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Application of deep learning in recognition of accrued earnings management

We choose the sample data in Chinese capital market to compare the measurement effect of earnings management with Deep Belief Network, Deep Convolution Generative Adversarial Network, Generalized Regression Neural Network and modified Jones model by performance. We find that Deep Belief Network has...

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Detalles Bibliográficos
Autores principales: Li, Jia, Sun, Zhoutianyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9976311/
https://www.ncbi.nlm.nih.gov/pubmed/36873477
http://dx.doi.org/10.1016/j.heliyon.2023.e13664
Descripción
Sumario:We choose the sample data in Chinese capital market to compare the measurement effect of earnings management with Deep Belief Network, Deep Convolution Generative Adversarial Network, Generalized Regression Neural Network and modified Jones model by performance. We find that Deep Belief Network has the best effect, while Deep Convolution Generative Adversarial Network has no significant advantage, and the measurement effect of Generalized Regression Neural Network and modified Jones model have little difference. This paper provides empirical evidence that neural networks based on deep learning technology and other artificial intelligence technologies can be widely applied to measure earnings management in the future.