Robust multiobjective portfolio optimization: A minimax regret approach
Robust multiobjective portfolio optimization: A minimax regret approach
复制标题
DOI：
10.1016/j.ejor.2017.03.041
复制
发表时间：
2017-10
期刊：
影响因子：
--
通讯作者：
Panagiotis Xidonas;G. Mavrotas;C. Hassapis;C. Zopounidis
中科院分区：
文献类型：
--
作者：
Panagiotis Xidonas;G. Mavrotas;C. Hassapis;C. Zopounidis
典型投资组合选择问题中的有效边界提供了一种表达回报和风险之间权衡的说明性方法。遵循马科维茨引入的现代投资组合理论的基本思想，证券回报通常是从过去的数据中提取的。我们本文的目的是将未来回报情景纳入投资决策过程。对于有效边界上的代表点，基于上述场景计算最小最大遗憾组合。这些点对应于特定的重量组合。通过这种方式，可以识别出比其他区域更稳健的有效前沿区域。潜在的关键贡献与多目标规划问题中传统的最小最大遗憾准则公式的扩展有关。该方法的有效性通过 Eurostoxx 50 的说明性实证测试应用得到验证。
An efficient frontier in the typical portfolio selection problem provides an illustrative way to express the tradeoffs between return and risk. Following the basic ideas of modern portfolio theory as introduced by Markowitz, security returns are usually extracted from past data. Our purpose in this paper is to incorporate future returns scenarios in the investment decision process. For representative points on the efficient frontier, the minimax regret portfolio is calculated, on the basis of the aforementioned scenarios. These points correspond to specific weight combinations. In this way, the areas of the efficient frontier that are more robust than others are identified. The underlying key-contribution is related to the extension of the conventional minimax regret criterion formulation, in multiobjective programming problems. The validity of the approach is verified through an illustrative empirical testing application on the Eurostoxx 50.