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Efficient Subset Selection in Large-Scale Portfolio with Singular Covariance Matrix

机译:具有奇异协方差矩阵的大型投资组合中的有效子集选择

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In the classic mean-variance model, the covariance matrix is supposed to be positive definite or nonsingular. However, the degenerate portfolio can arise from multi-collinearity and correlation of assets returns in large-scale portfolio. In this paper, we investigate the issue of which assets can be removed from the original portfolio. We propose a new concept of efficient subset of portfolio for mean-variance optimizing investor. Applying the generalized inverse matrix, we derive some conditions for determining the efficient subset. In addition, a new three fund separation result is also obtained as an economic interpretation, which in fact gives an extension of the mean-variance spanning.
机译:在经典的均方差模型中,协方差矩阵应为正定或非奇异的。但是,退化的投资组合可能来自于大型投资组合中的多重共线性和资产收益的相关性。在本文中,我们研究了可以从原始投资组合中删除哪些资产的问题。我们为均值方差优化投资者提出了有效投资组合子集的新概念。应用广义逆矩阵,我们得出确定有效子集的一些条件。另外,还获得了新的三项资金分离结果作为一种经济解释,实际上是对均值-方差跨度的扩展。

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