受限最大缩减:快速稳健的投资组合优化方法

Albert Dorador
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引用次数: 0

摘要

我们提出了一种基于最大缩减的经典马科维茨二次投资组合优化模型的替代线性化方法。该模型最大限度地减少了投资组合的最大缩水,在金融困境时期(如 COVID-19 大流行期间)尤其具有吸引力。此外,我们还将介绍我们的新模型的混合整数线性规划变体,根据我们的样本外结果和敏感性分析,该变体提供了一个更有利、更稳健的解决方案,与标准的马科维茨二次方公式相比,求解时间缩短了 200 倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Constrained Max Drawdown: a Fast and Robust Portfolio Optimization Approach
We propose an alternative linearization to the classical Markowitz quadratic portfolio optimization model, based on maximum drawdown. This model, which minimizes maximum portfolio drawdown, is particularly appealing during times of financial distress, like during the COVID-19 pandemic. In addition, we will present a Mixed-Integer Linear Programming variation of our new model that, based on our out-of-sample results and sensitivity analysis, delivers a more profitable and robust solution with a 200 times faster solving time compared to the standard Markowitz quadratic formulation.
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