This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

How to Predict a Movie's Success at the Box Office

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Ramesh Sharda
Dursun Delen
Abstract

Sharda and Delen describe the widely publicized and very successful model they have created to predict the financial performance of a movie before its release to the theaters. Based on neural networks, the model attempts to classify a movie into one of nine categories, ranging from a "flop' to a "blockbuster." Key factors used in the classification include MPAA rating, expected release month, star value, genre, level of special/technical effects, number of screens the movie is expected to open on, and whether or not it is a sequel. Examples of blockbuster movies that the model predicted correctly include Spiderman, Star Wars: Episode II, Harry Potter and the Sorcerer's Stone, Lord of the Rings: The Fellowship of the Ring, and Shrek. The model missed by under predicting the blockbuster success of My Big Fat Greek Wedding and by predicting success for Waterworld, which fell short. Copyright International Institute of Forecasters, 2006

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help file. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.forecasters.org/foresight/purchase.html
File Format:
File Function:
Download Restriction: no

Publisher Info
Article provided by International Institute of Forecasters in its journal Foresight: The International Journal of Applied Forecasting.

Volume (Year): (2006)
Issue (Month): 5 (Fall)
Pages: 32-36
Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Handle: RePEc:for:ijafaa:y:2006:i:5:p:32-36

Contact details of provider:
Web page: http://www.forecasters.org/
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Pam Stroud).

Related research
Keywords:

Statistics
Access and download statistics

Did you know? About 2000 working paper series are listed on RePEc.

This page was last updated on 2008-7-16.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.