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Portfolio optimization based on the process of estimating the covariance matrix is one of the new approaches. In this article, the author has conducted an analysis and evaluation of various covariance matrix estimators to measure their effectiveness in investment activities. The results of the empirical study on over 400 listed stocks on the Vietnamese stock market from January 2011 to January 2024 have shown that the covariance matrix estimator with balanced shrinkage weight yields significantly superior results across all three portfolio performance metrics: Sharpe ratio, Sortino ratio, and Calmar ratio, compared to the other seven estimators divided into three groups including the LW Shrinkage method group, the factor model group, and the traditional method group. The study’s findings also aim to further encourage investors to expand research on covariance matrix estimation in selecting optimal investment portfolios.
Nguyễn et al. (Sat,) studied this question.