Research On Equity Value Evaluation Of Film And Television Enterprises Based On BP Neural Network

With the deepening of the cultural system reform and the continuous development and progress of social economy and technology,people’s pursuit of spiritual culture is increasing and their consumption habits of film and television entertainment products have gradually developed.In this backdrop,the film and television industry is facing a crisis at the same time as its rapid development.With the arrival of 2021,the winter period of the film and television industry is over and the whole industry starts a new round of healthy growth.Whether it is listing,bond financing,M&A during the boom period,or restructuring and liquidation during the winter period,all kinds of business activities conducted by film and TV enterprises are inseparable from reasonable valuation.However,the uniqueness of film and television enterprises results in the lack of appropriate valuation methods to accurately assess their value.The mainstream valuation methods are based on certain assumptions,while film and TV enterprises are heavy on intangible assets and light on tangible assets,the industry is greatly influenced by policies,economy and audience preferences,and the business cycle and operating conditions of enterprises are highly uncertain,all of which eventually lead to the inapplicability of mainstream valuation methods and difficulties in value assessment.Therefore,it is of practical and theoretical significance to study the valuation methods of film and television enterprises.Combining relevant domestic and foreign research,we take value chain theory and efficient market theory as the theoretical support.This thesis establishes a value chain-based evaluation index system with the characteristics of film and television enterprises,constructs an evaluation model of the equity value of film and television enterprises using a modified BP neural network,and conducts an empirical analysis with listed film and television enterprises as a sample.The following conclusions were drawn from the research and analysis of this thesis:(1)The film and television enterprise value evaluation model constructed based on modified BP neural network can make up for the shortcomings of traditional evaluation methods,and is a better improvement method especially for the market approach.When the market approach is applied in the film and television industry,it faces the disadvantages of few comparable enterprises,difficult to determine comparable indicators,and the assessment results are greatly influenced by subjectivity.Through the simulation of nonlinear relationships by neural networks,the traditional market approach’s assumption of linear correlation between comparable indicators and enterprise value is broken through,making the restrictions for determining comparable enterprises greatly reduced and more enterprises in the industry can be used for assessment comparison.At the same time,through the systematic and comprehensive selection of indicators and the intelligent calculation in the assessment,the problem that comparable indicators are difficult to represent enterprises can be solved as well as the influence of subjectivity in the valuation can be avoided.(2)From the fitting results obtained after training and testing of the BP neural network,it is clear that there is indeed a nonlinear relationship between evaluation indexes selected in this thesis from the value chain of film and television enterprises and the value of film and television enterprises.(3)Compared with methods such as real option pricing models,BP neural networks do not have too many strict prerequisites and the valuation results will not be affected by the constraints.And after the empirical analysis,it is concluded that the modified BP neural network is accurate in assessing the equity value and can be used by appraisers,managers,and investors as a supplement to the valuation results obtained by the mainstream methods.