ENHANCEMENT OF THE APPLICABILITY OF MARKOWITZ'S PORTFOLIO OPTIMIZATION BY UTILIZING RANDOM MATRIX THEORY

189 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Large Sample Covariance Matrices and High-Dimensional Data Analysis (2015, background): “The second direction, following the work of Bai et al. (2009a), is to make systematic corrections to the classical multivariate statistical procedures so that the effect of large dimension is overcome.”
High-dimensionality effects in the Markowitz problem and other quadratic programs with linear constraints: Risk underestimation (2010, methodology): “We refer the interested reader to Johnstone (2001), El Karoui (2007, 2008, 2009a), Bickel and Levina (2008a), Rothman et al. (2008) for a partial introduction to these problems. We wish with this study to make clear that the “large n, large p” character of the problem has an important impact of the ”
Market efficiency of oil spot and futures: A mean-variance and stochastic dominance approach (2010, unknown): “In this situation, they could make huge profits by setting up zero-dollar portfolios to exploit this opportunity (Bai et al., 2009b). On the other hand, if FSD does not exist between X and Y , one could conclude that both markets display market efficiency and market rationality (Bernard and Seyhun, ”