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20242026
most citedTesting Alpha in High Dimensional Linear Factor Pricing Models with Dependent Observations

1 citations · 1 across the 8 of their papers we have counts for

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stat.ME2026

Sparse -spatial-median clustering for high-dimensional data

Ping Zhao, Dan Zhuang, Long Feng

We propose a robust clustering framework for high-dimensional data with heavy tails and a large fraction of irrelevant variables. The method replaces the mean updates of Lloyd's $K…

stat.ME2026

High dimensional alpha test for linear factor pricing model with -norm

Ping Zhao, Huifang Ma, Long Feng

We consider testing zero pricing errors in high-dimensional linear factor pricing models. Existing methods are mainly based on either an statistic, which is effective under d…

stat.ME2026

Note on High Dimensional Spatial-Sign Test for One Sample Problem

Ping Zhao, Long Feng

We revisit the null distribution of the high-dimensional spatial-sign test of Wang et al. (2015) under mild structural assumptions on the scatter matrix. We show that the standardi…

stat.ME2025

Inverse Norm Weighted Maxsum Test for High Dimensional Location Parameters

Guowei Yan, Ping Zhao, Long Feng

In the context of high-dimensional data, we investigate the one-sample location testing problem. We introduce a max-type test based on the weighted spatial sign, which exhibits exc…

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

Adaptive Sphericity Tests for High Dimensional Data

Ping Zhao, Wenwan Yang, Long Feng +1

In this paper, we investigate sphericity testing in high-dimensional settings, where existing methods primarily rely on sum-type test procedures that often underperform under spars…