Art as an Asset Class
Ms. Luisa Ann Rubino 2001 MBA
Gustav Klimt, "The Kiss"
Primary Address (Home)
Via G. Meda 28
MILANO 20141
ITALY
Phone: 39-335-498003
LUISA.RUBINO@ALUMNI.DUKE.EDU
Introduction
The goal of this study is to analyze art as an asset class. Specifically, I intend to
investigate the risk/reward profile of art and the size of its risk-adjusted appreciation
("alpha"). I will also determine art's correlation with known benchmarks, its performance
in "down markets", and therefore its ability to add diversification in a portfolio. Finally, I
will examine the relation between art index, consumer sentiment, and future real activity.
Summary of Findings
Art as an asset class displays a low level of correlation with equity. Consequently, art has
the ability to reduce the risk of a portfolio when combined with other asset classes.
What is Art?
Art can be viewed as the expression of culture, and art investing as an "investment in
meaning". But what is its monetary value? Historical data shows that prices of paintings
by well-known and less well-known artists have increased over centuries: this proves that
true artistic relevance prevails in the long run and ultimately also finds an appropriate
market value. Therefore the great challenge of the art investor appears to lie in
identifying artistic relevance.
The first issue I would like to address is whether art is a financial asset in the first place.
As Stein notes, works of art are extraordinary economic goods. They are at once durable
consumer goods and financial assets. Their aggregate supply is non-augmentable for the
works of deceased artists. They are extremely heterogeneous, with values that range from
a few dollars to a few million dollars. When hung in museums, they are public goods in
the sense that their viewing services are simultaneously available to everyone. They are
speculative goods to the extent that demand determines future price appreciation and
expected future price appreciation determined demand. In sum, they are the archetype of
what might be called "collector goods".
So, is art a financial asset? There is a wide debate on this point. Those who agree that art
is a financial asset seek to replicate the periodic cash flows generated using the rental
market as a proxy. Alongside these cash flows, though, art undoubtedly offers implicit
rents to ownership, that accrue from the aesthetic benefits of possession (the so-called
"aesthetic dividends" and from the status derived from ownership and possession, for
example from hanging up a painting in your house and displaying it to guests). In this
sense, there has been a discussion (see Frey and Eichenberger) as to what extent, and
under what circumstances, art is more likely to be a consumption good (with traditional
collectors prevailing) or an investment good (with financial speculations prevailing). The
fact that art may be a speculative asset appears to be confirmed by a 1953 survey, in
which 63% of art buyers admit that speculation is their most important criterion. Those
who disagree, point to the lack of liquidity in works of art. On the other hand there are
other forms of investment, such as venture capital and real estate, that are considered
financial assets without any doubt even though they probably have a lower level of
liquidity.
So, given that art is an asset, and that investors are interested in the financial returns of
this investment, the second issue I would like to address is the risk that this investment
entails and what is the source of the risk. Analysis shows that the standard deviation of
returns of investment in art is high. Goetzmann believes that the single largest source of
risk for the art investor is taste - the possibility that a work of art will fall from fashion
and become worthless. His analysis shows that purchasing a work by a well-known artist
is just as likely to provide high returns as purchasing the work of a lesser-known artist.
Also Pesando's work on prints disproves the popular notion that masterpieces outperform
the market. As Proust wrote in 1922 in "Cities of the Plain" on the re-appreciation of art
movements, "As on the Stock Exchange, when a rise occurs a whole group of securities
profit by it, so a certain number of despised artists benefited from the reaction, either
because they did not deserve such a scorn, or simply because they had incurred it."
Investing in Art
The difficulty of investing in the art market derives from the art market's inefficiency,
from the know-how and expertise that the art market requires, and from the uncertainty
surrounding tax issues.
The art market is definitely not an efficient market. The drivers of this are:

The traded products are differentiated: the art markets are seriously incomplete
and often very thin, with very few works of art of a specific author traded each
year.

Market transparency is low.

There are potentially large differences in expertise between buyers and sellers.

There is low liquidity: buyers and sellers are often distant in terms of space and
time, and there is not always an available buyer or seller.

Transaction costs (for example, auction fees, insurance and handling costs) are by
far larger than in other markets.

There are psychic benefits of owning art, which are largely absent in the case of
owning financial assets.
Additionally, as Baumol notes, the art markets have a much weaker equilibration process
(the process by which market prices tend to the equilibrium price) than other securities.
This is because:
1. Elasticity of supply is equal to zero for works of deceased artists.
2. Each individual work of art is unique, while the inventory of a particular stock is
made up of a large number of homogeneous securities, all perfect substitutes for
one another.
3. The owner of a work of art has a monopoly on that specific object, while a given
stock is held by many individuals who are potentially independent traders on a
near perfectly competitive stock market.
4. The purchase and sale of a work of art is an infrequent occurrence and may
happen even only once in a century.
5. The acquisition price of a work of art is not generally public information and is
often only known to the parties immediately involved.
6. The equilibrium price is unknown, so an objective evaluation (such as a present
value of future cash flows) is often impossible.
Successful investment in art requires not only extensive know-how about the artistic
quality and authenticity of the object to be acquired but also about peculiarities of the art
market. Additionally, it requires the investor to establish a scenario of future economic
and social developments, also including international factors such as exchange rate
movements, special cultural factors and market preferences.
Tax uncertainties add to the difficulty of investing in art and no study seriously takes into
account the tax effect of investing in art. In many countries investment in art is one of the
major possibilities of escaping or at least reducing the tax burden. And this is even more
important as it is often unclear which country's tax code applies.
Past Studies of Returns in the Art Market
A. Studies
Many studies focus on analyzing and predicting price trends, both for individual artists
and for schools of artists. I will briefly review some of the most significant studies.
Baumol concludes that art prices behave randomly. Further, he shows that large gains and
losses occur with shorter holding periods, while the returns on longer holding periods are
very close to zero (this is indicative of a random process with a mean of zero).
Stein treats works of art as a combination of consumer durables, yielding a flow of
nonpecuniary viewing services, and capital assets, yielding a return from financial
appreciation. He therefore divides the rate of return into two components, a return from
nominal capital appreciation and a residual return from durable services (the return from
viewing services, less insurance and maintenance costs, plus an annualized premium to
account for any tax advantages, less an annualized premium to account for the illiquidity
of this form of investment). The results show an estimated annual net return from durable
services of 1.6% (i.e. to the investor primarily interested in financial gain and valuing the
return from viewing pleasure at only about 1.6% per year, paintings are no more or less
attractive than other assets, and yield the going rate for their systematic risk). In
comparison, the 10.5% average annual appreciation of paintings in the US between 1946
and 1968 lends credibility to the assumption that collectors regard paintings as capital
assets.
Goetzman finds a very high correlation between his art index and an index of London
Stock Exchange shares; he therefore concludes that, while returns to art investment have
exceeded inflation for long periods, and the returns in the second half of the 20th century
have rivaled the stock market, they are no higher than would be justified by the
extraordinary risks they represent. Additionally, he finds that the high correlation to both
bonds and stock makes investment in art a poor vehicle for the purposes of
diversification.
In a 1995 paper, Goetzmann uses a simulated portfolio method. This yields very different
results with median annual returns of 8.24% in nominal terms and 2.42% in real terms,
and with standard deviations respectively of 8% and 7.47%. In his sample of less than
100 paintings there are a few dramatic outliers but the dispersion of annualized returns is
surprisingly small, suggesting that, at least for holding periods greater than a decade, the
risk is modest. Additionally, this risk not only reflects the risk of the art market as a
whole, but it includes the idiosyncratic risk of individual works, to the extent that it is not
diversified away completely through inclusion in a portfolio. These returns clearly beat
inflation, bond investment, and the capital appreciation of common stocks.
Weiland, Donaldson and Quintero examine the impact of US and Japanese equity
markets on art prices, and find a significant relationship. In particular, their analysis
shows that art price returns exhibited first-order autocorrelation and heteroskedasticity.
Further, they find that art and stock prices shared a single, common, long-term trend.
They believe, though, that investors can not make above-normal profits buying and
selling art, because the art market is less liquid than stock markets.
Chanel's work shows that financial markets influence the art market (in particular they
conclude that art never "causes" the stock markets, whereas English, Japanese and
American stocks significantly "cause" art), even with a lag of about one year. He further
uses a VAR (Vector Auto Regressive) model and concludes that lagged financial
variables help predict art prices, even if the lag does not allow for systematic profits.
Candela and Sorcu study the Italian art market over the 1983-1994 period and concluded
that art had lower returns than financial assets, explaining this with the aesthetic dividend
and ownership effect. They also conclude that in the long run art prices are unrelated to
financial asset prices, but find a positive correlation with real estate prices. Additionally,
they show that the correlations are not contemporaneous, due to the different level of
liquidity of the assets - equities being the most liquid and real estate being the least
liquid.
Pesando finds a negative correlation of prints with T-bills and identifies a minimum
variance portfolio - 94% Treasury bills and 6% modern prints - with a real return of
2.19% and a standard deviation of 3.19%. Wilke shows that for Contemporary Modern
Art the hypothesis that prices of an artist's work only rise significantly after his or her
death does not hold true.
Some of the results are summarized in the following table:
Article
Period Mean
St.
Dev.
Baumol
(1986)
1652 0.55
1961
1635 Frey and
198700 1.8000
Pommerehne
1950 - 6.70
(1989)
1987
Goetzmann
(1993)
1716 198600 3.2000 56.500
1850 - 6.2000 65.000
198600 17.50 52.80
1900 -
Beta
Correlation
1.250000
(t=2.4)
5.000000000
4.7
0.670000
0.790000000
0.78
1986
Goetzmann
(1995)
Mastumo,
Andoh, and
Hoban
(1994)
1907 - 5.75 8.00
1987 11.13
Pesando
(1993)
1977 1.51
1992
Stein (1977)
1975 16.00 17.00
1989
10.47
19.90
0.310000
(t=1.8)
0.30
0.820000
(t=2.4)
B. Techniques
Studies that have focused on measuring the returns of art investment have generally
encountered difficulties in building an adequate index. Another difficulty is the presence
of the bias (both on the low and on the high end) that derives from using auction prices.
The two techniques that have been used to build the indeces are:
1. Repeated sales regressions that look at paintings appearing several times in the
market
2. Art price indices, some of which have been estimated with hedonic regression
analysis. Some authors search for the underlying forces behind art movements
(e.g. income, inflation, stock prices movement), while others look at the
interdependencies between the markets for various types of paintings and of
various locations.
Examples of indices that have been used in the past include:

Baumol builds an index based on Gerald Reitlinger's 1961 compendium of sales
of art works by "...the best known painters of the world" over more than five
centuries. He takes all the data relative to works of art that have been sold at least
two times over a 300-year period and comes up with 640 transactions extending
from 1652 to 1961. Once deflated, Baumol calculates the returns for each painting
for the period between adjacent transactions.

Pesando builds an index based on the auction market for modern prints (which are
multiples and therefore allow for a larger number of repeat sales) over a 16-year
period from 1977 to 1992.

Stein builds his indices on US and UK auction prices.

Goetzmann constructs an index that includes paintings brought to market at least
twice over the 1715 - 1986 period. He again uses the Gerald Reitlinger data and
extends it with information from Enrique Mayer for the years 1971 - 1987. In
another paper, he recognizes the survivorship bias of repeat sales methods, and
therefore calculates appraisal-based returns to a simulated portfolio.

Weiland, Donaldson and Quintero use a sample of impressionist and modern
paintings sold at auctions held by Sotheby's and Christie's in New York over the
period May 1977 to May 1995. They calculate estimated prices based on a
hedonistic model and use them to construct a price index.

Candela and Sorcu propose a price index based on estimated and auction prices.
They use hedonic regression to construct a price index of a time-invariant
"representative painting" (a refinement of the average painting method).
Specifically, from the auctions in the period they consider, they calculate a grand
distribution of the distributions of prices estimated by the auction house in all the
auction sessions; this is meant to approximate the theoretical and unobservable
price structure of the market. The grand distribution is used to identify the
"representative painting", and the auction prices of the paintings included are then
used to generate the "representative painting's" price.

Chanel uses the Mayer compendia (1963 to 1993) and bases his index on prices
generated using hedonic regression.
Most of the data used in these analyses are based on auctions because the data are easily
available and reliable, but disregard other sales, which may be quantitatively more
important and show different price movements. Additionally, auction prices are really
wholesale prices and do not form a good basis to calculate the returns to private
collectors.
C. Summary
The long-term trend in inflation-adjusted art prices follows the general economic trend,
with art prices rising above average compared to the prices of other goods. However,
most segments of the art market react quickly to a worsening of the economic
environment, and this is especially true for objects in the lower price category, with broad
markets.
Results such as Goetzmann's have led researchers to conclude that art is an attractive
investment only for nearly risk-neutral investors, and then only if the expected returns to
art exceed the expected returns to stocks. The high correlation displayed in Goetzmann's
studies between the art and the stock and bond markets clearly makes art a poor vehicle
for the purposes of diversification.
According to an alternative interpretation of these results (see Frey and Eichenberger), art
returns come from two different sources: financial return (change in monetary value) and
phsychic return (consumption benefit of owning art). Therefore, if there is at least some
consumption benefit, the financial rate of return of art objects should in equilibrium be
lower than that in other markets with similar risks.
My approach
I have used Art Market Research data, run regressions and found that art has a low
correlation with equity. It is therefore a good vehicle for diversification. I have attempted
an optimization exercise, which gives a high prominence to art.
As far as opportunities for future research, if as many studies point out the market is not
efficient, then there is the possibility to predict it and thereby generate excess returns,
even more so than for more efficient financial markets.
A. Data Used
This is a very sensitive issue, as can be seen in all the papers on the present topic.
Building an index is very time-consuming and given the limited scope of the present
project, I have focused on searching existing sources. For my analysis I have used the
indices created by Art Market Research (http://www.artmarketresearch.com) that cover
the period from 1976 to the present. These indices are based on a methodology developed
by the London School of Economics together with leading art expert Robin Duthy. I
thank Art Market Research for giving me access to their indices.
B. My methodology
Within the choice of indices, I chose the "Central 80" category, which I believe
represents normal conditions on the art market, and excludes extreme data points. I first
plotted the Art 100 Index and the MSCI World Index, and then regressed the Art 100
Index against the MSCI World Index and also both the MCSI World Index and its lag. I
also regressed some of the country-specific Art Indices against the MCSI for that specific
country. Finally, I tried to plot artists, countries and the world art index to see if an
"efficient frontier" pattern emerges. I also attempted an asset allocation exercise to verify
an optimal allocation between art, equity and fixed income.
C. My results
The plot of the Art 100 index and the MSCI do not display a strong relation between the
two series. A closer examination of the period that surrounds the 1987 stockmarket crash
provides more information.
This detail shows how the Art 100 index did not suffer consequences as the MSCI
dipped. The Art Index started declining at the end of 1990 and this is attributed by many
to the worsening Japanese economy - Japanese buyers were believed to have created a
bubble in the art market.
Also, as the first complete plot shows, the recent turmoil in the stockmarket does not
appear to have affected the art market. For this reason, it is not surprising to see the
results of an explanatory regression of the Art 100 Index against the MSCI World Index:
The MSCI World has a low explanatory power, and the results are only slightly better
with a multiple regression of the Art 100 Index against the MSCI World and its first lag:
It is interesting to notice that the introduction of a new variable (the Lag of the MSCI
World Index) does not materially change the coefficient of the base variable (the MSCI
World Index) or the significance of its coefficient as expressed by its T-statistic.
The next step in my analysis was to consider country-specific Art Indices and their
relation with the MSCI Index for the specific country. These generally confirm the
overall picture and are also statistically significant.
Regressions:
Plots:
I have finally attempted to plot the different indices and verify if indices that represent a
more diversified mix of paintings expand the efficient frontier. Generally, this does seem
to be the case, as the following overall plot shows:
The overall plot is quite hard to see and I have therefore plotted a more limited set of
indices to verify the effect of diversification:
Finally, I attempted an optimization exercise with art, equity and fixed income to find an
optimal (return-maximizing) portfolio with 0.15% monthly standard deviation. I had to
use a shorter time period for this analysis (December 1990 - December 2000), due to
limits of data availability for fixed income. The allocation exercise is unconditional and
uses average 3-year returns, and not prediction of returns (and possibly standard
deviations and correlations) as a more appropriate analysis would require. I also did not
allow short selling in my exercise.
For equity, I attempted to use both the MSCI World series, and alternatively a
combination of the MSCI series of US equities and UK equities, but the results do not
differ substantially. Similarly, for fixed income I attempted to use both the JPM bond
index, and alternatively a combination of 10-year Treasuries and Corporate AAA 7-10
year, and again the results do not differ substantially. I therefore decided to show the
analysis with the MSCI World and JPM bond index.
Finally, I performed the analysis on the Art 100 Index, but also on a country-specific
index (French Impressionists) and on a specific artist (Francesco Clemente), to verify if
there are any substantial differences.
The optimizer for the 3 indices gives the following results:
In analyzing these results, art clearly has a very important weight. And comparing the
results of the Art 100 Index with those of the individual artist (Francesco Clemente), the
first case gives art a much higher weight, showing how it is a diversified portfolio of art.
D. My conclusions
My analysis shows that art has a low correlation with equity and is therefore a good
vehicle for diversification. This is evident in the optimizations I have performed, which
give a high prominence to art. In a time in which there is so much talk of alternative
investments and their increasing use in portfolios to boost performance, this study
indicates that art can be a good candidate. Like real estate, investment in art can be
securitized. One example would be the advances and guarantees offered by auction
houses to their clients.
Bibliography
William J. Baumol, Princeton University, "Unnatural Value: Or Art Investment as
Floating Crap Game".
G. Candela and E. Scorcu, University of Bologna, Italy, "A Price Index for Art Market
Auctions - An Application to the Italian Market of Modern and Contemporary Oil
Paintings".
Bruno S. Frey, University of Zurich, "Art markets and economics: Introduction".
Bruno S. Frey and Reiner Eichenberger, University of Zurich, "On the return of art
investment return analyses".
Bruno S. Frey, University of Zurich, "Arts and Economics".
William Goetzman, Yale School of Management, "Private Value Components, and the
Winner's Curse in an Art Index".
William Goetzman, Yale School of Management, "How Costly is the Fall From Fashion?
Survivorship Bias in the Painting Market".
William Goetzman, Yale School of Management, "The Informational Efficiency of the
Art Market".
William Goetzman, Yale School of Management, "Accounting for Taste: An Analysis of
Art Returns Over Three Centuries".
William Goetzman, Yale School of Management, and Matthew Spiegel, Haas School of
Business, "Private Value Components, and the winner's curse in an art index".
James E. Pesando, University of Toronto, "Art as an Investment: The Market for Modern
Prints".
John Picard Stein, "The monetary appreciation of paintings".
Kenneth Wieand, University of South Florida, Jeff Donaldson, Northern Kentucky
University, and Socorro Quintero, Oklahoma City University, "Are Real Assets Priced
Internationally? Evidence from the Art Market".
Wolfgang Wilke, Dresdner Bank, "Investing in art - the art of investing".
Wolfgang Wilke, Dresdner Bank, "Art market: expensive modern art?.
Wolfgang Wilke, Dresdner Bank, "The market for paintings: Noblesse oblige - the
Barbizon School".