Extended mean-variance model for reliable evolutionary portfolio optimization
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Real world optimization of financial portfolios pose a challenging multiobjective problem that can be tackled using Evolutionary Algorithms. The fact that the optimization process is subject to the presence of uncertainty concerning asset returns is likely to lead to unreliable solutions. This work suggests extending the classic mean-variance optimization problem with a third explicit robustness objective. This results on sets of portfolios that can be subsequently grouped together according to their reliability. This additional information allows for a better informed decision making regarding asset allocation. © 2014 - IOS Press and the authors. All rights reserved.
financial portfolio optimization; multiobjective evolutionary algorithms; robustness; evolutionary algorithms; financial data processing; investments; robustness (control systems); financial portfolio; informed decision; mean variance model; multi objective evolutionary algorithms; multi-objective problem; optimization problems; portfolio optimization; real-world optimization; multiobjective optimization