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The Effects of Twitter Sentiment on Stock Price Returns
Social media are increasingly reflecting and influencing behavior of other complex systems. In this paper we investigate the relations between a well-known micro-blogging platform Twitter and financial markets. In particular, we consider, in a period of 15 months, the Twitter volume and sentiment ab...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4577113/ https://www.ncbi.nlm.nih.gov/pubmed/26390434 http://dx.doi.org/10.1371/journal.pone.0138441 |
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author | Ranco, Gabriele Aleksovski, Darko Caldarelli, Guido Grčar, Miha Mozetič, Igor |
author_facet | Ranco, Gabriele Aleksovski, Darko Caldarelli, Guido Grčar, Miha Mozetič, Igor |
author_sort | Ranco, Gabriele |
collection | PubMed |
description | Social media are increasingly reflecting and influencing behavior of other complex systems. In this paper we investigate the relations between a well-known micro-blogging platform Twitter and financial markets. In particular, we consider, in a period of 15 months, the Twitter volume and sentiment about the 30 stock companies that form the Dow Jones Industrial Average (DJIA) index. We find a relatively low Pearson correlation and Granger causality between the corresponding time series over the entire time period. However, we find a significant dependence between the Twitter sentiment and abnormal returns during the peaks of Twitter volume. This is valid not only for the expected Twitter volume peaks (e.g., quarterly announcements), but also for peaks corresponding to less obvious events. We formalize the procedure by adapting the well-known “event study” from economics and finance to the analysis of Twitter data. The procedure allows to automatically identify events as Twitter volume peaks, to compute the prevailing sentiment (positive or negative) expressed in tweets at these peaks, and finally to apply the “event study” methodology to relate them to stock returns. We show that sentiment polarity of Twitter peaks implies the direction of cumulative abnormal returns. The amount of cumulative abnormal returns is relatively low (about 1–2%), but the dependence is statistically significant for several days after the events. |
format | Online Article Text |
id | pubmed-4577113 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-45771132015-09-25 The Effects of Twitter Sentiment on Stock Price Returns Ranco, Gabriele Aleksovski, Darko Caldarelli, Guido Grčar, Miha Mozetič, Igor PLoS One Research Article Social media are increasingly reflecting and influencing behavior of other complex systems. In this paper we investigate the relations between a well-known micro-blogging platform Twitter and financial markets. In particular, we consider, in a period of 15 months, the Twitter volume and sentiment about the 30 stock companies that form the Dow Jones Industrial Average (DJIA) index. We find a relatively low Pearson correlation and Granger causality between the corresponding time series over the entire time period. However, we find a significant dependence between the Twitter sentiment and abnormal returns during the peaks of Twitter volume. This is valid not only for the expected Twitter volume peaks (e.g., quarterly announcements), but also for peaks corresponding to less obvious events. We formalize the procedure by adapting the well-known “event study” from economics and finance to the analysis of Twitter data. The procedure allows to automatically identify events as Twitter volume peaks, to compute the prevailing sentiment (positive or negative) expressed in tweets at these peaks, and finally to apply the “event study” methodology to relate them to stock returns. We show that sentiment polarity of Twitter peaks implies the direction of cumulative abnormal returns. The amount of cumulative abnormal returns is relatively low (about 1–2%), but the dependence is statistically significant for several days after the events. Public Library of Science 2015-09-21 /pmc/articles/PMC4577113/ /pubmed/26390434 http://dx.doi.org/10.1371/journal.pone.0138441 Text en © 2015 Ranco et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Ranco, Gabriele Aleksovski, Darko Caldarelli, Guido Grčar, Miha Mozetič, Igor The Effects of Twitter Sentiment on Stock Price Returns |
title | The Effects of Twitter Sentiment on Stock Price Returns |
title_full | The Effects of Twitter Sentiment on Stock Price Returns |
title_fullStr | The Effects of Twitter Sentiment on Stock Price Returns |
title_full_unstemmed | The Effects of Twitter Sentiment on Stock Price Returns |
title_short | The Effects of Twitter Sentiment on Stock Price Returns |
title_sort | effects of twitter sentiment on stock price returns |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4577113/ https://www.ncbi.nlm.nih.gov/pubmed/26390434 http://dx.doi.org/10.1371/journal.pone.0138441 |
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