Abstract The purpose of this study is to find a portfolio that maximizes the risk-adjusted returns subject to constraints frequently faced during portfolio management by extending the classical Markowitz mean–variance portfolio optimization model. We propose a new two-step heuristic approach, GRASP & SOLVER, that evaluates the desirability of an asset by combining several properties about it into a single parameter. Using a real-life data set, we conduct a simulation study to compare our solution to a benchmark (S&P 500 index). We find that our method generates solutions satisfying nearly all of the constraints within reasonable computational time (under an hour), at the expense of a 13% reduction in the annual return of the portfolio, highlighting the effect of introducing these practice-based constraints.

中文翻译：

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经典均值-方差投资组合优化模型的扩展

摘要 本研究的目的是通过扩展经典的 Markowitz 均值-方差投资组合优化模型，找到一个投资组合，在投资组合管理过程中经常面临的约束条件下，最大化风险调整后的回报。我们提出了一种新的两步启发式方法 GRASP & SOLVER，它通过将资产的几个属性组合成一个参数来评估资产的合意性。我们使用真实数据集进行模拟研究，将我们的解决方案与基准（标准普尔 500 指数）进行比较。我们发现我们的方法在合理的计算时间内（不到一个小时）生成了满足几乎所有约束的解决方案，代价是投资组合的年回报率降低了 13%，突出了引入这些基于实践的约束的效果。