{"title":"当早期采用者向追随者学习:GBTC折扣和溢价的加密货币回报可预测性","authors":"Lei Huang, Tse-Chun Lin, Fangzhou Lu","doi":"10.2139/ssrn.3948407","DOIUrl":null,"url":null,"abstract":"We show that change in Grayscale Bitcoin Trust premium is the single most significant predictor of Bitcoin daily return. This sentiment measure is similar to the closed-end fund discount measure as in Baker and Wurgler (2006), but more likely to reflect the excess demand from traditional investors than from blockchain specialists. Although there is a substantial variation in Bitcoin price quotes worldwide, this Grayscale premium and discount predict Bitcoin daily return for the most liquid Bitcoin exchanges. Using K-means clustering and LDA analysis, we find that this predictability is especially significant when there is a large variation in bullish and bearish market sentiment, innovation regarding CBDC, regulations on crypto exchanges, but not when there is innovation regarding blockchain technology or bitcoin mining. A simple long and short strategy based on this signal generates a daily alpha of 40 bps. These findings suggest that Bitcoin prices react with a delay to the information contained in the sentiment of traditional investors and investors who are constrained from directly holding Bitcoin.","PeriodicalId":126646,"journal":{"name":"PSN: Exchange Rates & Currency (International) (Topic)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"When Early Adopters Learn From the Followers: The Cryptocurrency Return Predictability of GBTC Discount and Premium\",\"authors\":\"Lei Huang, Tse-Chun Lin, Fangzhou Lu\",\"doi\":\"10.2139/ssrn.3948407\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We show that change in Grayscale Bitcoin Trust premium is the single most significant predictor of Bitcoin daily return. This sentiment measure is similar to the closed-end fund discount measure as in Baker and Wurgler (2006), but more likely to reflect the excess demand from traditional investors than from blockchain specialists. Although there is a substantial variation in Bitcoin price quotes worldwide, this Grayscale premium and discount predict Bitcoin daily return for the most liquid Bitcoin exchanges. Using K-means clustering and LDA analysis, we find that this predictability is especially significant when there is a large variation in bullish and bearish market sentiment, innovation regarding CBDC, regulations on crypto exchanges, but not when there is innovation regarding blockchain technology or bitcoin mining. A simple long and short strategy based on this signal generates a daily alpha of 40 bps. These findings suggest that Bitcoin prices react with a delay to the information contained in the sentiment of traditional investors and investors who are constrained from directly holding Bitcoin.\",\"PeriodicalId\":126646,\"journal\":{\"name\":\"PSN: Exchange Rates & Currency (International) (Topic)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PSN: Exchange Rates & Currency (International) (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3948407\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PSN: Exchange Rates & Currency (International) (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3948407","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
When Early Adopters Learn From the Followers: The Cryptocurrency Return Predictability of GBTC Discount and Premium
We show that change in Grayscale Bitcoin Trust premium is the single most significant predictor of Bitcoin daily return. This sentiment measure is similar to the closed-end fund discount measure as in Baker and Wurgler (2006), but more likely to reflect the excess demand from traditional investors than from blockchain specialists. Although there is a substantial variation in Bitcoin price quotes worldwide, this Grayscale premium and discount predict Bitcoin daily return for the most liquid Bitcoin exchanges. Using K-means clustering and LDA analysis, we find that this predictability is especially significant when there is a large variation in bullish and bearish market sentiment, innovation regarding CBDC, regulations on crypto exchanges, but not when there is innovation regarding blockchain technology or bitcoin mining. A simple long and short strategy based on this signal generates a daily alpha of 40 bps. These findings suggest that Bitcoin prices react with a delay to the information contained in the sentiment of traditional investors and investors who are constrained from directly holding Bitcoin.