Howe School Faculty Participate in BI Congress
Howe School Faculty Participate in Business Intelligence Congress which precedes the ICIS 2012
Several papers are being presented by Howe School faculty in Orlando this month at the BI Congress; also David Belanger is a Keynote speaker: It’s About the Data: A Decade+ Experiment in “Big Data.” German Creamer presents the paper A Longitudinal Analysis of Volatility and Corporate News Network. ICIS is the major annual meeting of the Association for Information Systems (AIS), which has over 4,000 members representing universities in over 95 countries worldwide. The BI congress precedes the ICIS event.
Creamer's paper: “A Longitudinal Analysis of Volatility and Corporate News Network,” with Yong Ren and Jeffrey Nickerson
This paper analyzes the relationship between asset 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 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 in 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 (2008-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 among 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.
Dave Belanger’s Keynote: It’s About the Data: A Decade+ Experiment in “Big Data”
Over the last decade, AT&T Shannon Labs) developed a broad and deep capability to manipulate, analyze, and visualize large amounts of data. What is now typically referred to as “Big Data.” It has been done in a laboratory, AT&T InfoLab, with live, real time data for over a decade. The data, and associated business problems, both inform the technology created, and support value through many applications.
Recent topics of focus have included: real time data mining, data stream management, interactive visualization, data mining of non-relational data (e.g. speech), and mining of data from distributed sensor networks, with applications ranging from customer experience, to recommender systems to medical monitoring/prediction.
This discussion will highlight a number of the approaches to maximize the value of data, as well as highlighting trends in this area.