Title :
Diversification improvements through news article co-occurrences
Author :
Yaros, John Robert ; Imielinski, Tomasz
Author_Institution :
Dept. of Comput. Sci., Rutgers Univ., Piscataway, NJ, USA
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.
Keywords :
investment; organisational aspects; risk management; stock markets; company relatedness; competitors; diversification improvements; economic sector; expert-defined industry taxonomy; future stock-return correlation; news article cooccurrences; portfolio concentration; portfolio diversification; retailer; supply chain partners; Companies; Correlation; Industries; Portfolios; Risk management; Standards; Taxonomy;
Conference_Titel :
Computational Intelligence for Financial Engineering & Economics (CIFEr), 2104 IEEE Conference on
Conference_Location :
London
DOI :
10.1109/CIFEr.2014.6924064