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The Fourier Copula: Theory & Applications
Year Of Publication: 2011
Month Of Publication: April
Pages: 80
Download Count: 7
View Count: 1336
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 4-19-2011
Publisher: Administrator
Summary
This paper introduces a new parametric copula family based on Fourier expansions and flexible enough to describe arbitrary dependence structures. We derive its various properties and show that it can be fit efficiently by the Fast Fourier Transform. We overcome the Fourier series' assumption of periodicity by using a pseudo-copula and demonstrate the resulting model's superiority in applications like financial risk management. The concept of "discordant tail dependence" is introduced along with a Fourier-Clayton mixture copula. The Fourier-Clayton copula allows for some measure of tail dependence and also reduces the dimensionality of the Fourier copula's parameter space. The distinguishing feature of this new family of copulas is its ability to transform a flexible nonparametric density estimate into a robust parametric model.
Author(s)
Lowin, Jeremiah Sign in to follow this author
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