High dimensional Global Minimum Variance Portfolio

Li, Hua and Bai, Zhi Dong and Wong, Wing Keung (2015): High dimensional Global Minimum Variance Portfolio.

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Global Minimum Variance Portfolio, Spectral Corrected Covariance, Sample Covariance
• Subjects: C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods

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