Movie Box Office Inteval Forecasting Based on CART

This paper constructs a model for the forecasting of movie box office revenues during the pre-production period. Our study selects some basic variables in film forecasting field such as production country, genre, seasonality and star value. This paper divides the box office revenue into seven intervals ranged from ´flop´ to ´blockbuster´ and chooses Classification and Regression Tree to predict box office in China by comparing different models. The study sets the top 100 films of 2014 in box revenues as the training set and the top 50 films of the former 5 months in 2015 as the testing set. The model produces excellent forecasting accuracy in both training and testing sets. In our model, the fitting degree of training set is 99%, and the prediction accuracy value is 76%. The importance of variables indicates that the appeal of directors and stars is notable in China.