Font Size: a A A

Valuation Of Artificial Intelligence Enterprises Based On RBF-EVA Method

Posted on:2020-11-03Degree:MasterType:Thesis
Country:ChinaCandidate:Y J HaoFull Text:PDF
GTID:2439330578970216Subject:Asset Assessment
Abstract/Summary:PDF Full Text Request
At present,China is facing with economic restructuring,vigorously developing artificial intelligence industriesrstrengthening the development of artificial intelligence industry to drive economic transformation through industrial upgrading.The artificial intelligence enterprises continues to increase,facing a series of economic activities uch as mergers,listings,and restructurings,which need to be supported by scientific valuation methods.This paper analyzes the development status of China's artificial intelligence industry and finds that the development of artificial intelligence enterprises has good policies and investment and financing advantages.Due to the instability of the future earnings of artificial intelligence enterprises,this paper sdects the EVA(Economic Value Added)method to evaluate the enterprise value of the enterprise,and uses the RBF(Radial Basis Function)neural network model to optimize the traditional EVA method to obtain the evaluation result that can better reflect the intrinsic value of the enterprise.From the perspectives of technical dimensions,product and industry dimensions and historical performance,this paper selects Dahua.Hikvision,Jiadu Technology.Keda Xunfei,Keda Intelligence,Saiwei Intelligent,Tuols and Robots as Artificial Intelligence cases.The historical EVA of the eight case companies from 2008 to 2017 was calculated.The results show that the historical EVA of artificial intelligence enterprises shows nonlinear fluctuations,which is inconsistent with the assumption of fixed growth rate in the traditional EVA model.This paper proposes to use RBF neural network to predict the future EVA of artificial intelligence enterprises.In this paper,historical EVA of eight artificial intelligence enterprises is trained and tested.The results show that the average error of the predicted EVA in 2017 with fixed growth rate is 21.231%.and the average prediction error of RBF neural network is 9.746%,using RBF neural network model.Forecasting future EVA is better than predicting at a fixed growth rate.This paper constructs the RBF-EVA enterprise valuation model,evaluating the value of 8 artificial intelligence enterprises,and compares the results with the enterprise value evaluation under the four traditional EVA methods.The results show that the fixed growth model is not suitable for the artificial intelligence enterprises at the current stage.The artificial intelligence enterprise value evaluation under the zero growth model will lead to the underestimation of the enterprise value.Under the two-stage and three-stage growth models,the artificial intelligence enterprise value will be overestimated.The risk of the artificial intelligence enterprise value evaluation under the RBF-EVA model has relatively low requirements for the accuracy of the evaluation parameters,and can more truthfully reflect the value of the artificial intelligence enterprise.
Keywords/Search Tags:EVA, Valuation, Artificial Intelligence Enterprises, RBF Neural Network
PDF Full Text Request
Related items