A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Filipiak, Dominik; Filipowska, Agata Article Towards data oriented analysis of the art market: Survey and outlook e-Finanse: Financial Internet Quarterly Provided in Cooperation with: University of Information Technology and Management, Rzeszów Suggested Citation: Filipiak, Dominik; Filipowska, Agata (2016) : Towards data oriented analysis of the art market: Survey and outlook, e-Finanse: Financial Internet Quarterly, ISSN 1734-039X, University of Information Technology and Management, Rzeszów, Vol. 12, Iss. 1, pp. 21-31, http://dx.doi.org/10.14636/1734-039X_12_1_003 This Version is available at: http://hdl.handle.net/10419/197424 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. 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Determining the defi niti on of the arti sti c value or formalisati on of appraisal may be considered quite complex. Stati sti cal analysis, econometric methods or data mining techniques could pave the way towards bett er understanding of the me- chanisms occurring on the art market. The goal of this paper is to identi fy, describe and compare soluti ons (and related challenges) that help to analyse, make decisions and defi ne state of the art in the context of the intersecti on of econometrics on art markets and computer science. This work is also a starti ng point for further research. JEL classifi cati on: : C43, C51, G11, Z11 Keywords: art market analysis, hedonic regression Received: 01.08.2015 Accepted: 14.03.2016 1 Department of Informati on Systems, Poznań University of Economics, e-mail: dominik.fi [email protected]. 2 Department of Informati on Systems, Poznań University of Economics, e-mail: agata.fi [email protected]. www.e- nanse.com University of Information Technology and Management in Rzeszów 21 Dominik Filipiak, Agata Filipowska „e-Finanse” 2016, vol. 12 / nr 1 Towards data-oriented analysis of the art market: survey and outlook trend. Among various machine learning methods, there I is one especially used in art market research. Regression Platt ner (1998) has writt en about a market where analysis is a key technique due to its impact on building producers don’t make work primarily for sale, where price indices describing the whole market. Nevertheless, buyers oft en have no idea of the value of what they buy, some other methods are also used. and where middlemen routi nely claim reimbursement Identi fying trends or measuring the market seems for sales of things they’ve never seen to buyers they’ve to play the most important role in art market analysis. never dealt with. Although the art market connotes Art market research on the Internet can follow two mostly Christi e’s and Sotheby’s duopoly, a vast amount of approaches. The fi rst considers manually browsing primary and secondary market dealers is present in private historical sales records, provided by various services. The galleries, aucti on houses or on the Internet. Bidding second, which in fact has its roots in the fi rst approach, results are oft en presented by aucti on houses, whereas relies on various art market indices. In this work we prices in private galleries usually remain unpublished. present the current state of art research on methods for Usage of the Internet, on the contrary, is sti ll relati vely descripti on of the art market, taking into account recent small by this conservati ve market. This paper is focused developments in econometrics and computer science. on aucti on houses and regards mainly painti ngs among Possible further research directi ons are also outlined. other collecti bles. Here, sold lots are oft en classifi ed at This paper is organised as follows. First of all, the aucti ons (like old masters or contemporary art). art market is briefl y depicted. Then, Internet aucti on Treati ng art primarily as an asset may be controversial databases, which can help to minimise the informati on in, generally, two ways. First of all, considering it as an asymmetry to improve market transparency, are investment may raise some philosophical questi ons about described. The next secti on sheds light on price indices the purpose of art and moneti sing invaluable features or (commercial as well as those sprung from scienti fi c the relati on between an arti sti c value and a fi nal price. research) and all underlying calculati ons. Then, a direct Secondly, studies on the art market have fostered a debate usage of computer science methods for art market on potenti al returns. While people may be overwhelmed analysis is described. The last part of this paper consists by an amount of money spent during Christi e’s or of a concise discussion and summary. Sotheby’s aucti ons, some researches argue that investi ng in art yields generally low returns (Baumol, 1986; Frey & Pommerehne, 1989). More recent fi ndings say that A P D returns from art were close to the total return measured One of the most straight-forward approaches to by S&P500 between 2003 and 2013. Especially post- invest in art is to pick a potenti ally interesti ng arti st war or contemporary and traditi onal Chinese artworks and check their prices on past aucti ons. Intuiti vely, were among the best investments, delivering compound soaring trends may be considered an indicator of a good annual returns of respecti vely 10.5% and 14.9% (Deloitt e investment. Although sti cking only to increases may not & ArtTacti c, 2015). be the best strategy1, these databases are a valuable As a consequence of this ongoing debate, there is an source of informati on. The introducti on of Artnet in 1995 increasing number of research initi ati ves focused on the increased the number of possible art investors by making art market. Diff erent approaches and methods to measure aucti on sales data available (Coslor & Spaenjers, 2013). trends, performance and value have been studied. Despite This secti on describes some of the most popular art an appraisal based on art history knowledge, a wide range market databases. of methods stemming from econometrics and stati sti cs A wide range of prices may seem confusing, therefore were described in the literature. Data processing, analysis it is necessary to disti nguish each one by introducing and visualisati on have gained special att enti on in the the following glossary. Asking price is a threshold from 21st century and these techniques are applied in a wide which bidding for a given lot starts. Some aucti on houses variety of domains. Even though relati vely unexplored provide esti mati ons (low and high) to make potenti al in that manner, the art market is no excepti on to that 1 The „Damien Hirst Bubble” may be a good example: htt p://www. bloomberg.com/bw/articles/2012-11-21/for-collectors-with-hirst-co- mes-pain. www.e- nanse.com 22 University of Information Technology and Management in Rzeszów Dominik Filipiak, Agata Filipowska „e-Finanse” 2016, vol. 12 / nr 1 Towards data-oriented analysis of the art market: survey and outlook buyers aware of possible prices. Reserve price represents com). a confi denti al price agreed upon by the seller and aucti on house. To sell a lot, at least a set reserve price has to be reached. Hammer price is a winning bid price. Premium I price is equal to the sum of the hammer price and all fees and charges defi ned by the aucti on house. During an The main purposes of calculati ng price indices aucti on, a lot can be sold or bought in, which means that are measuring fi nancial performance, evaluati ng there were no bids or it has failed to reach a reserve price. diversifi cati on of a potenti al portf olio and describing The following list presents the most popular art trends on the market. Ginsburgh, Mei, and Moses (2006) market databases: outline the most important uses for art market indices, which are describing market trends, measuring volati lity, 1) ArtPrice Probably the largest database of past and searching for economic incenti ves infl uencing market aucti ons, ArtPrice (htt p://www.artprice.com/) off ers and an appraisal. access to 30,000,000 prices and indices for about 600,000 arti sts. Data is gathered from around 4500 aucti on Conventi onal price index methodologies are generally houses.