CORPORATE STRATEGY DEVIATION AND INSTITUTIONAL INVESTOR RECOGNITION: COMPLEX NETWORK-BASED AND GRAPH CLUSTERING ANALYSIS
利用金融复杂网络和聚类技术，基于2006-2020年季度面板数据，量化分析上市公司战略偏离如何影响机构投资者的认可程度，并考察不同创新领域、企业属性和市场风格下的异质性。
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.