| Description |
1 online resource |
| Series |
Lecture notes in statistics, 0930-0325 ; 213 |
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Lecture notes in statistics (Springer-Verlag) ; 213.
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| Contents |
A Convolution-Based Autoregressive Process / Umberto Cherubini, Fabio Gobbi -- Selection of Vine Copulas / Claudia Czado, Eike Christian Brechmann -- Copulas in Machine Learning / Gal Elidan -- An Overview of the Goodness-of-Fit Test Problem for Copulas / Jean-David Fermanian -- Assessing and Modeling Asymmetry in Bivariate Continuous Data / Christian Genest, Johanna G. Nešlehová -- Modeling Time-Varying Dependencies Between Positive-Valued High-Frequency Time Series / Nikolaus Hautsch, Ostap Okhrin -- The Limiting Properties of Copulas Under Univariate Conditioning / Piotr Jaworski -- Singular Mixture Copulas / Dominic Lauterbach, Dietmar Pfeifer -- Toward a Copula Theory for Multivariate Regular Variation / Haijun Li -- CIID Frailty Models and Implied Copulas / Jan-Frederik Mai, Matthias Scherer -- Copula-Based Models for Multivariate Discrete Response Data / Aristidis K. Nikoloulopoulos -- Vector Generalized Linear Models: A Gaussian Copula Approach / Peter X.-K. Song, Mingyao Li -- Application of Bernstein Copulas to the Pricing of Multi-Asset Derivatives / Bertrand Tavin |
| Summary |
Copulas are mathematical objects that fully capture the dependence structure among random variables and hence offer great flexibility in building multivariate stochastic models. Since their introduction in the early 1950s, copulas have gained considerable popularity in several fields of applied mathematics, especially finance and insurance. Today, copulas represent a well-recognized tool for market and credit models, aggregation of risks, and portfolio selection. Historically, the Gaussian copula model has been one of the most common models in credit risk. However, the recent financial crisis has underlined its limitations and drawbacks. In fact, despite their simplicity, Gaussian copula models severely underestimate the risk of the occurrence of joint extreme events. Recent theoretical investigations have put new tools for detecting and estimating dependence and risk (like tail dependence, time-varying models, etc) in the spotlight. All such investigations need to be further developed and promoted, a goal this book pursues. The bookincludes surveys that provide an up-to-date account of essential aspects of copula models in quantitative finance, as well as the extended versions of talks selected from papers presented at the workshop in Cracow |
| Analysis |
Statistics |
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Finance |
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Distribution (Probability theory) |
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Economics -- Statistics |
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Statistics for Business/Economics/Mathematical Finance/Insurance |
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Quantitative Finance |
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Probability Theory and Stochastic Processes |
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Financial Economics |
| Notes |
International conference proceedings |
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Includes index |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Online resource; title from PDF title page (SpringerLink, viewed July 2, 2013) |
| Subject |
Copulas (Mathematical statistics) -- Congresses
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Mathematics.
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Mathematics
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mathematics.
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applied mathematics.
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MATHEMATICS -- Probability & Statistics -- Multivariate Analysis.
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Matemáticas
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Mathematics
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Copulas (Mathematical statistics)
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| Genre/Form |
proceedings (reports)
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Conference papers and proceedings
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Conference papers and proceedings.
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Actes de congrès.
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| Form |
Electronic book
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| Author |
Jaworski, Piotr (Andrzej Piotr)
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Durante, Fabrizio
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Härdle, Wolfgang
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| ISBN |
9783642354076 |
|
3642354076 |
|
3642354068 |
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9783642354069 |
|
