Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/240566 
Erscheinungsjahr: 
2021
Schriftenreihe/Nr.: 
PhD Series No. 218
Verlag: 
University of Copenhagen, Department of Economics, Copenhagen
Zusammenfassung: 
In this thesis, we study a class of multivariate generalized autoregressive heteroskedasticity (GARCH) models, denoted the Dynamic Conditional Eigenvalue GARCH (or λ-GARCH) model. Multivariate GARCH models are useful for estimating and filtering time varying(co-)variances, which are used e.g. in empirical asset pricing, Markovitz-type portfoliooptimization and value-at-risk estimation. GARCH models have long been a staple inempirical finance and financial econometrics. This thesis contains three self-containedchapters on the λ-GARCH, covering large-sample properties and bootstrap-based inference.
Dokumentart: 
Doctoral Thesis

Datei(en):
Datei
Größe
1.68 MB





Publikationen in EconStor sind urheberrechtlich geschützt.