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Multivariate location-scale mixtures of normals and mean-variance-skewness portfolio allocation

机译:法线和均值-方差-偏度投资组合分配的多元位置尺度混合

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摘要

We show that the distribution of any portfolio whose components jointly follow a location-scale mixture of normals can be characterised solely by its mean, variance and skewness. Under this distributional assumption, we derive the mean-variance-skewness frontier in closed form, and show that it can be spanned by three funds. For practical purposes, we derive a standardised distribution, provide analytical expressions for the log-likelihood score and explain how to evaluate the information matrix. Finally, we present an empirical application in which we obtain the mean-variance-skewness frontier generated by the ten Datastream US sectoral indices, and conduct spanning tests.
机译:我们表明,其成分共同遵循位置尺度的法线混合的任何投资组合的分布都可以仅通过均值,方差和偏度来表征。在这种分布假设下,我们得出封闭形式的均值方差偏度边界,并表明它可以被三只基金跨越。出于实际目的,我们得出标准分布,提供对数似然得分的分析表达式,并解释如何评估信息矩阵。最后,我们提出了一个经验应用程序,其中我们获得了由十个Datastream美国部门指数生成的均值方差偏度边界,并进行了跨度测试。

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