Research Article
Corporate Performance Prediction Based on BP Neural Network
@INPROCEEDINGS{10.4108/eai.6-1-2023.2330321, author={Hongyan Ye}, title={Corporate Performance Prediction Based on BP Neural Network}, proceedings={Proceedings of the 2nd International Conference on Big Data Economy and Digital Management, BDEDM 2023, January 6-8, 2023, Changsha, China}, publisher={EAI}, proceedings_a={BDEDM}, year={2023}, month={6}, keywords={top management team characteristics r\&d investment corporate performance bp neural network}, doi={10.4108/eai.6-1-2023.2330321} }- Hongyan Ye
Year: 2023
Corporate Performance Prediction Based on BP Neural Network
BDEDM
EAI
DOI: 10.4108/eai.6-1-2023.2330321
Abstract
Top Management Team (TMT), as the most important presence in corporate decision-making, is an integral part of corporate research. Its impact on corporate performance is a topic that cannot be ignored. This paper uses earnings per share (EPS) to represent corporate performance, and the shareholding ratio of executives (SHARE) is used as TMT characteristics. Based on the BP neural network, the input layer of the model is set as five nodes, the implied layer as two nodes, and the output layer as one node. We use 75% of the data of listed information technology companies from 2017-2019 as the training set to derive the performance prediction model. In this study, 25% of the test set is used to validate the final valid performance prediction model obtained. This study integrates TMT characteristics into predicting corporate performance, helping to optimize the non-economic indicators used to assess and predict corporate performance.
