activity
20232026
collaborators
Showing stat.MEShow all

9 papers · 1 filter

stat.ME2026

Rank-Based Tests for Mutual Independence of High-Dimensional Random Vectors via Norm

Ping Zhao, Hongfei Wang, Long Feng

We consider the problem of testing mutual independence among the components of a high-dimensional random vector. Building on the rank-based max-sum framework, we introduce fixed fi…

stat.ME2026

High-Dimensional Two-Sample Test for Elliptical Symmetry Distribution

Long Feng, Hongfei Wang

We study the high-dimensional two-sample location problem under elliptical symmetry with arbitrary dependence in the scatter matrix. Existing spatial-sign procedures are attractive…

stat.ME2026

Robust Spatial-Sign-Based Testing of High-Dimensional Alpha in Conditional Factor Models

Ping Zhao, Hongfei Wang

This paper develops a new framework for alpha testing in high-dimensional factor pricing models with time-varying coefficients. To detect sparse alternatives, we propose a spatial-…

stat.ME2025

High dimensional matrix estimation through elliptical factor models

Xinyue Xu, Huifang Ma, Hongfei Wang +1

Elliptical factor models play a central role in modern high-dimensional data analysis, particularly due to their ability to capture heavy-tailed and heterogeneous dependence struct…

stat.ME2024

Robust Mutual Fund Selection with False Discovery Rate Control

Hongfei Wang, Long Feng, Ping Zhao +1

In this article, we address the challenge of identifying skilled mutual funds among a large pool of candidates, utilizing the linear factor pricing model. Assuming observable facto…

stat.ME2024

Double Robust high dimensional alpha test for linear factor pricing model

Ping Zhao, Long Feng, Hongfei Wang +1

In this paper, we investigate alpha testing for high-dimensional linear factor pricing models. We propose a spatial sign-based max-type test to handle sparse alternative cases. Add…