Benutzer: Gast  Login
Titel:

A partial correlation vine based approach for modeling and forecasting multivariate volatility time-series

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Barthel, Nicole; Czado, Claudia; Okhrin, Yarema
Abstract:
A novel approach for dynamic modeling and forecasting of realized covariance matrices is proposed. Realized variances and realized correlation matrices are jointly estimated. The one-to-one relationship between a positive definite correlation matrix and its associated set of partial correlations corresponding to any vine specification is used for data transformation. The model components therefore are realized variances as well as realized standard and partial correlations corresponding to a dai...     »
Stichworte:
Forecasting, Partial correlation vine Realized volatility Time-series modeling R-vine structure selection
Dewey Dezimalklassifikation:
510 Mathematik
Zeitschriftentitel:
Computational Statistics & Data Analysis
Jahr:
2020
Band / Volume:
142
Jahr / Monat:
2020-02
Quartal:
1. Quartal
Monat:
Feb
Heft / Issue:
142
Seitenangaben Beitrag:
t.b.a.
Sprache:
en
Volltext / DOI:
doi:10.1016/j.csda.2019.106810
Verlag / Institution:
Elsevier BV
E-ISSN:
0167-9473
Publikationsdatum:
01.02.2020
TUM Einrichtung:
Professur für Angewandte Mathematische Statistik
Format:
Text
 BibTeX