Dependence Modeling: Vine Copula Handbook, Kurowicka Dorota Et Al

Автор: Nelsen
Название: An Introduction to Copulas
ISBN: 0387286594 ISBN-13(EAN): 9780387286594
Издательство: Springer
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Цена: 22359.00 р.
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Описание: Copulas are functions that join multivariate distribution functions to their one-dimensional margins. The study of copulas and their role in statistics is a new but vigorously growing field. In this book the student or practitioner of statistics and probability will find discussions of the fundamental properties of copulas and some of their primary applications. The applications include the study of dependence and measures of association, and the construction of families of bivariate distributions.With nearly a hundred examples and over 150 exercises, this book is suitable as a text or for self-study. The only prerequisite is an upper level undergraduate course in probability and mathematical statistics, although some familiarity with nonparametric statistics would be useful. Knowledge of measure-theoretic probability is not required.Roger B. Nelsen is Professor of Mathematics at Lewis & Clark College in Portland, Oregon. He is also the author of "Proofs Without Words: Exercises in Visual Thinking," published by the Mathematical Association of America.

Автор: J?rome Dedecker; Paul Doukhan; Gabriel Lang; Jos?
Название: Weak Dependence: With Examples and Applications
ISBN: 0387699511 ISBN-13(EAN): 9780387699516
Издательство: Springer
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Цена: 18167.00 р.
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Описание: Develops Doukhan/Louhichi`s 1999 idea to measure asymptotic independence of a random process.

Автор: Umberto Cherubini; Fabio Gobbi; Sabrina Mulinacci
Название: Convolution Copula Econometrics
ISBN: 3319480146 ISBN-13(EAN): 9783319480145
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book presents a novel approach to time series econometrics, which studies the behavior of nonlinear stochastic processes. This approach allows for an arbitrary dependence structure in the increments and provides a generalization with respect to the standard linear independent increments assumption of classical time series models. The book offers a solution to the problem of a general semiparametric approach, which is given by a concept called C-convolution (convolution of dependent variables), and the corresponding theory of convolution-based copulas. Intended for econometrics and statistics scholars with a special interest in time series analysis and copula functions (or other nonparametric approaches), the book is also useful for doctoral students with a basic knowledge of copula functions wanting to learn about the latest research developments in the field.

Автор: Pipiras
Название: Long-Range Dependence and Self-Similarity
ISBN: 1107039460 ISBN-13(EAN): 9781107039469
Издательство: Cambridge Academ
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Цена: 13939.00 р.
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Описание: Real-world time series rarely satisfy simple assumptions, often exhibiting long-range dependence. Ignoring this undermines accurate detection of trends and other important behavior. This text for graduate students and researchers in statistics and probability is also a reference for specialists in fields such as economics, finance, and hydrology.

Автор: Malevergne Yannick, Sornette Didier
Название: Extreme Financial Risks / From Dependence to Risk Management
ISBN: 354027264X ISBN-13(EAN): 9783540272649
Издательство: Springer
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Цена: 9781.00 р.
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Описание: Portfolio analysis and optimization, together with the associated risk assessment and management, require knowledge of the likely distributions of returns at different time scales and insights into the nature and properties of dependences between the different assets.This book offers an original and thorough treatment of these two domains, focusing mainly on the concepts and tools that remain valid for large and extreme price moves. Strong emphasis is placed on the theory of copulas and their empirical testing and calibration, because they offer intrinsic and complete measures of dependences.Extreme Financial Risks will be useful to: students looking for a general and in-depth introduction to the field; financial engineers, economists, econometricians, actuarial professionals; researchers and mathematicians looking for a synoptic view comparing the pros and cons of different modelling strategies; andquantitative practitioners for the insights offered on the subtleties and the many dimensional components of both risk and dependence. In toto, the content of this book will also be useful to a broader scientific community interested in quantifying the complexity of many natural and artificial processes in which a growing emphasis is on the role and importance of extreme phenomena.