Disentangling the relationship between Bitcoin and market attention measures

Gianna Figà-Talamanca and Marco Patacca

Economia e Politica Industriale: Journal of Industrial and Business Economics, 2020, vol. 47, issue 1, No 3, 91 pages

Abstract: Abstract In the last few years Bitcoin price dynamics has been the subject of intense research. One of the main stream of investigation is the identification of relevant factors affecting its returns and volatility; empirical evidence suggests a positive association between returns and sentiment proxies about the Bitcoin network, such as Wikipedia inquiries, internet search intensity on the topic, trading volume in main exchanges or sentiment measures obtained via natural language processing algorithms applied on specialized forums comments or social media posts on the theme. In this paper we investigate the association of trading volume and internet search intensity with Bitcoin returns and volatility, complementing the outcomes in Figá-Talamanca and Patacca (Decis Econ Fin ISSN: 1129-6569, https://doi.org/10.1007/s10203-019-00258-7, 2019) and Urquhart (Econ Lett 166:40–44, ISSN: 0165-1765, https://doi.org/10.1016/j.econlet.2018.02.017, 2018): we find no direct relationship between the two market attention measures and returns while both the trading volume and the internet search intensity affect positively Bitcoin volatility. Conversely, an increase in Bitcoin returns does increase both trading volume and internet search intensity, evidencing an inverse relationship between returns and attention measures. As a byproduct, we also detect a positive association between trading volume and the internet search intensity and no reverse relationship. Since market attention, especially internet search volume, do increase around relevant events and corresponding news or announcements for the Bitcoin market, we also analyze whether and to which extent the above relationships change, after specific events are taken into account. Indeed, by applying two different approaches, we show that the relationships may change significantly.

Keywords: Bitcoin; Investor attention; VAR models; GARCH models (search for similar items in EconPapers)
JEL-codes: C22 C32 C52 C58 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (10)

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DOI: 10.1007/s40812-019-00133-x

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