On the dynamic relationship between transaction volume and returns: evidence from the cryptocurrency market

Yosra Ghabri, M. Gana
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Abstract

PurposeUsing vector autoregressive modelling (VAR) and Granger causality tests, this paper attempts to empirically investigate the dynamic relationship between return and volume of transactions of two main cryptocurrencies: Bitcoin and Ethereum.Design/methodology/approachBased on a generalized autoregressive conditional heteroskedasticity (GARCH) model with a transaction volume parameter in the conditional volatility equation.FindingsThe results provide empirical evidence of a positive contemporaneous relationship between the variation in transaction volume and the daily return of Bitcoin and Ethereum. The results also show that the conditional volatility of the returns is affected by the past volatility, which implies weak-form inefficiency for both Bitcoin and Ethereum markets. The results of the VAR model, testing Granger causality, indicate that the volume of transactions Granger-Causes Bitcoin and Ethereum returns. Furthermore, the findings show a Granger causal relation from returns to volume.Originality/valueThis result suggests that cryptocurrency returns can predict transaction volumes and vice versa.
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交易量与收益的动态关系:来自加密货币市场的证据
利用向量自回归模型(VAR)和格兰杰因果检验,本文试图实证研究两种主要加密货币:比特币和以太坊的收益与交易量之间的动态关系。基于广义自回归条件异方差(GARCH)模型,在条件波动方程中引入交易量参数。研究结果提供了经验证据,证明交易量变化与比特币和以太坊的每日回报之间存在正相关关系。结果还表明,回报的条件波动性受到过去波动性的影响,这意味着比特币和以太坊市场都存在弱形式的低效率。VAR模型检验格兰杰因果关系的结果表明,交易量格兰杰导致比特币和以太坊的回报。此外,研究结果表明,收益与交易量之间存在格兰杰因果关系。独创性/价值这一结果表明,加密货币的回报可以预测交易量,反之亦然。
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来源期刊
CiteScore
1.80
自引率
5.60%
发文量
83
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