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dc.contributor.authorSharma K.
dc.contributor.authorGopalakrishnan B.
dc.contributor.authorChakrabarti A.S.
dc.contributor.authorChakraborti A.
dc.date.accessioned2022-02-11T10:13:54Z
dc.date.available2022-02-11T10:13:54Z
dc.date.issued2017
dc.identifier.citationSharma, K., Gopalakrishnan, B., Chakrabarti, A. S., & Chakraborti, A. (2017). Financial fluctuations anchored to economic fundamentals: A mesoscopic network approach. Scientific Reports, 7(1). https://doi.org/10.1038/s41598-017-07758-9
dc.identifier.issn20452322
dc.identifier.urihttps://www.doi.org/10.1038/s41598-017-07758-9
dc.identifier.urihttp://hdl.handle.net/11718/25206
dc.description.abstractWe demonstrate the existence of an empirical linkage between nominal financial networks and the underlying economic fundamentals, across countries. We construct the nominal return correlation networks from daily data to encapsulate sector-level dynamics and infer the relative importance of the sectors in the nominal network through measures of centrality and clustering algorithms. Eigenvector centrality robustly identifies the backbone of the minimum spanning tree defined on the return networks as well as the primary cluster in the multidimensional scaling map. We show that the sectors that are relatively large in size, defined with three metrics, viz., market capitalization, revenue and number of employees, constitute the core of the return networks, whereas the periphery is mostly populated by relatively smaller sectors. Therefore, sector-level nominal return dynamics are anchored to the real size effect, which ultimately shapes the optimal portfolios for risk management. Our results are reasonably robust across 27 countries of varying degrees of prosperity and across periods of market turbulence (2008-09) as well as periods of relative calmness (2012-13 and 2015-16). � 2017 The Author(s).
dc.language.isoen_US
dc.publisherNature Publishing Group
dc.relation.ispartofScientific Reports
dc.titleFinancial fluctuations anchored to economic fundamentals: A mesoscopic network approach
dc.typeArticle
dc.rights.licenseCC BY
dc.contributor.affiliationSchool of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, 110067, India
dc.contributor.affiliationFinance and Accounting Area, Indian Institute of Management, Vastrapur, Ahmedabad, 380015, India
dc.contributor.affiliationEconomics Area, Indian Institute of Management, Vastrapur, Ahmedabad, 380015, India
dc.contributor.institutionauthorSharma, K., School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, 110067, India
dc.contributor.institutionauthorGopalakrishnan, B., Finance and Accounting Area, Indian Institute of Management, Vastrapur, Ahmedabad, 380015, India
dc.contributor.institutionauthorChakrabarti, A.S., Economics Area, Indian Institute of Management, Vastrapur, Ahmedabad, 380015, India
dc.contributor.institutionauthorChakraborti, A., School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, 110067, India
dc.description.scopusid57192438995
dc.description.scopusid57195360900
dc.description.scopusid26421940400
dc.description.scopusid7005107556
dc.identifier.doi10.1038/s41598-017-07758-9
dc.identifier.issue1
dc.identifier.volume7


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