{"title":"Análise de propriedades das séries temporais dos ativos que compõem o índice IBOVESPA","authors":"César Daltóe Berci, Ceslo Pascoli Bottura","doi":"10.18226/23185279.v9iss2p05","DOIUrl":null,"url":null,"abstract":"Several characteristics of financial time series are of interest both from an academic point of view, which is intended to analyze the dynamics of the data and its numerical properties, as well as from investors point of view, who use this knowledge to generate profit in their financial transactions. By applying several analysis tools and using a massive computing capacity, the numerical and statistical properties of the assets that compose the IBOVESPA index were evaluated. Given the relevance and scope of the analyzed time series, the results obtained from this analysis can serve as a basis for the characterization of financial time series","PeriodicalId":21696,"journal":{"name":"Scientia cum Industria","volume":"88 1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientia cum Industria","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18226/23185279.v9iss2p05","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Several characteristics of financial time series are of interest both from an academic point of view, which is intended to analyze the dynamics of the data and its numerical properties, as well as from investors point of view, who use this knowledge to generate profit in their financial transactions. By applying several analysis tools and using a massive computing capacity, the numerical and statistical properties of the assets that compose the IBOVESPA index were evaluated. Given the relevance and scope of the analyzed time series, the results obtained from this analysis can serve as a basis for the characterization of financial time series