Machines and Masterpieces: Predicting Prices in the Art Auction Market
| Autor: | Roman Kräussl, Gustavo Manso, Mathieu Aubry, Christophe Spaenjers |
|---|---|
| Přispěvatelé: | Laboratoire d'Informatique Gaspard-Monge (LIGM), Centre National de la Recherche Scientifique (CNRS)-Fédération de Recherche Bézout-ESIEE Paris-École des Ponts ParisTech (ENPC)-Université Paris-Est Marne-la-Vallée (UPEM), Department of Economics, Tilburg University [Netherlands], HEC Research Paper Series, Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC)-ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
asset valuation
History Polymers and Plastics Computer science Big data Machine learning computer.software_genre Industrial and Manufacturing Engineering big data 0502 economics and business Common value auction Price level auctions 050207 economics Business and International Management JEL: C - Mathematical and Quantitative Methods/C.C5 - Econometric Modeling/C.C5.C50 - General Valuation (finance) JEL: D - Microeconomics/D.D4 - Market Structure Pricing and Design/D.D4.D44 - Auctions 050208 finance Artificial neural network Ex-ante business.industry 05 social sciences experts Hedonic pricing TheoryofComputation_GENERAL JEL: Z - Other Special Topics/Z.Z1 - Cultural Economics • Economic Sociology • Economic Anthropology/Z.Z1.Z11 - Economics of the Arts and Literature machine learning [SHS.GESTION]Humanities and Social Sciences/Business administration Artificial intelligence business computer JEL: G - Financial Economics/G.G1 - General Financial Markets/G.G1.G12 - Asset Pricing • Trading Volume • Bond Interest Rates |
| Popis: | We study the accuracy and usefulness of automated (i.e., machine-generated) valuations for illiquid and heterogeneous real assets. We assemble a database of 1.1 million paintings auctioned between 2008 and 2015. We use a popular machine-learning technique - neural networks - to develop a pricing algorithm based on both non-visual and visual artwork characteristics. Our out-of-sample valuations predict auction prices dramatically better than valuations based on a standard hedonic pricing model. Moreover, they help explaining price levels and sale probabilities even after conditioning on auctioneers' pre-sale estimates. Machine learning is particularly helpful for assets that are associated with high price uncertainty. It can also correct human experts' systematic biases in expectations formation - and identify ex ante situations in which such biases are likely to arise. |
| Databáze: | OpenAIRE |
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