Phillips, RC;
Gorse, D;
(2018)
Predicting cryptocurrency price bubbles using social media data and epidemic modelling.
In:
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence (SSCI).
(pp. pp. 394-400).
IEEE: Honolulu, HI, USA.
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Abstract
Financial price bubbles have previously been linked with the epidemic-like spread of an investment idea; such bubbles are commonly seen in cryptocurrency prices. This paper aims to predict such bubbles for a number of cryptocurrencies using a hidden Markov model previously utilised to detect influenza epidemic outbreaks, based in this case on the behaviour of novel online social media indicators. To validate the methodology further, a trading strategy is built and tested on historical data. The resulting trading strategy outperforms a buy and hold strategy. The work demonstrates both the broader utility of epidemic-detecting hidden Markov models in the identification of bubble-like behaviour in time series, and that social media can provide valuable predictive information pertaining to cryptocurrency price movements.
| Type: | Proceedings paper |
|---|---|
| Title: | Predicting cryptocurrency price bubbles using social media data and epidemic modelling |
| Event: | 2017 IEEE Symposium Series on Computational Intelligence (SSCI) |
| Location: | Honolulu, HI |
| Dates: | 27 November 2017 - 01 December 2017 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/SSCI.2017.8280809 |
| Publisher version: | https://doi.org/10.1109/SSCI.2017.8280809 |
| 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: | Science & Technology, Technology, Computer Science, Artificial Intelligence, Engineering, Electrical & Electronic, Computer Science, Engineering, cryptocurrency price bubbles, social media data mining, hidden Markov model, trading strategy, epidemic detection |
| UCL classification: | UCL 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/10062913 |
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