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Jordi

This paper does something similar using the topic model methodology to build a corporate network of common news topics among different European companies. 

Best, G. Creamer

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2196572

Impact of Dynamic Corporate News Networks on Assets Return and Volatility



Abstract:      
This paper analyzes the relationship between assets return, volatility and the centrality indicators of a corporate news network. 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 conducted two studies to evaluate the impact of corporate news network in the assets return dynamic. In the first study we conducted a longitudinal network analysis using the stochastic actor oriented model with daily return and news for March 2009. We found that there was a 0.55 correlation between the rate of change of the news network and the STOXX 50 index. In the second study we extended our longitudinal analysis of networks using a sequence of daily corporate news networks for the period 2005-2011. 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 (January2008-March 2009). The same results hold when we examine this relationship at the level of individual companies. 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.


On Fri, Jun 13, 2014 at 9:55 AM, Jordi Comas <[log in to unmask]> wrote:
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Hello-

SO a friend and colleague is starting to think about doing some network studies of intellectuals, their groups, and ideas or concepts.

FOr example, in a period, there are intellectuals who have relations due to co-membership in journals, schools, universities, and so on.  That is a first bimodal network of groups by persons.  Second, he wants to look at a topic like baking (not his topic) and how it emerges in one journal/person cluster and perhaps "moves' over time to others.  Like a diffusion study.

A question in my head is if the the people, groups and concepts can be one big bimodal network?  Or, can we have "trimodal" networks of three kinds of objects?

Are there models of how to study this kind of question that is at the intersection of social structure and meaning-making/cultural dynamics.

THANK YOU!

Jordi

--
Jordi Comas

"There is nothing so practical as a good theory."  Kurt Lewin

Assistant Professor
School of Management
Bucknell University
Taylor 112
570 577 3161

Research and Writing Blog: Nets We Weave


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--

Germán (Herman) Creamer, PhD
Associate Professor 
Stevens Institute of Technology

T 201.216.8986
F 201.216.5385
http://ssrn.com/author=487822
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