Impact of dynamic corporate news networks on asset return and volatility

This paper analyzes the relationship between asset return, volatility and the centrality indicators of a corporate news network conducting a longitudinal network analysis. We build a sequence of daily corporate news network for the period 2005-2011 using companies of the STOXX 50 index as nodes; the weights of the edges are the sum of the number of news items with the same topic by every pair of companies identified by the topic model methodology. The STOXX 50 includes the top 50 European companies by level of capitalization. We performed the Granger causality test and the Brownian distance covariance test of independence among several measures of centrality, return and volatility. We found that the average eigenvector centrality of the corporate news networks at different points of time has an impact on return and volatility of the STOXX 50 index. Likewise, return and volatility of the STOXX 50 index also has an effect on average eigenvector centrality. These results are more significant during the most important period of the recent financial crisis (January 2008-March 2009). So, we observe that there is a dynamic process that affects and is affected by return, volatility, and centrality. The causality tests suggest it is possible to improve the prediction of return and volatility by extracting and analyzing a network based on the common topics of news stories.