Robust high-dimensional alpha test for conditional time-varying factor models

IF 1.2 4区数学 Q2 STATISTICS & PROBABILITY

Statistics Pub Date : 2023-02-23 DOI:10.1080/02331888.2023.2180003

Ping Zhao

引用次数: 2

Abstract

This paper considers the problem of testing the presence of alpha in high-dimensional conditional time-varying factor model. We proposed a spatial-sign-based test procedure which is robust and efficient for heavy-tailed distributions. We established the theoretical properties of the proposed test statistic under some mild conditions. Simulation studies and a real data example also show the superior of our test procedure to the existing methods.

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条件时变因子模型的稳健高维alpha检验

研究了高维条件时变因子模型中α的存在性检验问题。我们提出了一种基于空间符号的测试方法，该方法对重尾分布具有鲁棒性和有效性。我们在一些温和的条件下建立了所提出的检验统计量的理论性质。仿真研究和一个实际数据算例也表明了我们的测试方法比现有方法的优越性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Statistics 数学-统计学与概率论

CiteScore

1.00

自引率

0.00%

发文量

审稿时长

12 months

期刊介绍： Statistics publishes papers developing and analysing new methods for any active field of statistics, motivated by real-life problems. Papers submitted for consideration should provide interesting and novel contributions to statistical theory and its applications with rigorous mathematical results and proofs. Moreover, numerical simulations and application to real data sets can improve the quality of papers, and should be included where appropriate. Statistics does not publish papers which represent mere application of existing procedures to case studies, and papers are required to contain methodological or theoretical innovation. Topics of interest include, for example, nonparametric statistics, time series, analysis of topological or functional data. Furthermore the journal also welcomes submissions in the field of theoretical econometrics and its links to mathematical statistics.