Econometric analysis of volatile art markets
(2012) Computational Statistics & Data Analysis — Vol. 56, n° 11, p. 3091-3104 (2012)
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- 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.
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Citations
Bocart, F., & Hafner, C. (2012). Econometric analysis of volatile art markets. Computational Statistics & Data Analysis, 56(11), 3091-3104. https://doi.org/10.1016/j.csda.2011.10.019 (Original work published 2012)