Benutzer: Gast  Login
Titel:

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

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
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...     »
Stichworte:
Factor copula; Stochastic volatility model; Hamiltonian Monte Carlo; Value at risk
Dewey Dezimalklassifikation:
510 Mathematik
Zeitschriftentitel:
Econometrics and Statistics
Jahr:
2021
Band / Volume:
19
Jahr / Monat:
2021-07
Quartal:
3. Quartal
Monat:
Jul
Seitenangaben Beitrag:
130-150
Sprache:
en
Volltext / DOI:
doi:10.1016/j.ecosta.2020.12.001
Verlag / Institution:
Elsevier BV
E-ISSN:
2452-3062
Publikationsdatum:
01.07.2021
Semester:
SS 21
TUM Einrichtung:
Professur für Angewandte Mathematische Statistik
Format:
Text
 BibTeX