Portfolio optimization based on GARCH-EVT-Copula forecasting models

Maziar Sahamkhadam, Andreas Stephan, Ralf Östermark

    Tutkimustuotos: LehtiartikkeliArtikkeliTieteellinenvertaisarvioitu

    51 Sitaatiot (Scopus)

    Abstrakti

    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.
    AlkuperäiskieliEi tiedossa
    Sivut497–506
    Sivumäärä10
    JulkaisuInternational Journal of Forecasting
    Vuosikerta34
    Numero3
    DOI - pysyväislinkit
    TilaJulkaistu - 2018
    OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

    Keywords

    • GARCH models
    • Extreme value theory
    • Copula models
    • Conditional value-at-risk
    • Portfolio optimization

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