This is a succinct guide to the application and modelling of dependence models or copulas in the financial markets. First applied to credit risk modelling, copulas are now widely used across a range of derivatives transactions, asset pricing techniques and risk models and are a core part of the financial engineer's toolkit.

Author team provides a good balance of academic rigor and market practice essential for this complex topic The focus of the book is on arbitrary dimensions and arbitrary copulas (as is required in the industry), as opposed to 'bivariate literature' and 'elliptical copula literature' The book addresses specific modelling challenges in the industry, and illustrates how copula methods can help

Autorentext
Dr. Matthias Scherer is Professor of Mathematical Finance at the Technische Universität München, where he gives lectures in Mathematical Finance and Statistics. His research interests span Mathematical Finance, but focus on credit-risk analysis and the application of copulas. He holds a PhD from the University of Ulm, and a Masters in Mathematics from Syracuse University. Dr. Scherer has co-authored numerous articles on financial topics including dependence modeling and the book Simulating Copulas: Stochastic Models, Sampling Algorithms, and Applications.

Dr. Jan-Frederik Mai is Quantitative Analyst at XAIA Investment GmbH. He holds a PhD in Financial Mathematics from Technische Universität München and is co-author of numerous research articles in the field of dependence modeling and of the book Simulating Copulas: Stochastic Models, Sampling Algorithms, and Applications.

Inhalt

1. What are Copulas? 2. Which Rules for Handling Copulas Do I Need? 3. How to Measure Dependence? 4. What are Popular Families or Copulas? 5. How to Stimulate Multivariate Distributions? 6. How to Estimate Parameters of a Multivariate Model? 7. How to Deal with Uncertainty Concerning Dependence? 8. How to Construct a Portfolio-Default Model?