Modelling and estimation for bivariate financial returns | Macquarie University ResearchOnline

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.14/147015

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Title: Modelling and estimation for bivariate financial returns
Related: International statistical review, Vol. 78, No. 1, (2010), p.117-133
DOI: 10.1111/j.1751-5823.2010.00106.x
Publisher: Wiley-Blackwell
Date: 2010
Author/Creator: Fung, Thomas
Author/Creator: Seneta, Eugene
Description: Maximum likelihood estimates are obtained for long data sets of bivariate financial returns using mixing representation of the bivariate (skew) Variance Gamma (VG) and two (skew) t distributions. By analysing simulated and real data, issues such as asymptotic lower tail dependence and competitiveness of the three models are illustrated. A brief review of the properties of the models is included. The present paper is a companion to papers in this journal by Demarta & McNeil and Finlay & Seneta.
Description: 17 page(s)
Subject Keyword: Asymptotic tail dependence
Subject Keyword: maximum likelihood estimation
Subject Keyword: multivariate skew distribution
Subject Keyword: skew t distributions
Subject Keyword: skew Variance Gamma distribution
Subject Keyword: tail behaviour
Subject Keyword: WinBUGS
Resource Type: journal article
Organisation: Macquarie University. Dept. of Statistics

Macquarie University ResearchOnline