4.7 Article

Comparing search-engine and social-media attentions in finance research: Evidence from cryptocurrencies

Journal

INTERNATIONAL REVIEW OF ECONOMICS & FINANCE
Volume 75, Issue -, Pages 723-746

Publisher

ELSEVIER
DOI: 10.1016/j.iref.2021.05.003

Keywords

Cryptocurrencies; Investor attention; Granger causality; Social media; Twitter; Google; Wavelet testing

Funding

  1. National Natural Science Foundation of China [72071141]

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This study investigates the bi-directional causalities between cryptocurrency returns and investor attention, finding that the combined attention of social media and search engines has a more significant impact on cryptocurrencies.
There is considerable interest in the impact of investor attention on investment returns, especially for cryptocurrencies. However, previous research does not distinguish between search-engine attention and social-media forms of attention-even though this distinction is emphasized by marketing professionals. Professional marketers emphasize that attention is optimized by combinations of social-media and search-engine presence. We investigate the bi-directional causalities, and concomitant frequencies, between cryptocurrency returns and investor attention, comparing cryptocurrency sensitivity to Twitter tweets and the intensity of Google searches, as well as combinations of Twitter and Google. For 27 cryptocurrencies, we use a non-parametric wavelet Granger causality test to incorporate multiple time horizons. We also employ Diebold and Yilmaz spillover testing to assess respective pairwise influence between attention measures and respective cryptocurrencies. Results indicate a preponderance of bidirectional Granger causality for the great majority of cryptocurrencies, with the impact of Twitter on cryptocurrencies being shorter term. Consistent with expectations, we identify that bi-directional causalities, and spillovers, of cryptocurrencies with investor attention are significantly more evident for proxies of investor attention that are combinations of social media (Twitter) and search engine intensity (Google), rather than either one of these forms alone. Our results have applicability to a broad range of investor attention studies.

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