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  • Conference proceedings
  • © 2013

Copulae in Mathematical and Quantitative Finance

Proceedings of the Workshop Held in Cracow, 10-11 July 2012

  • A new reference book for copula-based stochastic models in quantitative finance
  • An up-to-date account about recent developments in copula-based financial models
  • Includes supplementary material: sn.pub/extras

Part of the book series: Lecture Notes in Statistics (LNS, volume 213)

Part of the book sub series: Lecture Notes in Statistics - Proceedings (LNSP)

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Table of contents (13 papers)

  1. Front Matter

    Pages i-xii
  2. A Convolution-Based Autoregressive Process

    • Umberto Cherubini, Fabio Gobbi
    Pages 1-15
  3. Selection of Vine Copulas

    • Claudia Czado, Eike Christian Brechmann, Lutz Gruber
    Pages 17-37
  4. Copulas in Machine Learning

    • Gal Elidan
    Pages 39-60
  5. Assessing and Modeling Asymmetry in Bivariate Continuous Data

    • Christian Genest, Johanna G. Nešlehová
    Pages 91-114
  6. Modeling Time-Varying Dependencies Between Positive-Valued High-Frequency Time Series

    • Nikolaus Hautsch, Ostap Okhrin, Alexander Ristig
    Pages 115-127
  7. Singular Mixture Copulas

    • Dominic Lauterbach, Dietmar Pfeifer
    Pages 165-175
  8. CIID Frailty Models and Implied Copulas

    • Jan-Frederik Mai, Matthias Scherer, Rudi Zagst
    Pages 201-230
  9. Copula-Based Models for Multivariate Discrete Response Data

    • Aristidis K. Nikoloulopoulos
    Pages 231-249
  10. Vector Generalized Linear Models: A Gaussian Copula Approach

    • Peter X.-K. Song, Mingyao Li, Peng Zhang
    Pages 251-276
  11. Back Matter

    Pages 289-294

About this book

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 book includes 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.

Editors and Affiliations

  • Faculty of Mathematics, Informatics, and Mechanics, University of Warsaw, Warszawa, Poland

    Piotr Jaworski

  • School of Economics and Management, Free University of Bozen-Bolzano, Bozen, Italy

    Fabrizio Durante

  • L.v.Bortkiewicz Chair of Statistics, C.A.S.E. Centre f. Appl. Stat. & Econ., Humboldt-Universität zu Berlin, Berlin, Germany

    Wolfgang Karl Härdle

About the editors

Piotr Jaworski is a Professor at the Faculty of Mathematics, Informatics and Mechanics at the Warsaw University Institute of Mathematics. He is also active in the Section of Financial and Actuarial Mathematics. He has engaged in research stays at several universities, e.g. Moscow State University (PhD studies), University of North Carolina in Chapel Hill (USA), University of Muenster (Germany), University of Dortmund (Germany), University of Cottbus (Germany) and Johannes Kepler University of Linz (Austria). At present his researches primarily focuses on the copula approach to multivariate modeling, risk theory and portfolio analysis.

Fabrizio Durante received his PhD (2006) at the University of Lecce (Italy) and completed his postdoctoral studies (2010) at the Johannes Kepler University of Linz (Austria). From 2006-2010, he was an assistant professor at Johannes Kepler University of Linz (Austria), before he started his appointment as an assistant professor in Statistics at the Free University of Bolzano-Bozen in 2010. He has had research stays at several European universities, e.g. Humboldt University (Berlin, Germany), University "La Sapienza" (Rome, Italy), University of Bratislava (Slovakia), University of Granada (Spain), and the University of Warsaw (Poland). His research interests include stochastic models, reliability theory, and risk management.

Wolfgang Karl Härdle is a Professor of Statistics at the Humboldt-Universität zu Berlin and the Director of CASE – the Centre for Applied Statistics and Economics. He teaches quantitative finance and semi-parametric statistical methods. His research focuses on dynamic factor models, multivariate statistics in finance and computational statistics. He is an elected member of the ISI and an advisor to the Guanghua School of Management, Peking University and to National Central University, Taiwan.

Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access