99
Views
0
CrossRef citations to date
0
Altmetric
Research Article

A Monte Carlo synthetic sample based performance evaluation method for covariance matrix estimators

ORCID Icon &
 

ABSTRACT

The evaluation of covariance matrix estimators is very important for portfolio analysis and risk management. The Monte Carlo synthetic sample based performance evaluation method proposed by this article can avoid the main shortcomings of statistical and economic methods which are widely used in the existing literature. The proposed method does not need the true covariance and does not need to introduce the performance of the out-of-sample portfolios. It is an intuitive, effective and robust measure for both simulation and empirical analysis.

JEL CLASSIFICATION:

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 RMSEΣˆ,Σ=ΣˆΣ, where stands for the Frobenius norm of two matrices.

Additional information

Funding

This work was partially supported by the Chinese Natural Science Foundations [11631013, 11971372 and 11801433]

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.