Scaramozzino Roberta, Cerchiello Paola, Aste Tomaso
Department of Economics and Management, University of Pavia, Via San Felice 7, 27100 Pavia, Italy.
Department of Computer Science, University College London, Gower Street, London WC1E 6EA, UK.
Entropy (Basel). 2021 May 16;23(5):621. doi: 10.3390/e23050621.
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.
通过一种信息论测度——转移熵，来分析博客和媒体上表达的情绪流与股票市场价格动态之间的相互作用，以量化因果关系。我们分析了2018年11月至2020年11月期间标准普尔（S&P）指数中排名前50的公司的每日股价和每日社交媒体情绪。我们还分析了同一时期提及这些公司的新闻。我们发现存在连接这些公司的信息因果流。显著因果联系的最大部分存在于价格之间和情绪之间，但也存在从情绪到价格以及从价格到情绪的双向显著因果信息。我们观察到，情绪与价格之间最强的因果信号与科技板块相关。
