Portfolio optimization based on GARCH-EVT-Copula forecasting models |
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Authors: | Maziar Sahamkhadam Andreas Stephan Ralf Östermark |
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Institution: | 1. Linnaeus University, Växjö, Sweden;2. Jönköping International Business School, Jönköping, Sweden;3. Åbo Akademi, Turku, Finland |
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Abstract: | 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- 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- copulas, are best at reducing the portfolio risk. |
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Keywords: | GARCH models Extreme value theory Copula models Conditional value-at-risk Portfolio optimization |
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