Pacific-Basin Finance Journal ? June 2018 ? Volume 49, Pages 213-231

一种更好投资组合的新方法：以韩国股市为例

作者：Cheoljun Eom (School of Business, Pusan National University, Republic of Korea),

Jong Won Park (College of Business Administration, University of Seoul, Republic of Korea)

摘要：本文提出了一种利用马尔可维茨均值方差优化函数（MVOF）来估计一个能够很好地构造多样化投资组合的相关矩阵的方法，并通过实证证明，该方法有效地降低了因投资组合输入变量误差引起的投资组合结果的敏感性，例如投资组合中股票的平均值和标准差。该方法通过随机矩阵理论去除了样本相关矩阵中包含的市场因子的性质。结果表明，该方法能有效地降低平均偏差和标准偏差对估计误差和预测误差的敏感性。特别是，这种比较优势依赖于通过构建良好多元化的投资组合，而获得的投资组合风险的显著降低。所提出的方法在风险收益领域也能取得较高的投资绩效，在市场崩溃或高风险投资组合的不稳定情况下尤其有效。因此，这项研究为如何通过控制样本相关矩阵中市场因素的性质来提高MVOF的实际适用性提供了新的见解。

关键词：均值-方差组合优化；相关矩阵；随机矩阵理论；非市场相关矩阵；敏感性检验；仿真实验

A new method for better portfolio investment: A case of the Korean stock market

Cheoljun Eom (School of Business, Pusan National University, Republic of Korea), Jong Won Park (College of Business Administration, University of Seoul, Republic of Korea)

ABSTRACT

In this study, a method is devised to estimate a correlation matrix capable of constructing a well-diversified portfolio by the Markowitz mean-variance (MV) optimization function (MVOF), after which evidence is presented to empirically prove that the proposed method effectively reduces the sensitivity of portfolio output caused by the error of input variables, such as the mean and standard deviation of stocks in a portfolio. The proposed method removes the property of a market factor included in the sample correlation matrix through random matrix theory. The results demonstrate the comparative advantage of the proposed method in effectively reducing the sensitivity on both the estimation error and the prediction error from the mean and standard deviation. In particular, this comparative advantage is dependent on the striking reduction of portfolio risk gained by constructing the well-diversified portfolio. The proposed method also achieves high investment performance in the risk-return domain, and is particularly stronger in the unstable situation of either a market crash or a higher-risk portfolio. Consequently, this study offers new insight into how to enhance the practical applicability of the MVOF by controlling the property of the market factor in the sample correlation matrix.

Keywords: Mean-variance portfolio optimization; Correlation matrix; Random matrix theory; Non-market correlation matrix; Sensitivity test; Simulation experiment

原文链接：

https://www.sciencedirect.com/science/article/pii/S0927538X17301257#!

翻译：施懿