Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/239181
Authors: 
Kim, Jong-Min
Xia, Leixin
Kim, Iksuk
Lee, Seungjoo
Lee, Keon-Hyung
Year of Publication: 
2020
Citation: 
[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 13 [Year:] 2020 [Issue:] 5 [Pages:] 1-12
Abstract: 
Analyzing the success of movies has always been a popular research topic in the film industry. Artificial intelligence and machine learning methods in the movie industry have been applied to modeling the financial success of the movie industry. The new contribution of this research combined Bayesian variable selection and machine learning methods for forecasting the return on investment (ROI). We also attempt to compare machine learning methods including the quantile regression model with movie performance data in terms of in-sample and out of sample forecasting.
Subjects: 
quantile regression
neural network
machine learning
forecasting
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

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