Research On The Evaluation Of Film Copyright Value Income Method

The film industry is the most important part of the entertainment industry.The film copyright value evaluation system still has deficiencies.Improving the value evaluation system of movie copyright can provide a value basis for film producers to project in the movie theater,and it is also conducive to provide value basis for film companies to obtain financing before the movie is released.This article first sorts out the literature on the evaluation of film copyright and the factors affecting the box office and the prediction model.In terms of box office revenue prediction,scholars mainly use multiple linear regression models and neural network algorithms.The accuracy of these model predictions needs to be improved in the case of uneven distribution of box office revenue in movie sample data;in the determination of royalty rate,scholars mainly use the industry average rate,without considering the differences between different movies;in terms of the determination of the income period,scholars mainly compare the income period of the evaluated movie and the historical movie income period of the same period to determine the estimated movie income period,the accuracy has room for improvement;regarding the determination of the discount rate,scholars mainly use the risk accumulation method and the capital asset pricing method,determining individual risk is a little subjective.Then it introduces the theory of film copyright in terms of its connotation and its value evaluation characteristics,the income evaluation method of film copyright and the GBRT algorithm.Then the paper selected 368 movie data from 2011 to 2018 for movie box office revenue prediction,including the selection of 21 box office income influencing factors and the construction of movie box office revenue prediction models.Among them,the movie box office revenue prediction models include multiple linear regression model and GBRT model using huber loss function.The next part explores the royalty rate,income period and discount rate of Relief-from-Royalty Method.The final part applies the GBRT model using huber loss function to predict the box office income and royalty rate of the case movie,analyze whether the case movie key is extended according to the predicted box office performance,determine the case movie copyright income period and use the factor analysis method to figure out individual risk in the discount rate of the case movie and industry sample movie.The discount rates are compared and determined,and the value of the copyright of the case movie "Climber" is evaluated using the Relief-from-Royalty Method.The results of this paper show that: First,GBRT model using huber loss function is more accurate than the multiple linear regression model in predicting box office income and royalty rate.The royalty rate is positively related to movie box office revenue,and the factors affecting movie box office revenue will also have an impact on movie royalty rate.Variables affecting the box office and royalty rate of movies differ in importance.The variables that are more important for movie box office are projection numbers,number of screens,Baidu search index,IMAX,distribution company,and plot;the variables that are more important for movie royalty rate are projection numbers,number of screens,Baidu search index,rating,director Likes and IMAX.Projection numbers is the most important factor affecting both movie box office revenue and movie royalty rate.Second,whether the movie key is extended is related to the performance of the box office of the movie.A movie that performs well at the box office is more likely to obtain a key extension,and the total release period of the movie,that is,the income period of the movie’s copyright will be greater.Third,the individual risk of movie related to the determination of the discount rate of movie copyright can be analyzed from three aspects: production risk,consumption risk and reputation risk.Using factor analysis method to calculate individual risk can finally conclude that the individual risk of case movie is smaller than the individual risk of industry sample movies.