Art as an Investment and the Underperformance of Masterpieces
By Jiang Mei, Michael J. Moses. 2002
498 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience, Finance, Visual Arts and Performing Arts
View Paper: https://www.semanticscholar.org/paper/ac7b1a85db923965d5f229cfda92ab4f24509f6d
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Citations in the corpus
- Does it Pay to Invest in Art? A Selection-Corrected Returns Perspective (2013, background): “…recent studies have found that there may be value in including art in investment portfolios, partly due to its low - or even negative - correlation with other asset classes (see the review in Ashenfelter and Graddy, 2003, and recent work by Mei and Moses, 2002, and Taylor and Coleman, 2011).”
- Art as an Investment and Conspicuous Consumption Good (2009, background): “…on sale and there may be a relationship between value increases and the occurrence of a transaction).8 With this in mind, I focus on the long-run return measures of “paintings in general,” including Mei and Moses (2002), to gauge the upper bound of the expected unconditional return on art assets.”
- Modeling On-Line Art Auction Dynamics Using Functional Data Analysis (2006, background): “Research on art has mostly concentrated on price formation at traditional auctions and art’s potential as an investment [1, 2, 9, 19, 23].”
- Buying Beauty: On Prices and Returns in the Art Market (2013, unknown): “In contrast, at first sight, the results seem at odds with the finding of Mei and Moses (2002) that masterpieces underperform – an issue that we turn to next.”
- The Price of Wine (2015, unknown): “Our work is in the spirit of recent research on the performance of other emotional assets such as art (e.g., Goetzmann, 1993; Mei and Moses, 2002), stamps (Dimson and Spaenjers, 2011), or violins (Graddy and Margolis, 2011).”
- Art and Money (2011, unknown): “In contrast, however, Mei and Moses (2002) report a correlation coefficient of not more than 0.04 between the S&P 500 and their art index (annual real returns, 1950-1999).”
- Anchoring Effects: Evidence from Art Auctions (2009, background): “While there are some datasets, such as the dataset put together by Mei and Moses (2002), that deal with large numbers of repeat sales over huge expanses of time in varied locations, the large time intervals in their dataset between sales make it likely that the seller is not the same person that…”