Please use this identifier to cite or link to this item: https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1745
Title: Identifying dominant economic sectors and stock markets: A social network mining approach
Authors: Roy, Ram Babu
Sarkar, Uttam Kumar
Keywords: Centrality
Correlation coefficient
Economic sectors
Global stock market
Minimum spanning tree
Social network mining
Issue Date: 2013
Publisher: SCOPUS
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Series/Report no.: 7867 LNAI
Abstract: We 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.
Description: Roy, Ram Babu, Indian Institute of Technology Kharagpur, Kharagpur, 721 302, India; Sarkar, Uttam Kumar, Indian Institute of Management Calcutta, Kolkata, 700 104, India
ISSN/ISBN - 03029743
pp.59-70
DOI - 10.1007/978-3-642-40319-4_6
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84892879831&doi=10.1007%2f978-3-642-40319-4_6&partnerID=40&md5=52a5a7c9af8d09a730940fa5f489f143
https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1745
Appears in Collections:Management Information Systems

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