
CORPORATE STRATEGY DEVIATION AND INSTITUTIONAL INVESTOR RECOGNITION: COMPLEX NETWORK-BASED AND GRAPH CLUSTERING ANALYSIS
Author(s) -
Chunyan Lin,
Jia Liu,
Пэйдэ Лю
Publication year - 2021
Publication title -
technological and economic development of economy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.634
H-Index - 47
eISSN - 2029-4921
pISSN - 2029-4913
DOI - 10.3846/tede.2021.15498
Subject(s) - fallacy , cluster analysis , business , perspective (graphical) , institutional investor , panel data , industrial organization , econometrics , economics , artificial intelligence , computer science , finance , corporate governance , philosophy , epistemology
In this paper, the quantitative analysis is implemented on the relationship between strategy deviation of listed firms and institutional investors’ recognition. For research methodology, financial complex networks and clustering techniques are employed to measure the de-gree of recognition by creating links to the common stockholding behaviour of institutional investors. Besides, quarterly panel data from 2006 to 2020 are constructed for an innovative study of the degree of recognition of institutional investors’ strategy deviation of listed firms under different innovation fields, firm properties, and market style heterogeneity and asymmetry. The stability test is conducted by the transformation of the measures and methods, thereby effectively avoiding the “cluster fallacy”. We validate the mechanism by which the differences in strategic choices and propensities of listed firms affect capital market recognition, and enrich the microscopic research perspective and methodology on related issues.