lnu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Portfolio optimization based on GARCH-EVT-Copula forecasting models
Linnaeus University, School of Business and Economics, Department of Management Accounting and Logistics.
Linnaeus University, School of Business and Economics, Department of Management Accounting and Logistics. Jönköping university.
Åbo Akad Univ, Finland.
2018 (English)In: International Journal of Forecasting, ISSN 0169-2070, E-ISSN 1872-8200, Vol. 34, no 3, p. 497-506Article in journal (Refereed) Published
Abstract [en]

This study uses GARCH-EVT-copula and ARMA-GARCH-EVT-copula models to perform out-of-sample forecasts and simulate one-day-ahead returns for ten stock indexes. We construct optimal portfolios based on the global minimum variance (GMV), minimum conditional value-at-risk (Min-CVaR) and certainty equivalence tangency (CET) criteria, and model the dependence structure between stock market returns by employing elliptical (Student-t and Gaussian) and Archimedean (Clayton, Frank and Gumbel) copulas. We analyze the performances of 288 risk modeling portfolio strategies using out-of-sample back-testing. Our main finding is that the CET portfolio, based on ARMA-GARCH-EVT-copula forecasts, outperforms the benchmark portfolio based on historical returns. The regression analyses show that GARCH-EVT forecasting models, which use Gaussian or Student-t copulas, are best at reducing the portfolio risk. (C) 2018 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 34, no 3, p. 497-506
Keywords [en]
GARCH models, Extreme value theory, Copula models, Conditional value-at-risk, Portfolio optimization
National Category
Economics and Business
Research subject
Economy
Identifiers
URN: urn:nbn:se:lnu:diva-79013DOI: 10.1016/j.ijforecast.2018.02.004ISI: 000449722000008Scopus ID: 2-s2.0-85046680082OAI: oai:DiVA.org:lnu-79013DiVA, id: diva2:1268532
Available from: 2018-12-06 Created: 2018-12-06 Last updated: 2019-08-29Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Sahamkhadam, MaziarStephan, Andreas

Search in DiVA

By author/editor
Sahamkhadam, MaziarStephan, Andreas
By organisation
Department of Management Accounting and Logistics
In the same journal
International Journal of Forecasting
Economics and Business

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 58 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf