The dynamic predictive power of company comparative networks for stock sector performance

Chen, Kun1; Luo, Peng2; Xu, Dongming3; Wang, Huaiqing1

2016-12

10.1016/j.im.2016.07.005

INFORMATION & MANAGEMENT   影响因子和分区

0378-7206

1872-7530

As economic integration and business connections increase, companies actively interact with each other in the market in cooperative or competitive relationships. To understand the market network structure with company relationships and to investigate the impacts of market network structure on stock sector performance, we propose the construct of a company comparative network based on public media data and sector interaction metrics based on the company network. All the market network structure metrics are integrated into a vector autoregression model with stock sector return and risk. Several findings demonstrate the dynamic relationships that exist between sector interactions and sector performance. First, sector interaction metrics constructed based on company networks are significant leading indicators of sector performance. Interestingly, the interactions between sectors have greater predictive power than those within sectors. Second, compared with the company closeness network, the company comparative network, which labels the cooperative or competitive relationships between companies, is a better construct to understand and predict sector interactions and performance. Third, competitive company interactions between sectors impact sector performance in a slower manner than cooperative company interactions. The findings enrich financial studies regarding asset pricing by providing additional explanations of company/sector interactions and insights into company management using industry-level strategies. (C) 2016 Elsevier B.V. All rights reserved.

Company network Sentiment analysis Vector autoregression Stock sector performance

SCI ; EI ; SSCI

英语

第一 ; 通讯

Shenzhen Fundamental Research Grant[JCYJ2010417105742712]

Computer Science ; Information Science & Library Science ; Business & Economics

Computer Science, Information Systems ; Information Science & Library Science ; Management

WOS:000389159600008

ELSEVIER

20164803066540

Regression analysis ; Sentiment analysis

Mathematical Statistics:922.2

SOCIAL SCIENCES, GENERAL

Web of Science

1.South Univ Sci & Technol, Dept Finance, Shenzhen 518055, Peoples R China
2.Harbin Inst Technol, Sch Management, Harbin 150001, Peoples R China
3.Univ Queensland, Sch Business, St Lucia, Qld 4072, Australia

Chen, Kun,Luo, Peng,Xu, Dongming,et al. The dynamic predictive power of company comparative networks for stock sector performance[J]. INFORMATION & MANAGEMENT,2016,53(8):1006-1019.

Chen, Kun,Luo, Peng,Xu, Dongming,&Wang, Huaiqing.(2016).The dynamic predictive power of company comparative networks for stock sector performance.INFORMATION & MANAGEMENT,53(8),1006-1019.

Chen, Kun,et al."The dynamic predictive power of company comparative networks for stock sector performance".INFORMATION & MANAGEMENT 53.8(2016):1006-1019.