Krzysztof Podgórski
Professor, Head of the Department of Statistics
A test for the global minimum variance portfolio for small sample and singular covariance
Author
Summary, in English
Recently, a test dealing with the linear hypothesis for the global minimum variance portfolio weights was obtained under the assumption of non-singular covariance matrix. However, the problem of potential multicollinearity and correlations of assets constitutes a limitation of the classical portfolio theory. Therefore, there is an interest in developing theory in the presence of singularities in the covariance matrix. In this paper, we extend the test by analyzing the portfolio weights in the small sample case with a singular population covariance matrix. The results are illustrated using actual stock returns and a discussion of practical relevance of the model is presented.
Department/s
- Department of Statistics
Publishing year
2017-07
Language
English
Pages
253-265
Publication/Series
AStA Advances in Statistical Analysis
Volume
101
Issue
3
Document type
Journal article
Publisher
Springer
Topic
- Probability Theory and Statistics
Keywords
- Global minimum variance portfolio
- Singular covariance matrix
- Singular Wishart distribution
- Small sample problem
Status
Published
ISBN/ISSN/Other
- ISSN: 1863-8171