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Can volume predict Bitcoin returns and volatility? A quantiles-based approach

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Balcilar, Mehmet, Bouri, Elie, Gupta, Rangan, Roubaud, David·2017·Economic Modelling
DOI 10.1016/j.econmod.2017.03.019
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Abstract

Prior studies on the price formation in the Bitcoin market consider the role of Bitcoin transactions at the conditional mean of the returns distribution. This study employs in contrast a non-parametric causality-in-quantiles test to analyse the causal relation between trading volume and Bitcoin returns and volatility, over the whole of their respective conditional distributions. The nonparametric characteristics of our test control for misspecification due to nonlinearity and structural breaks, two features of our data that cover 19th December 2011 to 25th April 2016. The causality-in-quantiles test reveals that volume can predict returns – except in Bitcoin bear and bull market regimes. This result highlights the importance of modelling nonlinearity and accounting for the tail behaviour when analysing causal relationships between Bitcoin returns and trading volume. We show, however, that volume cannot help predict the volatility of Bitcoin returns at any point of the conditional distribution.

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Metadata

Authors
Balcilar, M., Bouri, E., Gupta, R., & Roubaud, D.
Venue
Economic Modelling
Publisher
Elsevier BV
Published
2017-08
Volume
64
Pages
74-81
ISSN
0264-9993 (ISSN-L)
DOI
10.1016/j.econmod.2017.03.019
OpenAlex
W2601386739
Cited by
715
References
1
FWCI
106.13
Type
journal article
Language
en
Open access
green
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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CoChat. (2026). Citation check: Can volume predict Bitcoin returns and volatility? A quantiles-based approach. https://app.cochat.ai/papers/10.1016/j.econmod.2017.03.019
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Balcilar, M., Bouri, E., Gupta, R., & Roubaud, D. (2017). Can volume predict Bitcoin returns and volatility? A quantiles-based approach. Economic Modelling. https://doi.org/10.1016/j.econmod.2017.03.019

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