Abstract
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.
Original language | English |
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Pages (from-to) | 117-133 |
Number of pages | 17 |
Journal | International Statistical Review |
Volume | 78 |
Issue number | 1 |
DOIs | |
Publication status | Published - Apr 2010 |
Externally published | Yes |
Keywords
- Asymptotic tail dependence
- Maximum likelihood estimation
- Multivariate skew distribution
- Skew t distributions
- Skew Variance Gamma distribution
- Tail behaviour
- WinBUGS