@inproceedings{af77dbddb46e4f298aeb12637d7920f5,
title = "Diversification improvements through news article co-occurrences",
abstract = "Intuition suggests that a set of companies mentioned in the same news article are more likely to be related than unrelated. For instance, an article discussing a retailer would more probably mention its competitors or supply chain partners than mention other companies with no economic connection. Correspondingly, we consider using news article co-occurrences as a means to determine company relatedness. We show that companies mentioned together frequently are more likely to have higher future stock-return correlation, and consider using this data source as a means to achieve portfolio diversification by avoiding having pairs of related companies in the portfolio. We find this approach reduces risk and can be used to improve standard approaches to diversification that use expert-defined industry taxonomies, seeking to avoid portfolio concentration in any given economic sector.",
author = "Yaros, {John Robert} and Tomasz Imielinski",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2014 ; Conference date: 27-03-2014 Through 28-03-2014",
year = "2014",
month = oct,
day = "14",
doi = "10.1109/CIFEr.2014.6924064",
language = "English (US)",
series = "IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "130--137",
editor = "Antoaneta Serguieva and Dietmar Maringer and Vasile Palade and Almeida, {Rui Jorge}",
booktitle = "2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr Proceedings",
address = "United States",
}