期刊
INFORMATION PROCESSING & MANAGEMENT
卷 60, 期 5, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ipm.2023.103448
关键词
Investor Trust; Qualitative Simulation; Fuzzy Mathematics; Cusp Catastrophe Model
In recent years, investors have become overly reliant on intelligent systems, leading to polarization and frequent reversal of their behavior. This study used qualitative simulations and catastrophe theory to construct a model of investor behavior based on sentiment, confidence, and behavior changes. The results show that neutral-type investors are more influenced by information push from intelligent systems, resulting in drastic behavioral changes. Even if the direction of change in an investor's internal trust level is inconsistent with external disturbances, catastrophe behavior can still occur. This research lays the foundation for guiding and controlling investor behavior in the intelligent era.
In recent years, investors have benefited from the convenience of intelligent recommendation information push, but have exhibited over-dependence on intelligent systems. In some scenarios, investors' trust and behavioral decisions are even dominated by information provided by the intelligent environment, which can lead to polarization and frequent reversal of investor behavior. To explore the mechanism of this frequent change, this work combined qualitative simulations with catastrophe theory, and used text data on investor sentiment, confidence, and behavior changes to construct a catastrophe model of investor behavior. The results show that neutral-type investors are more likely to be affected by information push under the dominance effect of intelligent systems, which results in catastrophe in behavior. Meanwhile, due to the dominance of the intelligent system for some investors, even if the direction of change of the investor's internal trust level is inconsistent with the external situational disturbance, it may still lead to catastrophe behavior. Finally, the catastrophe region of investor behavior is explored through an in-depth analysis of fitted catastrophe model parameters. This can lay the foundation for financial institutions' guidance mechanisms and control strategies for investor behavior in the intelligent era.
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