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Title:

Bayesian inference for a single factor copula stochastic volatility model using Hamiltonian Monte Carlo

Document type:
Zeitschriftenaufsatz
Author(s):
Kreuzer, Alexander; Czado, Claudia
Abstract:
For modeling multivariate financial time series a single factor copula model with stochastic volatility margins is proposed. It generalizes single factor models based on the multivariate normal distribution by allowing for symmetric and asymmetric tail dependence. A joint Bayesian approach using Hamiltonian Monte Carlo (HMC) within Gibbs sampling is developed. Thus, the information loss caused by the two-step approach for margins and dependence is avoided. Further, the Bayesian approach is tract...     »
Keywords:
Factor copula; Stochastic volatility model; Hamiltonian Monte Carlo; Value at risk
Dewey Decimal Classification:
510 Mathematik
Journal title:
Econometrics and Statistics
Year:
2021
Journal volume:
19
Year / month:
2021-07
Quarter:
3. Quartal
Month:
Jul
Pages contribution:
130-150
Language:
en
Fulltext / DOI:
doi:10.1016/j.ecosta.2020.12.001
Publisher:
Elsevier BV
E-ISSN:
2452-3062
Date of publication:
01.07.2021
Semester:
SS 21
TUM Institution:
Professur für Angewandte Mathematische Statistik
Format:
Text
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