We examine the annual returns based on auction data for two groups of artists (Surrealists and Impressionists) and two individual artists (Picasso and Renoir) using hedonic pricing models in combination with a wild bootstrap statistical technique. With this approach we estimate confidence intervals for such returns; we also estimate confidence intervals for the correlations with returns of other type of assets, and risk-return metrics.
We find that the confidence intervals associated with these figures of merit are so wide that it is difficult, if not impossible, to derive absolute conclusions or to make meaningful comparisons, with the behavior of other assets. We also observe that relying on single-point estimates of the above-mentioned metrics — without accounting for the corresponding confidence intervals — can lead to erroneous interpretations regarding art-market returns.
Moreover, our results suggest that previous studies regarding art market returns, their correlation with broader market indices, and their risk-return profiles, should be re-examined as they were based on single-point estimates of the relevant metrics. These findings might be of interest to researchers who use hedonic pricing models in the analysis of other infrequently traded assets as the number of sales/observations is likely to be rather low.
Charlin, Ventura, and Arturo Cifuentes. "The Art Market: What Do We Know About Returns?" Columbia Business School, September 1, 2015.
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