Econometric analysis of volatile art markets
AbstractA 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.
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Bibliographic InfoPaper provided by Université catholique de Louvain in its series Open Access publications from Université catholique de Louvain with number info:hdl:2078.1/119711.
Date of creation: 2012
Date of revision:
Publication status: Published in Computational Statistics & Data Analysis (2012) v.56, p.3091-3104
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