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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.

Summary Price indices for heterogeneous goods such as real estate or fine art constitute crucial information for institutional or private investors considering alternative investment decisions in times of financial markets turmoil. Classical mean‐variance analysis of alternative investments has been hampered by the lack of a systematic treatment of volatility in these markets. In this paper we propose a hedonic regression framework which explicitly defines an underlying stochastic process for the price index, allowing to treat the volatility parameter as the object of interest. The model can be estimated using maximum likelihood in combination with the Kalman filter. We derive theoretical properties of the volatility estimator and show that it outperforms the standard estimator. We show that extensions to allow for time‐varying volatility are straightforward using a local‐likelihood approach. In an application to a large data set of international blue chip artists, we show that volatility of the art market, although generally lower than that of financial markets, has risen after the financial crisis of 2008–09, but sharply decreased during the recent debt crisis. Copyright © 2013 John Wiley & Sons, Ltd.

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The price of wine is a key topic among market participants interested in valuing their stock, including dealers and restaurants, and consumers who may be interested in optimizing their purchases. A closely related issue, revaluation is the need to regularly update the value of a stock. This need is especially acute in the growing industry of wine as an investment. In this case, fair-value measurement is compulsory by law. We briefly review methods available to funds and introduce a new quantitative method aimed at achieving compliance with IFRS (International Financial Reporting Standard) 13 for fair valuation. Using auction data on 26,640 lots, we apply this method to compute the current fair value of a basket of 232 different wines. (JEL Classifications: C14, C43, Z11)