Forecasting Film Revenues Using GAMLSS

26th International Workshop on Statistical Modelling (IWSM), València, 2011

6 Pages Posted: 13 Mar 2011 Last revised: 11 Apr 2011

See all articles by Robert Gilchrist

Robert Gilchrist

London Metropolitan University

Dimitrios Stasinopoulos

London Metropolitan University

Robert Rigby

London Metropolitan University

John Sedgwick

London Metropolitan Business School

Vlasios Voudouris

ABM Analytics Ltd

Date Written: March 10, 2011

Abstract

This paper utilises the GAMLSS framework for the statistical modelling of movie box-office revenues. The dominant modelling paradigm of the film industry, traditionally exemplified by the nobody knows principle is based upon the infinite variance of the Pareto distribution. Using GAMLSS we have the flexibility to model up to 4 parameters of any distribution in terms of the avail- able explanatory variates, including a predictor that has smooth non-parametric functions. We here show that total box-office revenue can be better modelled by distributions with finite variance contradicting the Paretian hypothesis. Moreover the final version of the paper will illustrate that the Box-Cox power exponential distribution gives models where the parameters vary smoothly with an important explanatory variable, leading to the substantive conclusion that the post-opening revenue can, in fact, be explained by the opening box-office

Keywords: GAMLSS, film revenues, box-office revenues

Suggested Citation

Gilchrist, Robert and Stasinopoulos, Dimitrios and Rigby, Robert and Sedgwick, John and Voudouris, Vlasios, Forecasting Film Revenues Using GAMLSS (March 10, 2011). 26th International Workshop on Statistical Modelling (IWSM), València, 2011. Available at SSRN: https://ssrn.com/abstract=1782783 or http://dx.doi.org/10.2139/ssrn.1782783

Robert Gilchrist

London Metropolitan University ( email )

166-220 Holloway Road
London EC3N 2EY, N7 8HN
United Kingdom

Dimitrios Stasinopoulos

London Metropolitan University ( email )

166-220 Holloway Road
London EC3N 2EY, N7 8HN
United Kingdom

Robert Rigby

London Metropolitan University ( email )

166-220 Holloway Road
London EC3N 2EY, N7 8HN
United Kingdom

John Sedgwick

London Metropolitan Business School ( email )

London Metropolitan University
Holloway Road 271-280
LONDON, London N7 8HN
United Kingdom

Vlasios Voudouris (Contact Author)

ABM Analytics Ltd ( email )

Suite 17 125
145-157 St John Street
London, EC1V 4PW
United Kingdom

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