<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The covariance matrix is an important element of many asset allocation strategies. The widely used sample covariance matrix estimator is unstable especially when the number of time observations is small and the number of assets is large or when high-dimensional data is involved in the computation. In this study, we focus on the most important estimators that are applied on a group of Markowitz-type strategies and also on a recently introduced method based on hierarchical tree clustering. The performance tests of the portfolio strategies using different covariance matrix estimators rely on the out-of-sample characteristics of synthetic and real stock data.</p>
</abstract>

The covariance matrix is an important element of many asset allocation strategies. The widely used sample covariance matrix estimator is unstable especially when the number of time observations is small and the number of assets is large or when high-dimensional data is involved in the computation. In this study, we focus on the most important estimators that are applied on a group of Markowitz-type strategies and also on a recently introduced method based on hierarchical tree clustering. The performance tests of the portfolio strategies using different covariance matrix estimators rely on the out-of-sample characteristics of synthetic and real stock data.

Asset Allocation Strategies Using Covariance Matrix Estimators

Sapientia Hungarian University of Transylvania

Acta Universitatis Sapientiae, Economics and Business

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Asset Allocation Strategies Using Covariance Matrix Estimators"}

The covariance matrix is an important element of many asset allocation strategies. The widely used sample covariance matrix estimator is unstable especially...

Asset Allocation Strategies Using Covariance Matrix Estimators

Publié en ligne: 13 oct. 2022

Pages: 133 - 144

DOI: https://doi.org/10.2478/auseb-2022-0008

Mots clés
portfolio optimization, covariance matrix estimators

© 2022 László PáL, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Asset Allocation Strategies Using Covariance Matrix Estimators

Publié en ligne: 13 oct. 2022

Pages: 133 - 144

DOI: https://doi.org/10.2478/auseb-2022-0008

Mots clésportfolio optimization, covariance matrix estimators

© 2022 László PáL, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
portfolio optimization, covariance matrix estimators