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Enhancing Financial Portfolio Robustness with an Objective Based on ϵ-Neighborhoods

Abstract : Financial portfolio optimization is a challenging task. One of the major difficulties is managing the uncertainty arising from different aspects of the process. This paper suggests a solution based on ϵ-neighborhoods that, combined with a time-stamped resampling mechanism, increases the robustness of the solutions. The approach is tested on four of the most popular evolutionary multiobjective algorithms over a long period of time. This results in a significant enhancement in the reliability of the estimated efficient frontier.
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Francisco Luna, David Quintana, Sandra García, Pedro Isasi. Enhancing Financial Portfolio Robustness with an Objective Based on ϵ-Neighborhoods. International Journal of Information Technology and Decision Making, World Scientific Publishing, 2016, 15 (3), pp.479-515. ⟨10.1142/S0219622016500115⟩. ⟨cea-01849801⟩



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