Economics

Page: 160

View: 779

An accessible yet rigorous package of probabilistic and statistical tools for anyone who must understand or model extreme events.
Categories: Business & Economics

Heavy Tail Phenomena

Heavy Tail Phenomena

M. Crovella, A. Bestavros, and M. S. Taqqu, Heavy-tailed probability distributions in the world wide web, in M. S. Taqqu, R. Adler, R. Feldman, eds., A Practical Guide to Heavy Tails: Statistical Techniques forAnalyzing Heavy Tailed ...

Author: Sidney I. Resnick

Publisher: Springer Science & Business Media

ISBN: 9780387450247

Category: Mathematics

Page: 404

View: 592

This comprehensive text gives an interesting and useful blend of the mathematical, probabilistic and statistical tools used in heavy-tail analysis. It is uniquely devoted to heavy-tails and emphasizes both probability modeling and statistical methods for fitting models. 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 a statistics package. This work will serve second-year graduate students and researchers in the areas of applied mathematics, statistics, operations research, electrical engineering, and economics.
Categories: Mathematics

Workload Modeling for Computer Systems Performance Evaluation

Workload Modeling for Computer Systems Performance Evaluation

Heavy-tailed data is not new. To quote from the preface of A Practical Guide to Heavy Tails [16], Ever since data has been collected, they have fallen into two quite distinct groups: “good data,” which meant that their owners knew how ...

Author: Dror G. Feitelson

Publisher: Cambridge University Press

ISBN: 9781107078239

Category: Computers

Page: 564

View: 793

A book for experts and practitioners, emphasizing the intuition and reasoning behind definitions and derivations related to evaluating computer systems performance.
Categories: Computers

Advances in Heavy Tailed Risk Modeling

Advances in Heavy Tailed Risk Modeling

A Practical Guide to Heavy Tails: Statistical Techniques and Applications. Springer. Feller, W. 1945. The fundamental limit theorems in probability. Bulletin of the American Mathematical Society, 51(11), 800–832. Feller, W. 1966.

Author: Gareth W. Peters

Publisher: John Wiley & Sons

ISBN: 9781118909553

Category: Mathematics

Page: 656

View: 669

A cutting-edge guide for the theories, applications, and statistical methodologies essential to heavy tailed risk modeling Focusing on the quantitative aspects of heavy tailed loss processes in operational risk and relevant insurance analytics, Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk presents comprehensive coverage of the latest research on the theories and applications in risk measurement and modeling techniques. Featuring a unique balance of mathematical and statistical perspectives, the handbook begins by introducing the motivation for heavy tailed risk processes in high consequence low frequency loss modeling. With a companion, Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk, the book provides a complete framework for all aspects of operational risk management and includes: Clear coverage on advanced topics such as splice loss models, extreme value theory, heavy tailed closed form loss distributional approach models, flexible heavy tailed risk models, risk measures, and higher order asymptotic approximations of risk measures for capital estimation An exploration of the characterization and estimation of risk and insurance modelling, which includes sub-exponential models, alpha-stable models, and tempered alpha stable models An extended discussion of the core concepts of risk measurement and capital estimation as well as the details on numerical approaches to evaluation of heavy tailed loss process model capital estimates Numerous detailed examples of real-world methods and practices of operational risk modeling used by both financial and non-financial institutions Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk is an excellent reference for risk management practitioners, quantitative analysts, financial engineers, and risk managers. The book is also a useful handbook for graduate-level courses on heavy tailed processes, advanced risk management, and actuarial science.
Categories: Mathematics