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

被引:2
作者
Sengupta, Anwesha [1 ]
Upadhyay, Shashankaditya [2 ]
Mukherjee, Indranil [3 ]
Panigrahi, Prasanta K. [2 ]
机构
[1] Maulana Abul Kalam Azad Univ Technol, Dept Appl Stat, Haringhata 741249, West Bengal, India
[2] Indian Inst Sci Educ & Res, Dept Phys Sci, Kolkata 741246, West Bengal, India
[3] Maulana Abul Kalam Azad Univ Technol West Bengal, Sch Management Sci, Haringhata 741249, West Bengal, India
来源
JOURNAL OF COMPUTATIONAL SOCIAL SCIENCE | 2024年 / 7卷 / 01期
关键词
Influential spreaders; Complex networks; Centrality measures; Market competition; Causality; GRANGER-CAUSALITY; IDENTIFICATION; CENTRALITY; BEHAVIOR; NODES; RISK;
D O I
10.1007/s42001-023-00229-4
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
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.
引用
收藏
页码:45 / 85
页数:41
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