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Econometric analysis of volatile art markets

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  • Bocart, Fabian
  • Hafner, Christian

Abstract

A new heteroskedastic hedonic regression model is suggested. It takes into account time-varying volatility and is applied to a blue chips art market. Furthermore, a nonparametric local likelihood estimator is used. This estimator is more precise than the often used dummy variables method. The empirical analysis reveals that errors are considerably non-Gaussian, and that a student distribution with time-varying scale and degrees of freedom does well in explaining deviations of prices from their expectation. The art price index is a smooth function of time and has a variability that is comparable to the volatility of stock indices.
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  • Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  • Handle: RePEc:aiz:louvar:2012020
    Note: In : Computational Statistics and Data Analysis, vol. 56, no. 11, p. 3091-3104 (2012)
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    Cited by:

    1. Bocart, Fabian Y.R.P. & Hafner, Christian M., 2012. "Econometric analysis of volatile art markets," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3091-3104.
    2. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
    3. Kim Oosterlinck, 2017. "Art as a Wartime Investment: Conspicuous Consumption and Discretion," Economic Journal, Royal Economic Society, vol. 127(607), pages 2665-2701, December.
    4. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    5. Dominik Filipiak & Agata Filipowska, 2016. "Towards data oriented analysis of the art market: survey and outlook," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 12(1), pages 21-31, June.
    6. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. David Chambers & Elroy Dimson & Christophe Spaenjers, 0. "Art as an Asset: Evidence from Keynes the Collector," Review of Asset Pricing Studies, Oxford University Press, vol. 10(3), pages 490-520.
    8. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2016. "Equilibrium Pricing in Incomplete Markets Under Translation Invariant Preferences," Mathematics of Operations Research, INFORMS, vol. 41(1), pages 174-195, February.
    9. Vecco, Marilena & Zanola, Roberto, 2017. "Don’t let the easy be the enemy of the good. Returns from art investments: What is wrong with it?," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 120-129.
    10. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • Z11 - Other Special Topics - - Cultural Economics - - - Economics of the Arts and Literature

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