Copulae in Mathematical and Quantitative Finance

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

  • Piotr Jaworski
  • Fabrizio Durante
  • Wolfgang Karl Härdle
Conference proceedings

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

Also part of the Lecture Notes in Statistics - Proceedings book sub series (LNSP, volume 213)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Umberto Cherubini, Fabio Gobbi
    Pages 1-15
  3. Claudia Czado, Eike Christian Brechmann, Lutz Gruber
    Pages 17-37
  4. Gal Elidan
    Pages 39-60
  5. Christian Genest, Johanna G. Nešlehová
    Pages 91-114
  6. Nikolaus Hautsch, Ostap Okhrin, Alexander Ristig
    Pages 115-127
  7. Dominic Lauterbach, Dietmar Pfeifer
    Pages 165-175
  8. Jan-Frederik Mai, Matthias Scherer, Rudi Zagst
    Pages 201-230
  9. Aristidis K. Nikoloulopoulos
    Pages 231-249
  10. Peter X.-K. Song, Mingyao Li, Peng Zhang
    Pages 251-276
  11. Back Matter
    Pages 289-294

About these proceedings


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.



Gaussian copula model Random variables Tail dependence Time-varying models

Editors and affiliations

  • Piotr Jaworski
    • 1
  • Fabrizio Durante
    • 2
  • Wolfgang Karl Härdle
    • 3
  1. 1.Faculty of Mathematics, Informatics, and MechanicsUniversity of WarsawWarszawaPoland
  2. 2.School of Economics and ManagementFree University of Bozen-BolzanoBozenItaly
  3. 3.L.v.Bortkiewicz Chair of Statistics, C.A.S.E. Centre f. Appl. Stat. & Econ.Humboldt-Universität zu BerlinBerlinGermany

Bibliographic information