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Extreme Events and Multi-Name Credit Derivatives
Year Of Publication: 2003
Month Of Publication: September
Pages: 32
Download Count: 534
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Comment Num: 0
Language: EN
Who Can Read: Free
Date: 8-5-2006
Publisher: Administrator
The dependence structure of asset returns lies at the heart of a class of models that iswidely employed for the valuation of multi-name credit derivatives. In this work, we study thedependence structure of asset returns using copula functions. In particular, using a statisticalmethodology that relies on a minimal amount of distributional assumptions, we compare thedependence structures of asset and equity returns to provide some insight into the commonpractice of estimating the former using equity data. Our results show that the presence ofjoint extreme events in the data is not compatible with the assumption of Normal dependence,and support the use of equity returns as proxies for asset returns. Furthermore, we presentevidence that the likelihood of joint extreme events does not diminish as we decrease the samplingfrequency of our observations. Building on our empirical ndings, we then describe how tocapture the e ects of joint extreme events by means of a simple and computationally ecienttime-to-default simulation. Using a t-copula model, we analyze the impact of extreme events onthe fair values and risk measures of popular multi-name credit derivatives such as nth-to-defaultbaskets and synthetic loss tranches.
Mashal, Roy Sign in to follow this author
Naldi, Marco Sign in to follow this author
Zeevi, Assaf Sign in to follow this author
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