Intraday Volume-Return Nexus in Cryptocurrency Markets: A Novel Evidence From Cryptocurrency Classification

L. Yarovaya, D. Zięba
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引用次数: 7

Abstract

This paper analyses the volume-return relationships across top 30 most traded cryptocurrencies from the April 2013 to June 2019 using a high-frequency intraday data. We use a novel approach for the classification of cryptocurrencies with respect to multiple qualitative factors, such as geographical location of headquarters, founder and founder’s origin, platform on which cryptocurrency built on, consensus algorithm, to name but a few. We identified significant bidirectional causalities between trading volume and returns at high-frequency intervals, however, those linkages are disappearing with increased frequencies of data. The findings confirm the leading position of the Bitcoin trading volume in the cryptocurrency price formation. This evidence will help investors to design effective trading strategies in cryptocurrency market providing useful insights from cryptocurrency categorisation.
加密货币市场的日内交易量-收益关系:来自加密货币分类的新证据
本文使用高频日内数据分析了2013年4月至2019年6月交易最多的30种加密货币的交易量-收益关系。我们使用了一种新颖的方法,根据多个定性因素对加密货币进行分类,例如总部的地理位置、创始人和创始人的来源、加密货币所依赖的平台、共识算法等等。我们确定了高频间隔下交易量和回报之间显著的双向因果关系,然而,这些联系随着数据频率的增加而消失。研究结果证实了比特币交易量在加密货币价格形成中的领先地位。这一证据将帮助投资者在加密货币市场中设计有效的交易策略,从加密货币分类中提供有用的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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