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Mutual-excitation of cryptocurrency market returns and social media topics

Phillips, RC; Gorse, D; (2018) Mutual-excitation of cryptocurrency market returns and social media topics. In: ICFET '18 Proceedings of the 4th International Conference on Frontiers of Educational Technologies. (pp. pp. 80-86). ACM: Moscow, Russian Federation. Green open access

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Abstract

Cryptocurrencies have recently experienced a new wave of price volatility and interest; activity within social media communities relating to cryptocurrencies has increased significantly. There is currently limited documented knowledge of factors which could indicate future price movements. This paper aims to decipher relationships between cryptocurrency price changes and topic discussion on social media to provide, among other things, an understanding of which topics are indicative of future price movements. To achieve this a well-known dynamic topic modelling approach is applied to social media communication to retrieve information about the temporal occurrence of various topics. A Hawkes model is then applied to find interactions between topics and cryptocurrency prices. The results show particular topics tend to precede certain types of price movements, for example the discussion of ‘risk and investment vs trading’ being indicative of price falls, the discussion of ‘substantial price movements’ being indicative of volatility, and the discussion of ‘fundamental cryptocurrency value’ by technical communities being indicative of price rises. The knowledge of topic relationships gained here could be built into a real-time system, providing trading or alerting signals.

Type: Proceedings paper
Title: Mutual-excitation of cryptocurrency market returns and social media topics
Event: ICFET '18: 4th International Conference on Frontiers of Educational Technologies
Location: Moscow, Russian Federation
Dates: 25 - 27 June 2018
ISBN-13: 9781450364720
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3233347.3233370
Publisher version: https://doi.org/10.1145/3233347.3233370
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: cryptocurrency trading, topic modelling, social media data mining, LDA, Hawkes models.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10074781
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