Bitcoin, uncertainty and internet searches

Abstract

Purpose This paper aims to examine the predictive power of the volume of Economic Uncertainty Related Queries and the Macroeconomic Uncertainty Index on the Bitcoin returns. Design/methodology/approach Data consists of 118 monthly observations from September 2010 to June 2020. Due to the departure of series from Gaussian distribution and the existence of outliers, the authors use the quantile analysis framework to investigate the persistency of the shocks, the long-run relationships and Granger causality among the variables. Findings This research provides several important findings. First, the substantial differences between conventional and quantile test results stress the importance of the method selection. Second, throughout the conditional distribution of the series, stochastic properties of the variables, long-run and the causal relationships between the variables might be significantly different. Third, rich information provided by the quantile framework might help the investors design better investment strategies. Originality/value This study differs from the previous research in terms of variable selection and econometric methodology. Therefore, it presents a more comprehensive framework that suggests implications for empirical researchers and Bitcoin investors.

Behavioural antecedents of Bitcoin trading volume

“…In that sense, the literature on the impact of various behavioural variables on Bitcoin trading has literally proliferated. These include assessments of Twitter sentiment [16], Google-based indicators of investor sentiment [13], sentiment derived from news headlines [22], the Economic Policy Uncertainty (EPU) index [14,25] and the Chicago Board Options Exchange Volatility (VIX) index [1]. The aforementioned papers almost uniformly find that sentiment variables contain relevant information for predicting Bitcoin prices.…”