Mutual-Excitation of Cryptocurrency Market Returns and Social Media Topics
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Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Jun 2018.
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Citing papers per year: 2021: 2; 2022: 1.
3 papers.
- 2022Cryptocurrency Bubble Detection: A New Stock Market Dataset, Financial Task & Hyperbolic Modelscited by 4
- 2021On Technical Trading and Social Media Indicators in Cryptocurrencies' Price Classification Through Deep Learningcited by 2
- 2021Integrating Heuristics and Learning in a Computational Architecture for Cognitive Tradingcited by 0
- 2022Cryptocurrency Bubble Detection: A New Stock Market Dataset, Financial Task & Hyperbolic Models11 May 2022
- 2021Integrating Heuristics and Learning in a Computational Architecture for Cognitive Trading27 Aug 2021
- 2021On Technical Trading and Social Media Indicators in Cryptocurrencies' Price Classification Through Deep Learning13 Feb 2021