4 papers
Clustering based on Stochastic Dominance with application for risk averters and risk seekers
Hua Li, Xue Jia, Yilin Kang +1
Stochastic Dominance (SD) theory provides a rigorous framework for selecting superior assets tailored to the asset allocation needs of investors with varying risk preferences (i.e.…
Spectrally-Corrected and Regularized QDA Classifier for Spiked Covariance Model
Wenya Luo, Hua Li, Zhidong Bai +1
Quadratic discriminant analysis (QDA) is a widely used method for classification problems, particularly preferable over Linear Discriminant Analysis (LDA) for heterogeneous data. H…
Spectrally-Corrected and Regularized Global Minimum Variance Portfolio for Spiked Model
Hua Li, Jiafu Huang
Considering the shortcomings of the traditional sample covariance matrix estimation, this paper proposes an improved global minimum variance portfolio model and named spectral corr…
Spectrally-Corrected and Regularized Linear Discriminant Analysis for Spiked Covariance Model
Hua Li, Wenya Luo, Zhidong Bai +2
This paper proposes an improved linear discriminant analysis called spectrally-corrected and regularized LDA (SRLDA). This method integrates the design ideas of the sample spectral…