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dc.contributor.authorRoy, Ram Babu
dc.contributor.authorSarkar, Uttam Kumar
dc.descriptionRoy, Ram Babu, Indian Institute of Technology Kharagpur, Kharagpur, 721 302, India; Sarkar, Uttam Kumar, Indian Institute of Management Calcutta, Kolkata, 700 104, India
dc.descriptionISSN/ISBN - 03029743
dc.descriptionDOI - 10.1007/978-3-642-40319-4_6
dc.description.abstractWe propose a method to identify dominant economic sectors and stock markets using a social network approach to mining stock market data. Closing price data from January 1998 through January 2011 of 2698 stocks selected from 17 major stock market indices have been used in the analysis. A Minimum Spanning Tree (MST) has been constructed using the cross-correlations between weekly returns of the stocks. The MST has been chosen to obtain a simplified but connected network having linkages among similarly behaving stocks and it constitutes a social network of stocks for our study. The macroscopic interdependence networks among economic sectors as well as among stock markets have been derived from the microscopic linkages among stocks in the MST. The analysis of these derived macroscopic networks demonstrates that the European and the North American stock markets and Financial, Industrials, Materials, and Consumer Discretionary economic sectors dominate in the global stock markets. © Springer-Verlag 2013.
dc.publisherLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation.ispartofseries7867 LNAI
dc.subjectCorrelation coefficient
dc.subjectEconomic sectors
dc.subjectGlobal stock market
dc.subjectMinimum spanning tree
dc.subjectSocial network mining
dc.titleIdentifying dominant economic sectors and stock markets: A social network mining approach
dc.typeConference Paper
Appears in Collections:Management Information Systems

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