Measuring information flux between social media and stock prices with Transfer Entropy.

Transfer Entropy was applied to analyze the correlations and flow of information between 200,500 tweets and 23 of the largest capitalized companies during 6 years along the period 2013-2018. The set of tweets were obtained applying a text mining algorithm and classified according to daily date and c...

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Autores principales:	Román Alejandro Mendoza Urdiales, Andrés García-Medina, José Antonio Nuñez Mora
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/22576571950040ca85063e1c7e365509
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spelling	oai:doaj.org-article:22576571950040ca85063e1c7e3655092021-12-02T20:14:15ZMeasuring information flux between social media and stock prices with Transfer Entropy.1932-620310.1371/journal.pone.0257686https://doaj.org/article/22576571950040ca85063e1c7e3655092021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0257686https://doaj.org/toc/1932-6203Transfer Entropy was applied to analyze the correlations and flow of information between 200,500 tweets and 23 of the largest capitalized companies during 6 years along the period 2013-2018. The set of tweets were obtained applying a text mining algorithm and classified according to daily date and company mentioned. We proposed the construction of a Sentiment Index applying a Natural Processing Language algorithm and structuring the sentiment polarity for each data set. Bootstrapped Simulations of Transfer Entropy were performed between stock prices and Sentiment Indexes. The results of the Transfer Entropy simulations show a clear information flux between general public opinion and companies' stock prices. There is a considerable amount of information flowing from general opinion to stock prices, even between different Sentiment Indexes. Our results suggest a deep relationship between general public opinion and stock prices. This is important for trading strategies and the information release policies for each company.Román Alejandro Mendoza UrdialesAndrés García-MedinaJosé Antonio Nuñez MoraPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 9, p e0257686 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Román Alejandro Mendoza Urdiales Andrés García-Medina José Antonio Nuñez Mora Measuring information flux between social media and stock prices with Transfer Entropy.
description	Transfer Entropy was applied to analyze the correlations and flow of information between 200,500 tweets and 23 of the largest capitalized companies during 6 years along the period 2013-2018. The set of tweets were obtained applying a text mining algorithm and classified according to daily date and company mentioned. We proposed the construction of a Sentiment Index applying a Natural Processing Language algorithm and structuring the sentiment polarity for each data set. Bootstrapped Simulations of Transfer Entropy were performed between stock prices and Sentiment Indexes. The results of the Transfer Entropy simulations show a clear information flux between general public opinion and companies' stock prices. There is a considerable amount of information flowing from general opinion to stock prices, even between different Sentiment Indexes. Our results suggest a deep relationship between general public opinion and stock prices. This is important for trading strategies and the information release policies for each company.
format	article
author	Román Alejandro Mendoza Urdiales Andrés García-Medina José Antonio Nuñez Mora
author_facet	Román Alejandro Mendoza Urdiales Andrés García-Medina José Antonio Nuñez Mora
author_sort	Román Alejandro Mendoza Urdiales
title	Measuring information flux between social media and stock prices with Transfer Entropy.
title_short	Measuring information flux between social media and stock prices with Transfer Entropy.
title_full	Measuring information flux between social media and stock prices with Transfer Entropy.
title_fullStr	Measuring information flux between social media and stock prices with Transfer Entropy.
title_full_unstemmed	Measuring information flux between social media and stock prices with Transfer Entropy.
title_sort	measuring information flux between social media and stock prices with transfer entropy.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/22576571950040ca85063e1c7e365509
work_keys_str_mv	AT romanalejandromendozaurdiales measuringinformationfluxbetweensocialmediaandstockpriceswithtransferentropy AT andresgarciamedina measuringinformationfluxbetweensocialmediaandstockpriceswithtransferentropy AT joseantonionunezmora measuringinformationfluxbetweensocialmediaandstockpriceswithtransferentropy
_version_	1718374692867276800

Measuring information flux between social media and stock prices with Transfer Entropy.

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