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A new methodology for multi-period portfolio selection based on the risk measure of lower partial moments

机译:基于较低局部时刻风险尺寸的多时期产品组合选择的新方法

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摘要

This study aims to optimize the multi-period investment portfolio model with lower partial moments (LPM) as a measure of risk under transaction costs constraint. A new method is used to calculate the LPM model. The meta-heuristic algorithm Non-dominated Sorting Genetic Algorithm II is used to solve the multi-period optimization problem. To show efficiency of the proposed method some quantitative performance measures such as skewness, conditional Sharpe ratio, modified Sharpe ratio and Jensen measure are used. The results show that in comparison to the regular method of computing LPM, the proposed method works better and improves the efficiency of portfolio optimization, especially in terms of the processing time. (C) 2019 Published by Elsevier Ltd.
机译:本研究旨在优化具有较低部分时刻(LPM)的多时期投资组合模型作为交易成本限制的风险衡量标准。一种新方法用于计算LPM模型。 Meta-heuristic算法非主导的分类遗传算法II用于解决多周期优化问题。为了表明所提出的方法的效率,使用了一些定量性能测量,例如偏斜,条件锐利比,改性的夏普比和Jensen测量。结果表明,与计算LPM的常规方法相比,该方法的工作更好并提高了组合优化的效率,特别是在处理时间方面。 (c)2019年由elestvier有限公司发布

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