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Study of Portfolio Optimization Model Based on Design-Free Estimation

机译：基于无设计估计的投资组合优化模型研究

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With the continuous advancement of the financial field, Markowitz portfolio model has become more mature, and covariance matrix estimation stands out in the application of the portfolio model. The covariance matrix estimation deviation problem in the portfolio model has great influence on the optimal solution. In order to correct the deviation of the covariance matrix and reduce the influence of the dimension curse and time-varying problems on the results, in this paper, the Design -Free estimation method is applied for the first time in the portfolio optimization model. Specifically, the portfolio optimization model is built on the basis of Design-Free estimation. The advantage of Design-Free estimation method is that it has no limit condition for the sample randomness and the parameter structure of covariance matrix, and can ensure that the estimated covariance matrix is a non-singular matrix, which effectively improves the accuracy of estimation. The empirical results show that compared with the traditional model and the stochastic matrix M-P distribution estimation portfolio model, the portfolio model based on design-free estimation has higher return-risk ratio.
机译：随着金融领域的不断发展，Markowitz投资组合模型变得越来越成熟，协方差矩阵估计在投资组合模型的应用中脱颖而出。投资组合模型中的协方差矩阵估计偏差问题对最优解有很大影响。为了校正协方差矩阵的偏差并减少维数诅咒和时变问题对结果的影响，本文在组合优化模型中首次采用了无设计估计方法。具体而言，投资组合优化模型是建立在无设计估算的基础上的。 Free-Design估计方法的优点是对样本随机性和协方差矩阵的参数结构没有限制条件，并且可以确保估计的协方差矩阵为非奇异矩阵，从而有效地提高了估计的准确性。实证结果表明，与传统模型和随机矩阵M-P分布估计投资组合模型相比，基于无设计估计的投资组合模型具有更高的收益率。

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