High dimensional Global Minimum Variance Portfolio

Hua Li, Zhi Dong Bai and Wing-Keung Wong

MPRA Paper from University Library of Munich, Germany

Abstract: This paper proposes the spectral corrected methodology to estimate the Global Minimum Variance Portfolio (GMVP) for the high dimensional data. In this paper, we analysis the limiting properties of the spectral corrected GMVP estimator as the dimension and the number of the sample set increase to infinity proportionally. In addition, we compare the spectral corrected estimation with the linear shrinkage and nonlinear shrinkage estimations and obtain that the performance of the spectral corrected methodology is best in the simulation study.

Keywords: Global Minimum Variance Portfolio; Spectral Corrected Covariance; Sample Covariance (search for similar items in EconPapers)
JEL-codes: C02 (search for similar items in EconPapers)
Date: 2015-08-26
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:66284

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