ArticleEntropy (Basel, Switzerland)2021
Information Theoretic Causality Detection between Financial and Sentiment Data.
Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- A methodological approach for inferring causal relationships from opinions and news-derived events with an application to climate change.PeerJ. Computer science · 2025Article
- Twitter Sentiment Analysis and Influence on Stock Performance Using Transfer Entropy and EGARCH Methods.Entropy (Basel, Switzerland) · 2022Article
- Network based evidence of the financial impact of Covid-19 pandemic.International review of financial analysis · 2022Article
- Assessing Banks' Distress Using News and Regular Financial Data.Frontiers in artificial intelligence · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The interaction between the flow of sentiment expressed on blogs and media and the dynamics of the stock market prices are analyzed through an information-theoretic measure, the transfer entropy, to quantify causality relations. We analyzed daily stock price and daily social media sentiment for the top 50 companies in the Standard & Poor (S&P) index during the period from November 2018 to November 2020. We also analyzed news mentioning these companies during the same period. We found that there is a causal flux of information that links those companies. The largest fraction of significant causal links is between prices and between sentiments, but there is also significant causal information which goes both ways from sentiment to prices and from prices to sentiment. We observe that the strongest causal signal between sentiment and prices is associated with the Tech sector.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.