Purpose

This paper aims to identify and quantify directional predictability between returns and volume in major cryptocurrencies markets.

Design/methodology/approach

The empirical analysis relies on the cross-quantilogram approach that allows one to assess the temporal (lag-lead) association between two stationary time series at different parts of their joint distribution. The data are daily prices and trading volumes from four markets (Bitcoin, Ethereum, Ripple and Litecoin).

Findings

Extreme returns either positive or negative tend to lead high volume levels. Low levels of trading activity have in general no information content about future returns; high levels, however, tend to precede extreme positive returns.

Originality/value

This is the first work that uses the cross-quantilogram approach to assess the temporal association between returns and volume in cryptocurrencies markets. The findings provide new insights about the informational efficiency of these markets and the traders’ strategies.

中文翻译：

---

加密货币市场回报和交易量之间的方向性可预测性

目的

本文旨在识别和量化主要加密货币市场中回报和交易量之间的方向可预测性。

设计/方法/方法

实证分析依赖于交叉分位数方法，该方法允许评估两个固定时间序列在其联合分布的不同部分之间的时间（滞后-超前）关联。数据是来自四个市场（比特币、以太坊、瑞波币和莱特币）的每日价格和交易量。

发现

正或负的极端回报往往会导致高成交量水平。低水平的交易活动通常没有关于未来回报的信息内容；然而，高水平往往先于极端正回报。

原创性/价值

这是第一项使用交叉数量图方法来评估加密货币市场中收益和交易量之间的时间关联的工作。研究结果为这些市场的信息效率和交易者的策略提供了新的见解。