10 papers · 1 filter
Cauchy-Aggregated Ridge Tests for High-Dimensional Factor Pricing Models
Ping Zhao, Dan Zhuang
In high-dimensional factor pricing models, the power of regularized alpha tests depends on the ridge parameter, whose optimal value varies with the unknown direction of pricing err…
Cauchy-Combined Hettmansperger-Randles Location Tests in High Dimensions
Ping Zhao, Long Feng, Xiaoyi Wang
High-dimensional mean testing is challenging under strong dependence and heavy tails, since classical Hotelling statistics are ill posed and regularized versions based on sample mo…
Adaptive Ridge-Regularized Hotelling Change-Point Tests for Functional Data
Ping Zhao, Long Feng
We propose a unified ridge-regularized Hotelling framework for detecting and locating mean changes in functional time series. A growing basis expansion converts the functional obse…
Cauchy Aggregation of Ridge-Regularized Hotelling Tests for High-Dimensional Change-Point Detection
Ping Zhao, Le Zhou, Long Feng
Ridge-regularized Hotelling-type (RHT) change-point tests depend on a ridge parameter , but the power-optimal value is determined by the unknown covariance structure and the unk…
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…
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…
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-…
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…
Rank-based Maxsum test for high dimensional regression coefficient
Ping Zhao, Liangliang Yuan
We study global inference for regression coefficients in high-dimensional linear models under potentially heavy-tailed errors. While sum-type tests are powerful for dense alternati…
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…