Abstract
This paper studies the identification of financial fraud behaviors of listed companies by innovatively considering investors’ heterogeneous beliefs. Firstly, the relationship between them is investigated through a logistic regression model and the results show that investors’ heterogeneous beliefs have a significantly positive correlation with financial fraud. Moreover, after considering the indicators of investors’ heterogeneous beliefs, the financial fraud identification accuracies through six machine learning models have been improved, implying that the consideration of investors’ heterogeneous beliefs is meaningful for fraud identification. This gives hints that the regulators and investors can take utilization of investors’ heterogeneous beliefs when detecting financial fraud behaviors.
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