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Modelling and Estimation for Bivariate Financial Returns
Author(s) -
Fung Thomas,
Seneta Eugene
Publication year - 2010
Publication title -
international statistical review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.051
H-Index - 54
eISSN - 1751-5823
pISSN - 0306-7734
DOI - 10.1111/j.1751-5823.2010.00106.x
Subject(s) - bivariate analysis , econometrics , skew , variance (accounting) , mathematics , maximum likelihood , bivariate data , statistics , representation (politics) , estimation , economics , computer science , accounting , telecommunications , management , politics , political science , law
Summary 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.