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Copula Methods in Finance Hardcover – Jul 2 2004
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"...This book is of great use for researchers as well as practitioners..." (Statistical Papers, July 2005)
From the Back Cover
The evaluation and risk measurement of portfolios of complex non-linear positions and non-normal risk factors has become a major nightmare for people working in the structured finance business. Dealing with "fat tails" and "smile effects", as well as the typical asymmetric shape of default risk has rapidly made obsolete the traditional linear correlation tools. In this new environment, the copula functions methodology has become the most significant new technique to handle the co-movement between markets and risk factors in a flexible way. This is the first book addressing copula functions from the viewpoint of mathematical finance applications. The method is to explain copulas by means of applications to major topics in derivative pricing and credit risk analysis, with the target to make the reader able to device her own application, following the strategies illustrated throughout the book. Examples include pricing of the main exotic derivatives typically included in commonly traded structured finance products (barrier, basket, rainbow options), as well as risk management issues. Particular focus is given to the pricing of asset-backed securities and basket credit derivative products and the evaluation of counterparty risk in derivative transactions.
Copula Methods in Finance provides:
- Rigorous treatment of the mathematics of copula functions, illustrated with financial applications
- Complete analysis of estimation and simulation issues applied to market data
- Credit-linked structured products applications: CDO and basket credit derivatives
- Equity-linked structured product applications: barrier, rainbow and basket derivatives
- Counterparty risk in derivative transactions: vulnerable option pricing
Inside This Book(Learn More)
Here we give a brief description of the basic pillar behind pricing techniques, that is the use of risk-neutral probability measures to evaluate contingent claims, versus the objective measure observed from the time series of market data. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
Most Helpful Customer Reviews on Amazon.com (beta)
However, there are numerous errors that I've come across, which make learning from this book very difficult or impossible. In fact, every section I've looked at in detail has mistakes, not typos, in the equations. (I just dropped my rating to 2 stars because of this!) The multivariate Frechet minimum boundary is written incorrectly in multiple locations. Whereas an example demonstrates that this bound is not a true copula, the following theorem says that it is a copula. The reference for the theorem, Sklar (1999), actually reads "Personal communication" in the bibliography! This reference is only slightly better than "From a dream..."
Unfortunate notation confuses the reader by repeating the copula density notation for the "conditional distribution" in the simulation section. This section is also riddled with mistakes and unexplained notation. Thankfully, enough examples exist that some use can be make of portions of the text by the practitioner.
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