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Econometric analysis of volatile art markets

Fabian Y. R. P. Bocart and Christian Hafner ()

SFB 649 Discussion Papers from Humboldt University, Collaborative Research Center 649

Abstract: A new heteroskedastic hedonic regression model is suggested which takes into account time-varying volatility and is applied to a blue chips art market. A nonparametric local likelihood estimator is proposed, and this 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.

Keywords: Volatility; art markets; hedonic regression; semiparametric estimation (search for similar items in EconPapers)
JEL-codes: C14 C43 Z11 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2011-10
New Economics Papers: this item is included in nep-cul and nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Related works:
Journal Article: Econometric analysis of volatile art markets (2012) Downloads
Working Paper: Econometric analysis of volatile art markets (2012)
Working Paper: Econometric analysis of volatile art markets (2011) Downloads
Working Paper: Econometric analysis of volatile art markets (2011) Downloads
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