Correlations and Flow of Information between The New York Times and Stock Markets

Andr\'es Garc\'ia-Medina, Leonidas Sandoval Junior (), Efra\'in Urrutia Ba\~nuelos and A. M. Mart\'inez-Arg\"uello

Papers from arXiv.org

Abstract: We use Random Matrix Theory (RMT) and information theory to analyze the correlations and flow of information between 64,939 news from The New York Times and 40 world financial indices during 10 months along the period 2015-2016. The set of news was quantified and transformed into daily polarity time series using tools from sentiment analysis. Results from RMT shows that a common factor lead the world indices and news, and even share the same dynamics. Furthermore, the global correlation structure has found preserved when adding white noise, which indicate that correlations are not due to sample size effects. Likewise, we found a lot of information flowing from news to world indices for specific delay, being of practical interest for trading purpose. Our results suggest a deep relationship between news and world indices, and show a situation where news drive world market movements, giving a new evidence to support behavioral finance as the current economic paradigm.

Date: 2017-07
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://arxiv.org/pdf/1707.05778 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1707.05778

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().