{"title":"预测加密货币:GARCH模型的比较","authors":"Giovanni Angelini, S. Emili","doi":"10.2139/ssrn.3195704","DOIUrl":null,"url":null,"abstract":"In this paper we enhance the literature exploring the forecasting capability of six alternatives GARCH-type models to predict volatility of four of the most traded cryptocurrencies: Bitcoin, Ethereum, Ripple and Litecoin. The analysis is performed on daily data from 1st March 2016 to 28th February 2018.","PeriodicalId":11495,"journal":{"name":"Econometric Modeling: Capital Markets - Forecasting eJournal","volume":"81 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Forecasting Cryptocurrencies: A Comparison of GARCH Models\",\"authors\":\"Giovanni Angelini, S. Emili\",\"doi\":\"10.2139/ssrn.3195704\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we enhance the literature exploring the forecasting capability of six alternatives GARCH-type models to predict volatility of four of the most traded cryptocurrencies: Bitcoin, Ethereum, Ripple and Litecoin. The analysis is performed on daily data from 1st March 2016 to 28th February 2018.\",\"PeriodicalId\":11495,\"journal\":{\"name\":\"Econometric Modeling: Capital Markets - Forecasting eJournal\",\"volume\":\"81 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Econometric Modeling: Capital Markets - Forecasting eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3195704\",\"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: Capital Markets - Forecasting eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3195704","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Forecasting Cryptocurrencies: A Comparison of GARCH Models
In this paper we enhance the literature exploring the forecasting capability of six alternatives GARCH-type models to predict volatility of four of the most traded cryptocurrencies: Bitcoin, Ethereum, Ripple and Litecoin. The analysis is performed on daily data from 1st March 2016 to 28th February 2018.
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