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

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  • Li, Yue
  • Goodell, John W.
  • Shen, Dehua

Abstract

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.

Suggested Citation

  • Li, Yue & Goodell, John W. & Shen, Dehua, 2021. "Comparing search-engine and social-media attentions in finance research: Evidence from cryptocurrencies," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 723-746.
    • Handle: RePEc:eee:reveco:v:75:y:2021:i:c:p:723-746
    DOI: 10.1016/j.iref.2021.05.003
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    More about this item

    Keywords

    Cryptocurrencies; Investor attention; Granger causality; Social media; Twitter; Google; Wavelet testing;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G4 - Financial Economics - - Behavioral Finance

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