Growth Enterprise Value Assessment Based on RF-BP Neural Network

2019 2nd International Conference of Green Buildings and Environmental Management

生态环境科学

Zheng, Yuhang^1 ; Duan, Yinying^1

School of Business, Sichuan Agricultural University, Chengdu, Sichuan, China^1

关键词: BP neural networks;    Enterprise values;    Evaluation methods;    Growth enterprise markets;    Historical data;    Learning abilities;    Neural network training;    Training and testing;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/310/5/052043/pdf
DOI  :  10.1088/1755-1315/310/5/052043

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Enterprise value assessment is an important prerequisite for company activities including listings, mergers, and acquisitions. In order to overcome the limitations of the methods including income method, market law, and to improve the accuracy of enterprise value assessment, this research has used the historical data of 164 growth/developing companies listed on the Growth Enterprise Market (GEM) to conduct neural network training, so as to explore the accuracy and applicability of the evaluation methods of enterprise value based on deep learning. The most important five types of indicators from many indicators were firstly selected with the random forest (RF) algorithm, then used as neural network input neurons. Meanwhile, in order to improve the learning ability of the neural network, this study has used RMSProp algorithm to rectify the node weights and offsets, which reduces the problem that the neural network may fall into the local minimum. The results gained from the training and testing of the data show that the method has high accuracy.