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PERFORMANCE EVALUATION OF PORTFOLIOS WITH FUZZY RETURNS

机译:带有模糊收益的投资组合的绩效评估

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摘要

The existing literature on DEA (Data Envelopment Analysis) for evaluating fuzzy portfolios usually takes risk as an input and return as an output. This assumption is actually not congruent with the real investment process, where the input is the initial wealth and the output is the corresponding terminal wealth. As for the risk and return, which are essentially two indicators derived from the terminal wealth, both should be regarded as outputs. In addition, few studies have employed the diversification model (nonlinear DEA) to estimate the fuzzy portfolio efficiency (PE), despite the fact that there are many studies available within the framework of classical probability theory. Further, the relationship between DEA and diversification models needs to be defined. In this paper, we take the initial wealth as an input, while the return and risk of terminal wealth are taken as desirable and undesirable outputs, respectively. We construct different evaluation models under the fuzzy portfolio framework. The relationships among the evaluation model based on a real frontier, the diversification model and the DEA model are investigated. We show the convergence of the diversification and DEA models under the fuzzy theory framework. Some simulations as well as empirical analysis are presented to further verify the effectiveness of the proposed models. Finally, we check the robustness of the evaluation results by using the bootstrap re-sampling approach.
机译:现有用于评估模糊投资组合的DEA(数据包络分析)文献通常将风险作为输入,将收益作为输出。该假设实际上与实际投资过程不一致,在实际投资过程中,输入是初始财富,而输出是相应的最终财富。至于风险和收益,它们本质上是来自终端财富的两个指标,都应视为产出。此外,尽管在经典概率论的框架内有许多研究可用,但很少有研究采用多元化模型(非线性DEA)来估计模糊投资组合效率(PE)。此外,需要定义DEA与多元化模型之间的关系。在本文中,我们将初始财富作为输入,而终端财富的收益和风险分别作为期望和不期望的产出。我们在模糊投资组合框架下构建了不同的评估模型。研究了基于真实边界的评估模型,多元化模型和DEA模型之间的关系。我们展示了在模糊理论框架下多元化和DEA模型的收敛性。提出了一些模拟以及经验分析,以进一步验证所提出模型的有效性。最后,我们使用引导重采样方法检查评估结果的鲁棒性。

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