Diego Nascimento, C. Xavier, I. Felipe, F. L. Neto
{"title":"动态条件相关GARCH：一种基于贝叶斯方法的多变量时间序列新方法","authors":"Diego Nascimento, C. Xavier, I. Felipe, F. L. Neto","doi":"10.22237/jmasm/1556669220","DOIUrl":null,"url":null,"abstract":"The Dynamic Conditional Correlation GARCH (DCC-GARCH) mutation model is considered using a Monte Carlo approach via Markov chains in the estimation of parameters, time-dependence variation is visually demonstrated. Fifteen indices were analyzed from the main financial markets of developed and developing countries from different continents. The performances of indices are similar, with a joint evolution. Most index returns, especially SPX and NDX, evolve over time with a higher positive correlation.","PeriodicalId":47201,"journal":{"name":"Journal of Modern Applied Statistical Methods","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Dynamic Conditional Correlation GARCH: A Multivariate Time Series Novel using a Bayesian Approach\",\"authors\":\"Diego Nascimento, C. Xavier, I. Felipe, F. L. Neto\",\"doi\":\"10.22237/jmasm/1556669220\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Dynamic Conditional Correlation GARCH (DCC-GARCH) mutation model is considered using a Monte Carlo approach via Markov chains in the estimation of parameters, time-dependence variation is visually demonstrated. Fifteen indices were analyzed from the main financial markets of developed and developing countries from different continents. The performances of indices are similar, with a joint evolution. Most index returns, especially SPX and NDX, evolve over time with a higher positive correlation.\",\"PeriodicalId\":47201,\"journal\":{\"name\":\"Journal of Modern Applied Statistical Methods\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Modern Applied Statistical Methods\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22237/jmasm/1556669220\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Modern Applied Statistical Methods","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22237/jmasm/1556669220","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
Dynamic Conditional Correlation GARCH: A Multivariate Time Series Novel using a Bayesian Approach
The Dynamic Conditional Correlation GARCH (DCC-GARCH) mutation model is considered using a Monte Carlo approach via Markov chains in the estimation of parameters, time-dependence variation is visually demonstrated. Fifteen indices were analyzed from the main financial markets of developed and developing countries from different continents. The performances of indices are similar, with a joint evolution. Most index returns, especially SPX and NDX, evolve over time with a higher positive correlation.
期刊介绍：
The Journal of Modern Applied Statistical Methods is an independent, peer-reviewed, open access journal designed to provide an outlet for the scholarly works of applied nonparametric or parametric statisticians, data analysts, researchers, classical or modern psychometricians, and quantitative or qualitative methodologists/evaluators.
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