Statistical Inference for the Expected Utility Portfolio in High Dimensions

In this paper, using the shrinkage-based approach for portfolio weights and modern results from random matrix theory we construct an effective procedure for testing the efficiency of the expected utility (EU) portfolio and discuss the asymptotic behavior of the proposed test statistic under the high-dimensional asymptotic regime, namely when...

Tests for the Weights of the Global Minimum Variance Portfolio in a High-Dimensional Setting

In this paper, we construct two tests for the weights of the global minimum variance portfolio (GMVP) in a high-dimensional setting, namely, when the number of assets p depends on the sample size n such that p/n → c ϵ (0, 1) as n tends to infinity. In the case of a singular covariance matrix with rank equal to q we assume that q/n → c ϵ (0, 1...