Does market attention affect Bitcoin returns and volatility?

Gianna Figà-Talamanca and Marco Patacca

Decisions in Economics and Finance, 2019, vol. 42, issue 1, No 8, 135-155

Abstract: Abstract In this paper, we analyze the relative impact of attention measures either on the mean or on the variance of Bitcoin returns by fitting nonlinear econometric models to historical data: Two non-overlapping subsamples are considered from January 1, 2012, to December 31, 2017. Outcomes confirm that market attention has an impact on Bitcoin returns and volatility, when measured by applying several transformations on time series for the trading volume or the SVI Google searches index. Specifically, best candidate models are selected via the so-called Box–Jenkins methodology and by maximizing out-of-sample forecasting performance. Overall, we can conclude that trading volume-related measures affect both the mean and the volatility of the cryptocurrency returns, while Internet searches volume mainly affects the volatility. An interesting side finding is that the inclusion of attention measures in model specification makes forecast estimates more accurate.

Keywords: Bitcoin; Market attention; ARMA time series models; GARCH time series models; Box–Jenkins procedure; Forecasting analysis; 91B20; 91G70 (search for similar items in EconPapers)
JEL-codes: C22 C52 C58 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (18)

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DOI: 10.1007/s10203-019-00258-7

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