Time- and Quantile-Varying Causality between Investor Attention and Bitcoin Returns: A Rolling-Window Causality-in-Quantiles Approach

Jianqin Hang,Xu Zhang,Atila Bueno

doi:10.1155/2021/5543995

Jianqin Hang, Xu Zhang + Show 1 more

Open Access

https://doi.org/10.1155/2021/5543995

Copy DOI

Abstract

This study proposes a novel approach that incorporates rolling-window estimation and a quantile causality test. Using this approach, Google Trends and Bitcoin price data are used to empirically investigate the time-varying quantile causality between investor attention and Bitcoin returns. The results show that the parameters of the causality tests are unstable during the sample period. The results also show strong evidence of quantile- and time-varying causality between investor attention and Bitcoin returns. Specifically, our results show that causality appears only in high volatility periods within the time domain, and causality presents various patterns across quantiles within the quantile domain.

Highlights

Cryptocurrencies, a new form of digital assets, have drawn the attention of investors, researchers, and central banks since the global financial crisis
According to the results of Augmented Dickey-Fuller (ADF) tests, we fail to reject the null hypothesis of a unit root for the lnIA and the lnBP series under all specifications, implying that these two series are nonstationary
We reject the null hypothesis for the daily growth of IA (dIA) and dBP series, implying that these two series are stationary

Summary

Introduction

Cryptocurrencies, a new form of digital assets, have drawn the attention of investors, researchers, and central banks since the global financial crisis. It is widely regarded that such decentralized and encrypted currencies will be a subversive asset that brings shocks to the financial system. It is critical for investors and supervisors to identify the price mechanism to manage risks better. Due to their sharp volatility, cryptocurrency price movements have garnered much attention from economic scholars. In their dynamic network analysis, Balli et al [9] find that the short-term connectedness among cryptocurrencies is much stronger than medium and long term, and the connectedness decreases with the increase in economic uncertainty. Related studies have been conducted by Fousekis and Tzaferi [11] and Katsiampa [12], among others

Objectives

Methods

Results