{"title":"Robust high-dimensional alpha test for conditional time-varying factor models","authors":"Ping Zhao","doi":"10.1080/02331888.2023.2180003","DOIUrl":null,"url":null,"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.","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"255 1","pages":"444 - 457"},"PeriodicalIF":1.2000,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/02331888.2023.2180003","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
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.
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.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
