论文标题
欧盟投资组合在高维度上的统计推断
Statistical inference for the EU portfolio in high dimensions
论文作者
论文摘要
在本文中，使用基于收缩的投资组合权重的方法和随机矩阵理论的现代结果，我们构建了一个有效的程序，用于测试预期效用（EU）投资组合的效率，并讨论了在高维差异状态下提出的测试统计量的渐近行为，当时，当他们的$ p $ p $ par $ par $ par $ par $ par n y时，$ （0,1）$的正常数$ c \ in $ n \ to \ infty $。我们提供了一项广泛的模拟研究，其中分析了测试的功率函数和接收器操作特性曲线。在实证研究中，该方法应用于S \＆P 500成分的回报。
In this paper, using the shrinkage-based approach for portfolio weights and modern results from random matrix theory we construct an effective procedure for testing the efficiency of the expected utility (EU) portfolio and discuss the asymptotic behavior of the proposed test statistic under the high-dimensional asymptotic regime, namely when the number of assets $p$ increases at the same rate as the sample size $n$ such that their ratio $p/n$ approaches a positive constant $c\in(0,1)$ as $n\to\infty$. We provide an extensive simulation study where the power function and receiver operating characteristic curves of the test are analyzed. In the empirical study, the methodology is applied to the returns of S\&P 500 constituents.
