{"title":"GARCH模型、重尾与中国股市收益","authors":"Michael Day, Mark Diamond","doi":"10.2139/ssrn.3018940","DOIUrl":null,"url":null,"abstract":"The Chinese stock market is unique in which it is moved more by individual retail investors than institutional investors. Therefore, for economic and political stability it is more important to efficiently manage the risk of the Chinese stock market. We investigate its volatility dynamics through the GARCH model with three types of heavy-tailed distributions, the Student’s t, the NIG and the NRIG distributions. Our results show that estimated parameters for all the three types of distributions are statistical significant and the NIG distribution has the best empirical performance in fitting the Chinese stock market index returns.","PeriodicalId":108284,"journal":{"name":"Econometric Modeling: International Financial Markets - Emerging Markets eJournal","volume":"324 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GARCH Model, Heavy Tails and the Chinese Stock Market Returns\",\"authors\":\"Michael Day, Mark Diamond\",\"doi\":\"10.2139/ssrn.3018940\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Chinese stock market is unique in which it is moved more by individual retail investors than institutional investors. Therefore, for economic and political stability it is more important to efficiently manage the risk of the Chinese stock market. We investigate its volatility dynamics through the GARCH model with three types of heavy-tailed distributions, the Student’s t, the NIG and the NRIG distributions. Our results show that estimated parameters for all the three types of distributions are statistical significant and the NIG distribution has the best empirical performance in fitting the Chinese stock market index returns.\",\"PeriodicalId\":108284,\"journal\":{\"name\":\"Econometric Modeling: International Financial Markets - Emerging Markets eJournal\",\"volume\":\"324 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Econometric Modeling: International Financial Markets - Emerging Markets eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3018940\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometric Modeling: International Financial Markets - Emerging Markets eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3018940","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GARCH Model, Heavy Tails and the Chinese Stock Market Returns
The Chinese stock market is unique in which it is moved more by individual retail investors than institutional investors. Therefore, for economic and political stability it is more important to efficiently manage the risk of the Chinese stock market. We investigate its volatility dynamics through the GARCH model with three types of heavy-tailed distributions, the Student’s t, the NIG and the NRIG distributions. Our results show that estimated parameters for all the three types of distributions are statistical significant and the NIG distribution has the best empirical performance in fitting the Chinese stock market index returns.