Header

UZH-Logo

Maintenance Infos

Mixture models in financial risk modeling


Krause, Lars Jochen. Mixture models in financial risk modeling. 2014, University of Zurich, Faculty of Economics.

Abstract

A new model class for univariate asset returns is proposed which involves the use of mixtures of stable Paretian distributions, and readily lends itself to use in a multivariate context for portfolio selection. The model nests numerous ones currently in use, and is shown to outperform all its special cases. In particular, an extensive out-of-sample risk forecasting exercise for seven major FX and equity indices confirms the superiority of the general model compared to its special cases and other competitors. An improved method (in terms of speed and accuracy) is developed for the computation of the stable Paretian density. Estimation issues related to problems associated with mixture models are discussed, and a new, general, method is proposed to successfully circumvent these. The model is straightforwardly extended to the multivariate setting by using an independent component analysis framework. The tractability of the relevant characteristic function then facilitates portfolio optimization using expected shortfall as the downside risk measure.

Abstract

A new model class for univariate asset returns is proposed which involves the use of mixtures of stable Paretian distributions, and readily lends itself to use in a multivariate context for portfolio selection. The model nests numerous ones currently in use, and is shown to outperform all its special cases. In particular, an extensive out-of-sample risk forecasting exercise for seven major FX and equity indices confirms the superiority of the general model compared to its special cases and other competitors. An improved method (in terms of speed and accuracy) is developed for the computation of the stable Paretian density. Estimation issues related to problems associated with mixture models are discussed, and a new, general, method is proposed to successfully circumvent these. The model is straightforwardly extended to the multivariate setting by using an independent component analysis framework. The tractability of the relevant characteristic function then facilitates portfolio optimization using expected shortfall as the downside risk measure.

Statistics

Downloads

23 downloads since deposited on 04 Apr 2019
22 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Dissertation (monographical)
Referees:Paolella Marc S, Farkas Erich W
Communities & Collections:UZH Dissertations
Dewey Decimal Classification:Unspecified
Language:English
Place of Publication:Zürich
Date:2014
Deposited On:04 Apr 2019 08:43
Last Modified:07 Apr 2020 07:17
Number of Pages:113
OA Status:Green
Related URLs:https://www.recherche-portal.ch/primo-explore/fulldisplay?docid=ebi01_prod010569438&context=L&vid=ZAD&search_scope=default_scope&tab=default_tab&lang=de_DE (Library Catalogue)

Download

Green Open Access

Download PDF  'Mixture models in financial risk modeling'.
Preview
Content: Published Version
Language: English
Filetype: PDF
Size: 3MB