Assessing causal relationships between cryptocurrencies and investor attention: New results from transfer entropy methodology

Zezheng Tong, John W. Goodell and Dehua Shen

Finance Research Letters, 2022, vol. 50, issue C

Abstract: Studies apply non-parametric wavelet Granger causality testing to investigate bi-directional causalities of cryptocurrencies with Twitter and Google. However, this method only provides the existence of information flows without quantization and assumes time series are linear. Considering this, we highlight transfer entropy as an alternative, model-free methodology. We quantify the impact of search-engine attention (Google Trends) and social-media attention (Twitter) on cryptocurrency returns, employing in turn Shannon and Rényi transfer entropy methodologies. We document levels of bi-directional causalities, showing that tail events are more informative than center observations in the cryptocurrency market.

Keywords: Cryptocurrencies; Investor attention; Transfer entropy; Google trends; Twitter (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1544612322005293
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:50:y:2022:i:c:s1544612322005293

DOI: 10.1016/j.frl.2022.103351

Access Statistics for this article

Finance Research Letters is currently edited by R. Gençay

More articles in Finance Research Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().