A study of the effect of influential spreaders on the different sectors of Indian market and a few foreign markets: a complex networks perspective

Anwesha Sengupta (), Shashankaditya Upadhyay, Indranil Mukherjee and Prasanta K. Panigrahi
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Anwesha Sengupta: Maulana Abul Kalam Azad University of Technology
Shashankaditya Upadhyay: Indian Institute of Science Education and Research, Kolkata
Indranil Mukherjee: Maulana Abul Kalam Azad University of Technology
Prasanta K. Panigrahi: Indian Institute of Science Education and Research, Kolkata

Journal of Computational Social Science, 2024, vol. 7, issue 1, No 3, 45-85

Abstract: Abstract Market competition has a role that is directly or indirectly associated with the influential effects of individual sectors on other sectors of the financial market. The present work studies the relative position of stocks in the market through the identification of influential spreaders and their corresponding effect on the other sectors of the market using complex network analysis during and after the COVID-19-induced lockdown periods. The study uses daily data of NSE along with those of different countries like USA (Nasdaq), UK (UK stock exchange), Japan (Nikkei) and Brazil (Bovespa) from December 2019 to June 2021. The existing network approaches using different centrality measures failed to distinguish between the positive and negative influences of the different sectors in the market which act as spreaders. To overcome this problem, this paper presents an effective measure called LIEST (Local Influential Effects for a Specific Target) that can examine the positive and negative influences separately with respect to any period. LIEST considers the combined impact of all possible nodes which are at most three steps away from the specific target nodes in the networks. This study considers the transmission of financial influence originating at a source node (a particular stock) and propagating to target nodes through the financial market modeled as a complex network where the structure of the network is captured by correlation. The essence of non-linearity in the network dynamics without considering the single node effect becomes visible in the proposed network. A comparative analysis has been undertaken among the stocks drawn from financial markets around the world (USA, UK, Brazil and Japan) with that of the Indian stock to obtain an idea about the global market behaviour. As an example, the active participation of healthcare and consumer defensive sectors along with financial, industrial and technology sectors have been found to create an effective positive impact on the Indian market. Similar results have been obtained with stock market data obtained from other countries. In addition, in respect of spreading performance the proposed approach is found to be efficient as validated by the TRIVALENCY model.

Keywords: Influential spreaders; Complex networks; Centrality measures; Market competition; Causality (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s42001-023-00229-4

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