User: Guest  Login
Document type:
Zeitungsartikel 
Author(s):
Kreuzer, A. and Czado, C. 
Title:
Bayesian inference for a single factor copula stochastic volatility model using Hamiltonian Monte Carlo 
Abstract:
Single factor models are used in finance to model the joint behaviour of stocks. The dependence is commonly modeled with a multivariate normal distribution. Krupskii and Joe(2013) provide a copula based extension. This single factor copula requires the specification of bivariate linking copulas. Resulting joint models can accommodate symmetric or asymmetric tail dependence. For modeling multivariate time series we propose a single factor copula model together with stochastic volatility margins....    »
 
Dewey Decimal Classification:
510 Mathematik 
Journal title:
Preprint 
Year:
2019 
Year / month:
2019-11 
Quarter:
4. Quartal 
Month:
Nov 
Language:
en 
WWW:
Status:
Preprint / submitted 
TUM Institution:
Professur für Angewandte Mathematische Statistik 
Format:
Text