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Modelling the financial risk associated with U.S. movie box office earnings

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  • Bi, Guang
  • Giles, David E.

Abstract

In this paper we use extreme value theory to model the U.S. movie box office returns, using weekly data for the period January 1982 to September 2006. The Peak over Threshold method is used to fit the Generalized Pareto distribution to the tails of the distributions of both positive weekly returns and negative returns. Tail risk measures such as value at risk and expected shortfall are computed using maximum likelihood methods. These measures can be used as indicators for the film distributors in the preparation of movie prints, or as references for actual or potential investors in the movie industry.

Suggested Citation

  • Bi, Guang & Giles, David E., 2009. "Modelling the financial risk associated with U.S. movie box office earnings," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2759-2766.
    • Handle: RePEc:eee:matcom:v:79:y:2009:i:9:p:2759-2766
    DOI: 10.1016/j.matcom.2008.04.014
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    References listed on IDEAS

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    1. Danielsson, J. & de Haan, L. & Peng, L. & de Vries, C. G., 2001. "Using a Bootstrap Method to Choose the Sample Fraction in Tail Index Estimation," Journal of Multivariate Analysis, Elsevier, vol. 76(2), pages 226-248, February.
    2. Manfred Gilli & Evis këllezi, 2006. "An Application of Extreme Value Theory for Measuring Financial Risk," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 207-228, May.
    3. Gencay, Ramazan & Selcuk, Faruk, 2006. "Overnight borrowing, interest rates and extreme value theory," European Economic Review, Elsevier, vol. 50(3), pages 547-563, April.
    4. Jondeau, E. & Rockinger, M., 1999. "The Tail Behavior of Sotck Returns: Emerging Versus Mature Markets," Working papers 66, Banque de France.
    5. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    6. repec:adr:anecst:y:2000:i:60:p:10 is not listed on IDEAS
    7. Jon Danielsson & Casper G. De Vries, 2000. "Value-at-Risk and Extreme Returns," Annals of Economics and Statistics, GENES, issue 60, pages 239-270.
    8. Gencay, Ramazan & Selcuk, Faruk & Ulugulyagci, Abdurrahman, 2003. "High volatility, thick tails and extreme value theory in value-at-risk estimation," Insurance: Mathematics and Economics, Elsevier, vol. 33(2), pages 337-356, October.
    9. Longin, Francois M, 1996. "The Asymptotic Distribution of Extreme Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 69(3), pages 383-408, July.
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    Cited by:

    1. Jordi McKenzie, 2023. "The economics of movies (revisited): A survey of recent literature," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 480-525, April.
    2. Ledermann, Daniel & Alexander, Carol, 2012. "Further properties of random orthogonal matrix simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 83(C), pages 56-79.
    3. Saralees Nadarajah & Bo Zhang & Stephen Chan, 2014. "Estimation methods for expected shortfall," Quantitative Finance, Taylor & Francis Journals, vol. 14(2), pages 271-291, February.

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