{"title":"The Finite-Sample Size of the BDS Test for GARCH Standardized Residuals","authors":"Marcelo Fernandes, P. Preumont","doi":"10.12660/BRE.V32N22012.18608","DOIUrl":null,"url":null,"abstract":"This paper uses a multivariate response surface methodology to analyze the size distortion of the BDS test when applied to standardized residuals of rst-order GARCH processes. The results show that the asymptotic standard normal distribution is an unreliable approximation even in large samples. On the other hand, a simple log-transformation of the squared standardized residuals seems to correct most of the size problems. The estimated response surfaces can nonetheless provide not only a measure of the size distortion, but also more adequate critical values for theBDS test in small samples.","PeriodicalId":332423,"journal":{"name":"Brazilian Review of Econometrics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brazilian Review of Econometrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12660/BRE.V32N22012.18608","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper uses a multivariate response surface methodology to analyze the size distortion of the BDS test when applied to standardized residuals of rst-order GARCH processes. The results show that the asymptotic standard normal distribution is an unreliable approximation even in large samples. On the other hand, a simple log-transformation of the squared standardized residuals seems to correct most of the size problems. The estimated response surfaces can nonetheless provide not only a measure of the size distortion, but also more adequate critical values for theBDS test in small samples.