Stock Market Investment Behavior Based on Behavioral Finance Based on Data Fusion Algorithm

The stock market is developing rapidly and the study of its investment behavior is indispensable. In this paper, based on the framework of fusion algorithm, information on various investor behaviors is federated based on IoT technology. Psychological experimental method is used to collect experimental sample data in the form of questionnaires. And based on the theoretical knowledge of behavioral finance, some investment recommendations on individual investors’ investment behavior are proposed. The results of this empirical study show that when individual investors face investment risks, the psychological bias of their perceptions is unfavorable to most of them. And the results prove that more than 50% of them are influenced by their own limited cognition.