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Dissertations

Inferring dependencies between financial assets with applications to multi-name credit derivatives

Roy Mashal, 2004
Faculty Advisor: Assaf Zeevi

Abstract

In this dissertation we: (1) develop a statistical framework for testing dependence assumptions in a given time series; (2) develop a statistical test for comparing dependence structures (aka copula functions ) derived from the Normal and Student-t distributions and use this to quantify the potential for extreme co-movements and; (3) analyze in detail credit derivative models and their sensitivity to different dependence assumptions. The main results of our studies may be summarized as follows. First, the t-copula assumption is a more plausible model of dependence for the tested time-series; the Normal copula provides a lesser fit than the t-copula but a superior fit compared with the three Archimedean copulas tested, namely, Frank, Gumbel, and Clayton. Second, exploiting the nesting of the Normal copula within the t-family we show that the former can be almost always rejected on the basis of a likelihood ratio test. Third, financial data exhibit a clear tendency for extreme co-movements which cannot be predicted on the basis of a Normal copula model. Fourth, as the dimensionality increases (i.e., the number of assets being tested for dependence increases) the distinction between the Normal and t-copulas become “sharper”. Fifth, the dependence structure of asset returns is strikingly similar to the one underlying equity returns. Finally, the tendency for extreme co-movements does not seem to be affected by the sampling frequency, in contrast to the phenomenon observed in univariate returns that tend to be “heavy-tailed” in higher frequencies, and more “Gaussian-like” in lower frequencies. Our results bear important financial implications which we illustrate throughout this thesis with examples that include: MSCI national equity indices data; risk measure for portfolios of equity options; pricing n th to default baskets; pricing and risk measures of synthetic CDO tranches, and; analysis of portfolio tail dependence indices.

Doctoral Program News

Honigsberg featured in Ideas at Work

The August issue of Ideas at Work features research that doctoral candidate Colleen Honigsberg led in conjunction with Sharon Katz.

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Wazlawek featured in Ideas at Work

Abbie Wazlawek's joint research with Professor Daniel Ames is featured in the June 24th, 2014 edition of Ideas at Work

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Ethan Rouen featured in Ideas at Work

Ethan Rouen's joint research with Professor Dan Amiram is featured in the May 15th, 2014 edition of Ideas at Work

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Rivas Wins Fellowship

The PhD program is proud to congratulate Miguel Duro Rivas, who was awarded the Nasdaq Educational Foundation Doctoral Dissertation Fellowship.

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Wong wins Deloitte Fellowship

We are proud to announce that Yu Ting (Forester) Wong is one of the recipients of the 2014 Deloitte Foundation Doctoral Fellowship in Accounting.

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The PhD Program Congratulates John Yao

PhD student John Yao was a finalist in the 2013 M&SOM (Manufacturing & Service Operations Management) student paper competition.

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Honigsberg Named Postdoctoral Fellow

The PhD program is proud to congratulate Colleen Honigsberg, who was named the Postdoctoral Fellow in Corporate Governance at the Millstein Center at Columbia Law School in October 2013

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Master of Science in Financial Economics

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Regular Decision: Feb 15, 2014

 

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