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Multi-channel discourse as an indicator for Bitcoin price and volume movements

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  • Marvin Aron Kennis

Abstract

This research aims to identify how Bitcoin-related news publications and online discourse are expressed in Bitcoin exchange movements of price and volume. Being inherently digital, all Bitcoin-related fundamental data (from exchanges, as well as transactional data directly from the blockchain) is available online, something that is not true for traditional businesses or currencies traded on exchanges. This makes Bitcoin an interesting subject for such research, as it enables the mapping of sentiment to fundamental events that might otherwise be inaccessible. Furthermore, Bitcoin discussion largely takes place on online forums and chat channels. In stock trading, the value of sentiment data in trading decisions has been demonstrated numerous times [1] [2] [3], and this research aims to determine whether there is value in such data for Bitcoin trading models. To achieve this, data over the year 2015 has been collected from Bitcointalk.org, (the biggest Bitcoin forum in post volume), established news sources such as Bloomberg and the Wall Street Journal, the complete /r/btc and /r/Bitcoin subreddits, and the bitcoin-otc and bitcoin-dev IRC channels. By analyzing this data on sentiment and volume, we find weak to moderate correlations between forum, news, and Reddit sentiment and movements in price and volume from 1 to 5 days after the sentiment was expressed. A Granger causality test confirms the predictive causality of the sentiment on the daily percentage price and volume movements, and at the same time underscores the predictive causality of market movements on sentiment expressions in online communities

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  • Marvin Aron Kennis, 2018. "Multi-channel discourse as an indicator for Bitcoin price and volume movements," Papers 1811.03146, arXiv.org.
    • Handle: RePEc:arx:papers:1811.03146
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    References listed on IDEAS

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    1. Pearce, Douglas K & Roley, V Vance, 1985. "Stock Prices and Economic News," The Journal of Business, University of Chicago Press, vol. 58(1), pages 49-67, January.
    2. Glantz, Morton & Kissell, Robert, 2013. "Multi-Asset Risk Modeling," Elsevier Monographs, Elsevier, edition 1, number 9780124016903.
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    Cited by:

    1. Kumar Kulbhaskar, Anamika & Subramaniam, Sowmya, 2023. "Breaking news headlines: Impact on trading activity in the cryptocurrency market," Economic Modelling, Elsevier, vol. 126(C).

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