The mainstream in finance tackles portfolio selection based on a plug-in approach without consideration of the main objective of the inferential situation. We propose minimum expected loss (MELO) estimators for portfolio selection that explicitly consider the trading rule of interest. The asymptotic properties of our MELO proposal are similar to the plug-in approach. Nevertheless, simulation exercises show that our proposal exhibits better finite sample properties when compared to the competing alternatives, especially when the tangency portfolio is taken as the asset allocation strategy. We have also developed a graphical user interface to help practitioners to use our MELO proposal.

中文翻译：

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最佳投资组合选择：最小预期损失法

金融界的主流是基于插件方法来选择投资组合，而不考虑推论情况的主要目标。我们为投资组合选择建议了最小预期损失（MELO）估计量，该估计量明确考虑了感兴趣的交易规则。我们的MELO提议的渐近性质类似于插件方法。尽管如此，仿真实验表明，与竞争性替代方案相比，我们的建议显示出更好的有限样本属性，尤其是在将相切组合作为资产分配策略时。我们还开发了图形用户界面，以帮助从业人员使用我们的MELO建议。