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NYU Stern Professor Sam Hui Creates New Model to Predict Box Office Revenue from Movie Scripts 

Statistics show that green-lighting a movie script that fails to produce profits at the box office can lead to financial ruin for studios – close to negative 50% ROI for unsuccessful films.

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This research is the first step toward providing investors and hedge fund managers investing in movie production with a reliable framework to determine the likelihood of success for each screenplay and to optimally select a film production portfolio based on their risk preferences.

On the upside, box office hits can produce more than 200% ROI.

In a recent study, Professor of Marketing Sam Hui, and colleagues Jehoshua Eliashberg and John Zhang of the Wharton School at the University of Pennsylvania, developed a new and reliable screening method to choose movie scripts that will outperform the market.

Over the course of six years, the researchers studied 200 scripts, examining features including genre, content, semantics and the use of specific words, in relation to box office revenue and production budgets. The study shows how textual information from movie scripts can help predict revenues.

Using textual information from scripts in their predictive model, Hui and his co-authors were able to accurately forecast ROI for both box office hits and flops. For example, looking at the script from the smash hit Hotel Rwanda, the researchers’ estimates were within 4% of the actual box office revenue. Similarly, with the flop Batman and Robin, the model predicted its failure within 5% of the film’s actual returns.

Underlining the model’s continued relevance, Hui explains: “If we applied this model to today’s newest movie scripts, we can differentiate between movies that are likely to be successful and those that are not.”

Additional research findings include:

  • "Family" and "Comedy" genre films fare the best in terms of risk-adjusted ROI

  • "Horror" movies are the worst performers in terms of risk-adjusted ROI

  • "Rated-R" films, in general, have a lower risk-adjusted ROI then "non-R" rated movies

In their paper, “Green-lighting Movie Scripts: Revenue Forecasting and Risk Management,” the authors identify several problems with the current approach that studios use to evaluate scripts.

“The current evaluation process includes several stages of readers, and results in not only a high level of uncertainty, but a large strain on monetary and human resources as well,” says Hui.

Hui also underscores the importance of this research for a film’s financial backers: “This research is the first step toward providing investors and hedge fund managers investing in movie production with a reliable framework to determine the likelihood of success for each screenplay and to optimally select a film production portfolio based on their risk preferences.”

To read the full paper, click here.

To speak with Professor Sam Hui, please contact him directly at 212-998-0551, khui@stern.nyu.edu; or contact Carolyn Ritter in NYU Stern’s Office of Public Affairs, 212-998-0624, critter@stern.nyu.edu.