Modelling the Dynamics of Conditional Dependency Between Financial Series
Détails
ID Serval
serval:BIB_4A2654A0627E
Type
Partie de livre
Collection
Publications
Institution
Titre
Modelling the Dynamics of Conditional Dependency Between Financial Series
Titre du livre
Multi-moment Asset Allocation and Pricing Models
Editeur
Wiley
Lieu d'édition
Chichester, UK
ISBN
9780470034156
9781119201830
9781119201830
Statut éditorial
Publié
Date de publication
2006
Editeur⸱rice scientifique
Jurczenko E., Maillet B.
Série
Wiley Finance Series
Numéro de chapitre
8
Pages
195-221
Langue
anglais
Résumé
This chapter introduces a flexible copula-based multivariate distributional specification that allows for wide possibilities of dynamics for conditional systematic (co) higher moments. The chapter develops a new methodology to measure conditional dependency between daily stock-market returns, which are known to be driven by complicated marginal distributions. Copula functions are used, which are a convenient tool for joining marginal distributions. The marginal model is a GARCH-type model with time-varying skewness and kurtosis. It is known that the residuals obtained for a GARCH model are generally non-normal, and this observation has led to the introduction of fat-tailed distributions for innovations. This chapter models the dynamics of the dependency parameter of the copula as a function of predetermined variables. It provides evidence that the model fits the data quite well. The chapter establishes that the dependency parameter is both large and persistent between European markets. This methodology has many potential applications, such as VaR measurement and portfolio allocation in non-Gaussian environments.
Création de la notice
09/05/2008 13:52
Dernière modification de la notice
20/08/2019 14:57