{"title":"A seesaw effect in the cryptocurrency market: Understanding the return cross predictability of cryptocurrencies","authors":"Yuecheng Jia , Yangru Wu , Shu Yan , Yuzheng Liu","doi":"10.1016/j.jempfin.2023.101428","DOIUrl":null,"url":null,"abstract":"<div><p><span>This paper investigates the intraday return cross-predictability of cryptocurrencies. In contrast to the positive lead–lag effect for stocks, we document a negative lead–lag effect in the cryptocurrency market. Specifically, the large coins negatively predict the other coins but the small coins rarely predict the large coins. A trading strategy that exploits the cross-predictability via the Least Absolute Shrinkage and Selection Operator (</span><span><math><mrow><mi>L</mi><mi>A</mi><mi>S</mi><mi>S</mi><mi>O</mi></mrow></math></span>) yields highly significant profits across major cryptocurrency exchanges even in the presence of realistic transaction costs.</p></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"74 ","pages":"Article 101428"},"PeriodicalIF":2.1000,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Empirical Finance","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0927539823000956","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
This paper investigates the intraday return cross-predictability of cryptocurrencies. In contrast to the positive lead–lag effect for stocks, we document a negative lead–lag effect in the cryptocurrency market. Specifically, the large coins negatively predict the other coins but the small coins rarely predict the large coins. A trading strategy that exploits the cross-predictability via the Least Absolute Shrinkage and Selection Operator () yields highly significant profits across major cryptocurrency exchanges even in the presence of realistic transaction costs.
期刊介绍:
The Journal of Empirical Finance is a financial economics journal whose aim is to publish high quality articles in empirical finance. Empirical finance is interpreted broadly to include any type of empirical work in financial economics, financial econometrics, and also theoretical work with clear empirical implications, even when there is no empirical analysis. The Journal welcomes articles in all fields of finance, such as asset pricing, corporate finance, financial econometrics, banking, international finance, microstructure, behavioural finance, etc. The Editorial Team is willing to take risks on innovative research, controversial papers, and unusual approaches. We are also particularly interested in work produced by young scholars. The composition of the editorial board reflects such goals.