{"title":"基于copula的单变量时间序列结构位移识别检验","authors":"H. Penikas","doi":"10.2139/SSRN.2196716","DOIUrl":null,"url":null,"abstract":"An approach is proposed to determine structural shift in time-series assuming non-linear dependence of lagged values of dependent variable. Copulas are used to model non-linear dependence of time series components.","PeriodicalId":250928,"journal":{"name":"arXiv: General Finance","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Copula-Based Univariate Time Series Structural Shift Identification Test\",\"authors\":\"H. Penikas\",\"doi\":\"10.2139/SSRN.2196716\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An approach is proposed to determine structural shift in time-series assuming non-linear dependence of lagged values of dependent variable. Copulas are used to model non-linear dependence of time series components.\",\"PeriodicalId\":250928,\"journal\":{\"name\":\"arXiv: General Finance\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv: General Finance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/SSRN.2196716\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv: General Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/SSRN.2196716","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Copula-Based Univariate Time Series Structural Shift Identification Test
An approach is proposed to determine structural shift in time-series assuming non-linear dependence of lagged values of dependent variable. Copulas are used to model non-linear dependence of time series components.
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