Zheludev, Ilya, Smith, Robert and Aste, Tomaso (2014) When can social media lead financial markets? Scientific Reports, 4 (4213). ISSN 2045-2322
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Abstract
Social media analytics is showing promise for the prediction of financial markets. However, the true value of such data for trading is unclear due to a lack of consensus on which instruments can be predicted and how. Current approaches are based on the evaluation of message volumes and are typically assessed via retrospective (ex-post facto) evaluation of trading strategy returns. In this paper, we present instead a sentiment analysis methodology to quantify and statistically validate which assets could qualify for trading from social media analytics in an ex-ante configuration. We use sentiment analysis techniques and Information Theory measures to demonstrate that social media message sentiment can contain statistically-significant ex-ante information on the future prices of the S&P500 index and a limited set of stocks, in excess of what is achievable using solely message volumes.
| Item Type: | Article |
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| Official URL: | http://www.nature.com/srep/2014/140227/srep04213/f... |
| Additional Information: | © 2014 Macmillan Publishers Limited |
| Divisions: | LSE |
| Subjects: | H Social Sciences > H Social Sciences (General) H Social Sciences > HC Economic History and Conditions H Social Sciences > HJ Public Finance |
| Date Deposited: | 01 Jul 2014 15:34 |
| Last Modified: | 12 Dec 2024 00:40 |
| Projects: | ES/K002309/1 |
| Funders: | Economic and Social Research Council |
| URI: | http://eprints.lse.ac.uk/id/eprint/57376 |
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