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Title:

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

Document type:
Zeitschriftenaufsatz
Author(s):
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...     »
Keywords:
Forecasting, Partial correlation vine Realized volatility Time-series modeling R-vine structure selection
Dewey Decimal Classification:
510 Mathematik
Journal title:
Computational Statistics & Data Analysis
Year:
2020
Journal volume:
142
Year / month:
2020-02
Quarter:
1. Quartal
Month:
Feb
Journal issue:
142
Pages contribution:
t.b.a.
Language:
en
Fulltext / DOI:
doi:10.1016/j.csda.2019.106810
Publisher:
Elsevier BV
E-ISSN:
0167-9473
Date of publication:
01.02.2020
TUM Institution:
Professur für Angewandte Mathematische Statistik
Format:
Text
 BibTeX