Research on Accounting Information Quality Evaluation Model of Listed Companies from the Perspective of Differentiated Machine Learning

Peitian Su; Hongtao Rong; Guo Xiang; Danfeng Huang

doi:10.6911/

Authors

Peitian Su School of Economics and Management, Guangzhou Institute of Science and Technology, Guangzhou, China
Hongtao Rong School of Economics and Management, Guangzhou Institute of Science and Technology, Guangzhou, China
Guo Xiang School of Economics and Management, Guangzhou Institute of Science and Technology, Guangzhou, China
Danfeng Huang School of Business Administration, Huaqiao University, Quanzhou, China

DOI:

https://doi.org/10.6911/

Keywords:

Listed company; accounting information quality; random forest; convolutional neural network; long short-term memory network.

Abstract

Developing quantitative tools to evaluate the accounting information quality of listed companies is of great value for in- vestors' risk prevention. Based on the selection of multi-dimensional factors affecting the accounting information quality , the random forest model is used to screen the importance , and then the accounting information quality evaluation system is built. At the same time , based on convolutional neural netowrk long short-term memory (CNN-LSTM) method , the evaluation model of accounting information quality is constructed , and the good performance of the model in the evaluation of accounting informa- tion quality is proved.

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