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A linear test for the global minimum variance portfolio for small sample and singular covariance

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Author

Summary, in English

Bodnar and Schmid (2008) derived the distribution of the global minimum variance portfolio weights and obtained the distribution of the test statistics for the general linear hypothesis. Their results are obtained in the case when the number of observations n is bigger or equal than the size of portfolio k. In the present paper, we extend the result by analyzing the portfolio weights in a small sample case of

n < k, with the singular covariance matrix. The results are illustrated using actual stock returns. A discussion of practical relevance of the model is presented.

Publishing year

2015

Language

English

Publication/Series

Working Papers in Statistics

Issue

10

Document type

Working paper

Publisher

Department of Statistics, Lund university

Topic

  • Other Natural Sciences not elsewhere specified

Keywords

  • singular co-variance matrix
  • singular Wishart distribution
  • small sample problem
  • global minimum variance portfolio

Status

Published