{"title":"用GARCH模型对标准普尔500指数的回报进行建模","authors":"Rodrigo Alfaro, Alejandra Inzunza","doi":"10.1016/j.latcb.2023.100096","DOIUrl":null,"url":null,"abstract":"<div><p>This paper provides several estimates of the GARCH models’ parameters for the S&P500 index, based on returns and CBOE VIX. Using a daily sample collected from 2007 to 2022, we can conclude that adding the VIX information improves the estimates of the long-term volatility. By providing an external validation of the model using an option-based index reported by the Federal Reserve of Minneapolis, we are able to propose a calibrate model to track the tail-risk of this stock index.</p></div>","PeriodicalId":100867,"journal":{"name":"Latin American Journal of Central Banking","volume":"4 3","pages":"Article 100096"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling S&P500 returns with GARCH models\",\"authors\":\"Rodrigo Alfaro, Alejandra Inzunza\",\"doi\":\"10.1016/j.latcb.2023.100096\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper provides several estimates of the GARCH models’ parameters for the S&P500 index, based on returns and CBOE VIX. Using a daily sample collected from 2007 to 2022, we can conclude that adding the VIX information improves the estimates of the long-term volatility. By providing an external validation of the model using an option-based index reported by the Federal Reserve of Minneapolis, we are able to propose a calibrate model to track the tail-risk of this stock index.</p></div>\",\"PeriodicalId\":100867,\"journal\":{\"name\":\"Latin American Journal of Central Banking\",\"volume\":\"4 3\",\"pages\":\"Article 100096\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Latin American Journal of Central Banking\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666143823000170\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Latin American Journal of Central Banking","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666143823000170","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper provides several estimates of the GARCH models’ parameters for the S&P500 index, based on returns and CBOE VIX. Using a daily sample collected from 2007 to 2022, we can conclude that adding the VIX information improves the estimates of the long-term volatility. By providing an external validation of the model using an option-based index reported by the Federal Reserve of Minneapolis, we are able to propose a calibrate model to track the tail-risk of this stock index.
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