{"title":"用偏态Student- T分布的指数Garch模型估计股票市场波动","authors":"Syamraj Kp, Regina Sibi Cleetus","doi":"10.59640/cbr.v14i2.98-104","DOIUrl":null,"url":null,"abstract":"The aim of the study is to empirically investigate the performance of the EGARCH (1, 1) volatility model with the normal, skew-normal, and student t and skewed student t distributions on the NSE Nifty Fifty Index. Ten years of daily closing rates over the period of January 2010 to December 2020, for a total of 2730 observations, have been analyzed. According to the information criterion, this study has found that the EGARCH (1, 1) model under skewed student t distribution is a better fit than other distribution models.","PeriodicalId":426677,"journal":{"name":"Commerce & Business Researcher","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimating Stock Market Volatility Using Exponential Garch Model with Skewed Student- T Distribution\",\"authors\":\"Syamraj Kp, Regina Sibi Cleetus\",\"doi\":\"10.59640/cbr.v14i2.98-104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of the study is to empirically investigate the performance of the EGARCH (1, 1) volatility model with the normal, skew-normal, and student t and skewed student t distributions on the NSE Nifty Fifty Index. Ten years of daily closing rates over the period of January 2010 to December 2020, for a total of 2730 observations, have been analyzed. According to the information criterion, this study has found that the EGARCH (1, 1) model under skewed student t distribution is a better fit than other distribution models.\",\"PeriodicalId\":426677,\"journal\":{\"name\":\"Commerce & Business Researcher\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Commerce & Business Researcher\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.59640/cbr.v14i2.98-104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Commerce & Business Researcher","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59640/cbr.v14i2.98-104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimating Stock Market Volatility Using Exponential Garch Model with Skewed Student- T Distribution
The aim of the study is to empirically investigate the performance of the EGARCH (1, 1) volatility model with the normal, skew-normal, and student t and skewed student t distributions on the NSE Nifty Fifty Index. Ten years of daily closing rates over the period of January 2010 to December 2020, for a total of 2730 observations, have been analyzed. According to the information criterion, this study has found that the EGARCH (1, 1) model under skewed student t distribution is a better fit than other distribution models.
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