1
An Optimal Global Fine Wine Portfolio Mengyi Jiang (Melly)
Thesis Advisor: Prof. Richard Walker
Abstract
Traditional academic focus on fine wine investments has long been associated with
western fine wine. The Asian fine wine market has always been neglected. This paper argues that
the addition of China’s fine wine to the traditional western fine wine portfolio will significantly
benefit investors. This is because China’s fine wine return has a negative average correlation
coefficient of -0.0242 with western fine wines. In order to capture the diversification benefits,
this paper collects wine returns from eight different regions (i.e. Australia, Burgundy, Bordeaux,
California, China, Italy, Portugal, Rhone) to form an optimal global fine wine portfolio. This
optimal global fine wine portfolio outperforms the equity and the commodity markets according
to 2005-2010 data. This is because both the equity and the commodity markets suffered
tremendously during the 2008 financial crisis whereas the wine market remained fairly intact
during this period. Due to fine wine’s independence of the financial market, 2005-2010 data
shows that a rational investor should invest 71.92% of one’s total risky assets in the
geographically diversified fine wine portfolio, with the rest in the traditional equity and
commodity markets. Such a high weight on fine wine assets reflects the fact that fine wine can
effectively protect investors’ returns per unit of risk in a financial crisis. Therefore,
geographically diversified fine wine assets are excellent investment alternatives because of their
diversification benefits and their low exposure to financial market movements.
Keyword:
Optimal global fine wine portfolio, China’s fine wine, diversification benefits, wine indices, fine
wine market, optimal share of wine, financial crisis
1. Introduction
The vineyards of Italy, France and other Western countries are continually renowned for
their fine wine. The habit of drinking wine has long been associated with western lifestyles.
Although wine is still mainly regarded as a consumption good, there is an increasing trend
among western investors towards treating wine as an alternative financial investment asset. In
fact, wine has an active trading market that allows it to be analyzed as an investment vehicle, and
the volume of trading in this wine market is phenomenal. For example, monthly wine auctions at
the top six auction houses often exceed $15 million. In addition, according to International
Herald Tribune, there are at least two mutual funds that specially invest in wine: the Ascot Wine
Management Fine Wine Fund (founded in 1999) and the Orange Wine Fund (founded in 2001).
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Most of the current wine investors focus on fine wine in the western society though, and little
attention is given to the emerging Asian market, especially China’s fine wine market.
China’s fine wine market has been booming along with China’s rapid economic growth.
China significantly enhanced its domestic fine wine quantity and quality in recent years. In 2011,
for example, Chinese wine makers beat French wine makers by winning a coveted Decanter
award for best Bordeaux Varietal. China’s fine wine is gaining global recognition in the
traditionally Western fine wine market.
This research paper will explore an optimal fine wine portfolio with truly global coverage
for financial investors. Specifically, this paper will discuss the potential gains from including
Chinese wines in the global fine wine portfolio and the investment value of this portfolio
especially in the recent financial crisis. In addition, this paper will solve for the optimal share of
fine wine assets that an average investor should hold in one’s total risky investment.
The remainder of this paper is organized as follows. Section 2 describes China’s wine
industry. Section 3 summarizes related academic literatures about wine and discusses the main
contribution of this paper. Section 4 provides a description of the data. Section 5 presents the
analysis and discusses the potential benefits to an average investor from including Chinese fine
wine in a global wine portfolio. This section also analyzes the investment value of
geographically diversified fine wine assets to financial investors. Section 6 concludes the paper.
2. Background of China’s Wine Industry
China has both an ancient history of wine traditions and a current emerging wine market.
Until this century, China’s 2000-year history of wine making has had a different style than the
Western style of wine making.
After the establishment of the PRC in 1949, there were few wine enterprises and the output
of wine was only 200 tons per year. However, several national policies subsequently favored the
domestic wine market. For example, in 1987 the Chinese government began to encourage its
citizens to drink grape wine over “Baijiu”, a kind of pure white liquor made of rice and sorghum.
As a result, the number of wine enterprises in China reached 179 in 2011 and the output of each
was over RMB 20 million. The total assets of the wine industry in China were worth RMB 32.05
billion in 2011. 1
China is one of the fastest growing wine markets in the world. The IWSP annual study2
shows that between 2009 and 2010, the consumption of still, light and sparkling wines grew by
33.4% in China. This led to a total consumption of 156.9 million 9-liter bottles of wine in 2011.
Due to rising popularity of wine, China has overtaken the UK in the world’s top five wine-
consuming nations.
1 CRI (China Research and Intelligence Co., Ltd.) Report: Research Report on Chinese Wine Industry, 2010-2011;
April 2012. 2 The IWSR (International Wine & Spirit Research) China Wine Market Report; August 2011.
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To meet the growing demand for wine, domestic Chinese vineyards are expanding
production. The important wine varieties in China are Sauvignon blanc, Chenin blanc, Italian
Riesling, white Riesling, Cabernet Sauvignon, Cabernet franc, Merlot and Pinot noir. Also, large
vineyards in China have a comparative advantage as the cold climate eliminates pest problems.
In 2000, there were more than 400 wine companies established in 26 provinces. In 2005, China’s
wine produced 487 million liters of wine from 1150 thousand acres of vineyard, exceeding
Australia, Chile, and South Africa combined. At the moment, grape production ranks 5th
in fruit
production in China. 3
In addition to the rising production, domestic wine makers are also improving their wine
quality. For example, He Lan Qing Xue vineyard in China recently won the 2011 Decanter
World Wine Award for Best Bordeaux Varietal with its Jia Bei Lan carbenet dry wine.
Moreover, Jancis Robinson, a Master of Wine, told Reuters Television at the 2011 Hong Kong
International Wine Conference the following: “Every time I get to China, I try and get together
the best wines that are being made. When I first went into that exercise, I think it was 2002, it
wasn’t very inspiring at all. But actually last year, I was very heartened because I tasted several
wines that I thought were quite respectable... The grapes are fully ripe. They’re clean. They’re
fruity.” Robinson said later in the interview that she was also convinced that China has the
potential to produce more fine wines in the future. With improvement in quality, domestic wine
in China is gaining more attention from the international community. Thus, it makes sense to
include China in the list of the countries that produce fine wine.
The current domestic wine market in China is very concentrated. This is demonstrated by
the fact that 60% of the market is controlled by the top four companies: Yantai Changyu, China
Great Wall, Tonghua Grape Wine and Dynasty Fine Wine.
One should pay particular attention to the company called Yantai Changyu, as it has led
several innovations in China’s domestic fine wine production. Established in 1892, Yantai
Changyu is the largest wine production company in China and accounts for about one fifth of all
sales in this country. In 2001, the firm formed a strategic alliance with the well-known French
wine group Castel, in order to focus on mid-range and high-end wines. In 2003, the company
launched the “barrel ordering” sales mode. In 2007, Yantai Changyu opened the AFIP Chateau
in Beijing to cater high-end customers. With the launch of the new chateau, Changyu introduced
a new investment vehicle to Chinese investors: Wine Futures. This is a milestone in the
development of China’s wine industry because it showed the transition of the wine from a
consumption commodity to an investment asset in China.
3. Literature Review
There are two major research directions regarding fine wine. In the first research direction,
studies focus on the determinants of fine wine prices for different varieties. In the second
research direction, fine wine is treated as an investment vehicle such as stocks and bonds. As this
paper is more related to the second research direction in wine, this section presents an overview
3 International Journal of Wine Research 2009:I 19-25
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of the main conclusions of the past academic papers that explore the investment value of fine
wine.
Krasker (1979) concluded that there was no risk premium (excess return over the baseline
of risk-free rate) for storing red Bordeaux and California Cabernet Sauvignon by analyzing their
returns from 1973 to 1977. On the contrary, Jaeger (1981) proposed that there was an annual
12% risk premium for storing these two types of wines by extending Krasker’s sample period to
1969-1977 and assuming a much lower storage cost. Weil (1993) discovered that the return to
wine assets was approximately 9.5% by calculating the returns to an individual wine portfolio
over a 13-year period (1980-1992). However, by comparing the return of the wine assets to the
return of NYSE stocks, Weil found only Bordeaux fine wine had better return than the traditional
stock market. Later on, Burton and Jacobsen (2001) argued against Weil’s conclusion by using a
repeat-sale regression to estimate the return for Bordeaux wines from 1986 to1996. By
comparing these returns to the Dow Jones Industrial Average, Burton and Jacobsen found that
only the 1982 vintage portfolio outperforms the index. This was in contrast to the conclusion of
Weil. The academic debate over the investment value of fine wine was unsettled at this point.
In 2008, Sanning, Shaffer, and Sharratt re-visited this topic by analyzing the level and
quality of Bordeaux wine returns using the Fama-French Three-Factor Model and the Capital
Asset Pricing Model. According to these two models, they found an alpha of 0.75% per month in
Bordeaux wine investments. In addition, they discovered that investment grade wine benefited
from low exposure to market risk factors. This feature led to the possibility of portfolio
diversification.
Based on the concept of portfolio diversification, Kourtis, Markellos, and Psychoyios
(2010) used online fine wine index data to demonstrate that significant international
diversification benefits exist for investors in Italian, Australian and Portuguese fine wine. In
particular, they showed that the correlation coefficients of wine returns in Italy, Australia and
Portugal were relatively small with average values at 28.1%, 32.7% and 29% respectively.
This paper is going to contribute to the existing literature in the following three aspects.
First, this paper will expand the traditional academic focus on western fine wine and include
China’s fine wine from a global perspective. Second, this paper will use empirical data to realize
the theoretical diversification benefits of geographically diversified wine assets. As although past
literature has analyzed the diversification benefits of fine wine in particular western countries, no
optimal fine wine portfolio has been constructed on a global basis. Third, this paper is going to
contribute to the ongoing academic debate over the investment value of fine wine by discussing
the particular worthiness of fine wine in the recent financial crisis.
In order to achieve these contributions, this paper organizes the structure of the entire
analysis as follows. First, this paper will first use the modern portfolio theory to construct an
optimal global fine wine portfolio. Then this paper will compare the performance of this optimal
global fine wine portfolio with those of the benchmark indices in the wine auction market, the
equity market and the commodity market. Finally, this paper will help average investors to find
the optimal share of wine in their total risky investments, taking account of the empirical pattern
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of wine returns (specifically, their mean, variance, and correlation with equity and commodity
returns).
4. Data
Three categories of data are collected for this paper. The first category of data is eight
wine price series from different regions. Specifically, this paper has collected the monthly prices
of seven region-specific wine indices and one wine company stock from Jan 2005 to Jan 2010.
The paper will use these eight wine price series to construct an optimal global fine wine
portfolio. The second category of data includes major benchmarks in the wine auction market,
the equity market, and the commodity market. The third set of data is the 2005-2010 T-Bill rates,
which will be used to calculate the risk free rate in the economy during this five-year period.
A.1. Region- Specific Wine Indices
The seven region-specific wine indices were obtained from WinePrices.com. Kourtis,
Markellos, and Psychoyios (2010) also used these wine indices as part of their entire dataset in
their research paper. These wine indices are popular among wine researchers because they are
the only indices that have a regional focus and are publicly available. Specifically, these seven
wine indices are Australia 20 Index (A20), Burgundy 50 Index (B50), Bordeaux First-Growth
100 Index (BFG100), Rhone 50 Index (R50), California 100 Index (C100), Italy 25 Index (I25),
and Port 10 Index (P10). The region name in each index title specifies the region on which this
wine index focuses, and the number in each index title describes how many different wines in
this region are selected to form the index.
WinePrices.com is an online resource for wine auction and retail price information.
WinePrices.com is the most comprehensive online resource for up-to-date wine price
information, with over 400,000 prices from the last eight years and over 1 million US wine retail
prices. According to this website, the wines that make up an individual index are the most
actively traded fine wines bought and sold at global auctions. In particular, individual wine is
selected based on a combination of its month-to-month sales consistency and its absolute
frequency of auction sales. Each wine appearing in the initial index must have been sold at an
auction in a 750ml size during the first quarter of 2005. Wines whose trading activity slows are
candidates for removal and more frequently traded wines will replace them from time to time.
Each index is calculated monthly based on global auction results. Each wine's monthly price
variation is weighted equally with any other in the same index.
This paper obtains 61 observations of monthly prices during the period of Jan 2005-Jan
2010 for each of the seven wine indices. Monthly returns of each index are calculated from these
monthly prices. Their descriptive statistics are presented in Table 1. BFG100 has the highest
average monthly return of 1.85%, whereas the lowest average monthly return of 0.38% comes
from A20. In terms of return variation, C100 has the lowest standard deviation of returns of
0.0026. This means that investments in C100 suffer from fewer risks. P10, on the contrary, has
the highest standard deviation of 0.1098.
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These seven wine indices only describe the wine market in western societies. For the
purpose of this paper, information about China’s fine wine return is also necessary. However, as
the wine market in China is still young, a systematic index that shows the monthly price
variation of China’s fine wine has not yet been constructed.
A.2. The Changyu Stock
This paper derives the monthly return of China’s fine wine from the monthly stock price of
Yantai Changyu (Changyu). Changyu is the leading fine wine producer in China. The Changyu
stock is traded on the Shenzhen Stock Exchange. The monthly return of the Changyu stock is
3.34%, which is much higher than the average return of western wines (0.99%). This is because
the return to Changyu as a firm is not the same as the return to outsiders buying Changyu's wine
product (for one thing, Changyu is made better off and outsiders worse off by a rise in the initial
price of a wine). This means that the stock return is an imperfect proxy for China’s fine wine
return. In order to make Changyu’s return representative of the return of China’s fine wine, this
paper assumes that
where S is the stock price of Changyu, R is the return of China’s fine wine, a and b are
parameters, and 𝜀 is a random shock.
Since the return of China’s fine wine and the price level of the Changyu stock are
inherently related, this paper assumes the above linear relationship between the two variables.
The main profit of Changyu comes from producing and selling China’s fine wine. It is very
likely that more people will desire to hold the Changyu stock when the return of China’s fine
wine is high. Driven by the high demand, the price of the Changyu stock will consequently
increase. There are two mechanisms to support this hypothesis. First, given that the investment
channels in China are still quite limited, more people in China are willing to buy and to hold
Changyu’s fine wine as a physical investment asset when the general return of China’s fine wine
is high. Thus, the sales and profits of Changyu will rise and this will directly lead to higher stock
price of Changyu. Second, as China’s fine wine return gets higher, the market will raise its
evaluation of the total asset value of Changyu, which includes plenty of fine wine inventories. As
a result, the Changyu stock will get a higher valuation.
This paper also assumes that investments in China’s fine wine enjoy the same return and
risk as in the general fine wine market. In other words, in order to estimate the values of the
parameters, this paper normalizes the mean and variance of China’s fine wine return to be equal
to the average of other wines. By doing so, this paper is able to isolate the correlation aspect
from other investment factors of these fine wine assets. Thus, this paper can focus solely on the
diversification benefits of these eight wine assets. In finance, diversification means reducing
risks by investing in a variety of assets. An investor can reduce portfolio risk simply by holding
combinations of instruments which are not perfectly positively correlated (correlation coefficient
). Diversification may allow for the same portfolio expected return with reduced
risk. This is called diversification benefits. These ideas have been started with Markowitz and
then reinforced by other economists and mathematicians such as Andrew Brennan who have
expressed ideas in the limitation of variance through portfolio theory. In my case, by calculating
the correlation between China’s fine wine return and the return of other regions’ fine wine, this
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paper will be able to show whether it is worthwhile to add China’s fine wine in the traditional
western fine wine market from the perspective of diversification.
Since Var(𝜀)=0,
( ) ( ) ( ) ( )
E(R) is equal to the average mean return across the seven wine indices (0.99%) and Var(R)
is equal to the average variance of returns across the seven wine indices (0.0058). With E(S) =
373.68 and Var(S) = 27056.88 from the Changyu stock prices, this paper backs out that a = -
16.37 and b = 0.00046. Therefore, this paper derives the monthly mean and variance of China’s
fine wine return as follows:
( ) ( ) ( ) ( )
A summary that describes the statistics of wine returns across the eight different regions is
as follows:
Table 2 presents the correlation between the returns of the eight fine wine assets:
From the correlation matrix, it is obvious that the addition of China’s fine wine to the
traditional fine wine market will bring investors significant diversification benefits. According to
the theory of diversification, it is worthwhile to add an additional asset to a portfolio if the
additional asset is not perfectly positively correlated with the existing portfolio. In Table 2,
China’s fine wine has a negative average correlation of -0.0242 with the other seven wine assets.
This means the price of China’s fine wine moves in a somewhat opposite direction with the other
wines. An asset that has negative correlations with other assets is very valuable in a portfolio.
This is because this asset can effectively reduce the individual risk of the portfolio through
A20 B50 BFG100 R50 C100 I25 P10 China Changyu Stock
Number 60 60 60 60 60 60 60 60 60
Mean 0.38% 1.50% 1.85% 0.92% 0.45% 0.72% 1.09% 1.20% 3.34%
Median 0.00% 0.79% 0.67% 0.00% 0.00% 0.00% 0.55% 1.37% 3.67%
Maximum 15.17% 19.74% 26.57% 37.34% 12.36% 17.48% 34.09% 15.02% 32.06%
Minimum -16.99% -13.13% -21.30% -19.72% -13.74% -14.16% -16.69% -11.55% -19.47%
Variance 0.0037 0.0047 0.0070 0.0071 0.0026 0.0037 0.0120 0.0057 0.0092
Std. Dev. 0.0610 0.0682 0.0837 0.0845 0.0505 0.0610 0.1098 0.0752 0.0958
Table 1: Descriptive Statistics of Wine Returns
A20 B50 BFG100 R50 C100 I25 P10 China
A20 0.2363 0.3497 0.2298 0.4045 0.1147 0.3831 -0.0474
B50 0.2363 0.5234 0.5782 0.3530 0.1329 0.3416 0.0058
BFG100 0.3497 0.5234 0.5142 0.6653 0.2711 0.2392 0.0126
R50 0.2298 0.5782 0.5142 0.5313 0.3489 0.2476 -0.0574
C100 0.4045 0.3530 0.6653 0.5313 0.3639 0.1877 -0.0880
I25 0.1147 0.1329 0.2711 0.3489 0.3639 0.2788 -0.0003
P10 0.3831 0.3416 0.2392 0.2476 0.1877 0.2788 0.0054
China -0.0474 0.0058 0.0126 -0.0574 -0.0880 -0.0003 0.0054
Mean 0.2387 0.3102 0.3679 0.3418 0.3454 0.2157 0.2405 -0.0242
Table 2: Correlation Matrix Between Wine Assets
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hedging without sacrificing the portfolio return. Thus, the correlation matrix shows that it is
necessary to add China’s fine wine to the traditional fine wine market in order to achieve an
optimal investment result.
B. Benchmarks
In order to evaluate the performance of the optimal global fine wine portfolio, this paper
finds several benchmarks in three different markets.
In the wine auctions market, this paper chooses the Fine Wine 250 Index as the
benchmark. This paper obtains monthly observations of the index price from Jan 2005 to Jan
2010 from WinePrices.com. According to the website, the Fine Wine 250 is the most
representative index of fine wines. The index is constructed by including the 250 most actively
traded wines at global auctions. The price trend of this benchmark is depicted in Figure 2. The
Fine Wine 250 Index has a mean of 1.35% and a standard deviation of 0.0664, which are
displayed in Table 3. However, after looking more deeply into the composition of the Fine Wine
250 Index, this paper finds that the benchmark has a heavy focus on French wine. Also, no Asian
or Chinese wine is included in this index. For better demonstration, Figure 1 decomposes the
Fine Wine 250 Index based on different countries:
In the equity market, this paper chooses DJIA and S&P500 as the benchmarks in the US
stock market. For the Asian stock market, this paper chooses Heng Seng Index and Shanghai
Composite Index as the benchmarks. All the data on these stock indices are publicly available.
This paper obtains monthly prices for these four indices from Jan 2005 to Jan 2010. The price
patterns of the four equity market benchmarks are presented in Figure 2. The descriptive
statistics of these equity market benchmarks are in Table 3. In particular, Shanghai Composite
Index has the highest monthly return of 2.13% and S&P500 has the lowest standard deviation of
0.0456.
In the commodity market, this paper collects monthly price observations of the Dow
Jones-UBS Commodity Index (DJ-UBSCI) for the period of Jan 2005-Jan 2010. This commodity
Australia, 0.4%
France, 84.0%
Italy, 2.8%
Portugual, 0.8% USA, 12.0%
Figure 1: Country Decomposition of the Fine Wine 250 Index
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index is a broadly diversified index that allows investors to track commodity futures through a
single measure. The DJ-UBSCI is composed of commodities traded on U.S. exchanges, with the
exception of aluminum, nickel and zinc, which are traded on the London Metal Exchange
(LME). The monthly prices of DJ-UBSCI are depicted in Figure 2 and its descriptive statistics
are presented in Table 3. DJ-UBSCI has a monthly return of -0.09% and a standard deviation of
0.0588.
Figure 2 presents the price trends of the six benchmarks from Jan 2005 to Jan 2010. For
better demonstration, this paper normalizes the initial prices of all the benchmarks to be 100.
C. Treasury Bill (T-Bill)
This paper collects monthly observations of the 4-week T-Bill secondary market rates for
the period of 2005-2010 from the Board of Governors of the Federal Reserve System. However,
the original rates are annual rates. To get the monthly T-Bill rates, this paper uses the following
conversion method:
Fine Wine
250 IndexDJIA S&P 500
Heng Seng
Index
Shanghai
Composite IndexDJ-UBSCI
Number 60 60 60 60 60 60
Mean 1.35% 0.14% -0.03% 0.91% 2.13% -0.09%
Median 0.49% 1.18% 0.89% 1.98% 4.17% 1.08%
Maximum 18.00% 11.15% 9.39% 17.07% 27.45% 12.99%
Minimum -17.18% -21.43% -16.94% -22.47% -24.63% -21.34%
Variance 0.0044 0.0026 0.0022 0.0053 0.0115 0.0035
Std. Dev. 0.0664 0.0509 0.0465 0.0729 0.1071 0.0588
Table 3: Descriptive Statistics of Benchmarks' Returns
0
50
100
150
200
250
300
350
400
450
500
550
Jan-05 Jun-05 Nov-05 Apr-06 Sep-06 Feb-07 Jul-07 Dec-07 May-08 Oct-08 Mar-09 Aug-09 Jan-10
Figure 2: Normalized Price Levels for Benchmarks
Fine Wine 250 Index DJIA S&P 500
Heng Seng Index Shanghai Composite Index DJ-UBSCI
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( )
Figure 3 shows the T-Bill monthly rates from 2005 to 2010:
Since T-Bill is regarded as a safe investment, this paper assumes that the monthly risk-free
rate is the monthly T-Bill rate. To get an average risk free rate from 2005 to 2010, I calculate the
mean of all the monthly T-Bill rates over the five years and get an average monthly risk free rate
of 0.21%.
5. Analysis
This paper will conduct three steps of analyses to construct and evaluate the optimal global
wine portfolio. First, this paper will use the modern portfolio theory to build an optimal global
fine wine portfolio from the eight data series of wine returns. Second, this paper will compare the
performance of the global wine portfolio with those of the benchmarks. Third, this paper will
find the optimal share of fine wine for a common investor to include in his/her total risky
investment portfolio.
Step 1:
The modern portfolio theory maximizes the expected return of a portfolio for a given
amount of portfolio risk (or equivalently, minimizes the portfolio risk for a given level of
expected return) by carefully choosing the proportions of various assets in the portfolio.
Consider a portfolio of n risky assets, whose returns are normally distributed. By
assigning different weights to these n assets in the portfolio, the portfolio will exhibit different
pairs of mean and standard deviation. By plotting all the points with the highest return for a
given level of standard deviation, we can get the Efficient Frontier (EF) for this portfolio. As all
rational investors want high returns and low risks, they will choose the one point on the EF that
has the highest Sharpe Ratio, which is a measure of the excess return (or risk premium) per unit
of deviation in an investment. The formula for Sharpe Ratio is:
0.00%
0.05%
0.10%
0.15%
0.20%
0.25%
0.30%
0.35%
0.40%
0.45%
Feb
-05
May
-05
Au
g-0
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Figure 3: T-Bill Monthly Rates from 2005 to 2010
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( )
where ( ) is the expected return of the portfolio, is the risk-free rate, and is the standard
deviation of the portfolio. The point with the highest Sharpe Ratio is called the Tangency
Portfolio. This is the optimal portfolio that any investor could possibly get if he/she only invests
in the n risky assets. This is also the optimal fine wine portfolio that this paper is going to
construct with the empirical data. The line that links the Tangency Portfolio and the risk free
asset is the best possible Capital Allocation Line (CAL), which displays to investors the most
return that they can make by taking on a certain level of risk. The slope of the best possible CAL
is the Sharpe Ratio of the Tangency Portfolio. Figure 4 shows the Modern Portfolio Theory in a
graph:
Figure 4: Illustration of the Modern Portfolio Theory
The modern portfolio theory, which is based on mean-variance analyses, is developed by
Harry Markowitz in the early 1960’s. The general model is as follows:
( )
where
( ) ∑ ( )
∑
∑∑
√
In this model, is the return of the portfolio. is the return of the asset i and is the weight of
the component asset i (that is, the share of asset i in the portfolio). is the variance of the
portfolio and is the variance of the asset i. is the standard deviation of the portfolio and
is the standard deviation of the asset i. is the correlation coefficient between the returns of
assets i and j.
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Kourtis, Markellos, and Psychoyios (2010) have showed that all the wine indices are
normally distributed, with the exception of R50. This paper makes the assumption that the data
series of R50 and China also have normal distribution to satisfy the requirement of the model.
Applying the empirical wine returns to Markowitz’s model, this paper gets an optimal global fine
wine portfolio that gives investors the highest return per unit of standard deviation. This optimal
global wine portfolio has a Sharpe Ratio of 0.2842. The Excel program which computes the
weight on individual asset is presented in Table 4. The composition of this optimal global wine
portfolio is shown in Figure 5:
Table 4: Excel Program for the Computation of the Optimal Wine Portfolio
-9.43%
55.72% 67.39%
-18.78%
-65.00%
31.17%
0.84%
38.09%
100%
-80%
-60%
-40%
-20%
0%
20%
40%
60%
80%
100%
120%
A20 B50 BFG100 R50 C100 I25 P10 China Total
Figure 5: Composition of the Optimal Wine Portfolio
Portfolio's Expected ReturnExpected Tracking ErrorPortfolio's Standard DeviationTracking Error Std. Dev.
Number of securities: 8
No Name Fraction Expected Standard Correlations 1 2 3 4 5 6 7 8
Return Deviation A20 B50 BFG100 R50 C100 I25 P10 China
1 A20 -9.43% 0.382% 0.0610 1 A20 1 0.2363 0.3497 0.2298 0.4045 0.1147 0.3831 -0.0474
2 B50 55.72% 1.502% 0.0682 2 B50 1 0.5234 0.5782 0.3530 0.1329 0.3416 0.0058
3 BFG100 67.39% 1.849% 0.0837 3 BFG100 1 0.5142 0.6653 0.2711 0.2392 0.0126
4 R50 -18.78% 0.923% 0.0845 4 R50 1 0.5313 0.3489 0.2476 -0.0574
5 C100 -65.00% 0.446% 0.0505 5 C100 1 0.3639 0.1877 -0.0880
6 I25 31.17% 0.722% 0.0610 6 I25 1 0.2788 -0.0003
7 P10 0.84% 1.093% 0.1098 7 P10 1 0.0054
8 China 38.09% 1.200% 0.0752 8 China 1
100.00% Corr OK? YES
Results:
Portfolio's Expected Return 0.0228
Portfolio's Standard Deviation 0.0727
0.21%
0.2842
Risk Free Rate
Sharpe Ratio
© Ravi Jagannathan, Kellogg School of Management, NU, 1999-2001, Rev Fall 2004
Construct Tables Fill In Names
13
In order to reach the maximum Sharpe Ratio of 0.2842, an investor has to be able to short
three wine indices (A20, R50, C100) in this portfolio. However, these wine indices on
WinePrices.com are not traded on any exchange. This means that an investor cannot short these
wine indices as easily as shorting a stock. In order to short a wine index, one needs to be able to
physically short all the wines that constitute the index in wine auction houses. In particular, this
implies that an investor has to be able to do the following things:
a) Borrow all the wines in a single wine index and sell them in auction houses;
b) Use the proceeds to buy other wines that one wants to long;
c) Hold these longed wines to the next period and sell them;
d) In the second period, use the gains from sale to buy back the wines that they originally
borrowed;
e) Return the wines, which have been bought back, to the lender in the second period.
Obviously, this is not something that an average investor is able to do. Thus, to figure out a
more realistic wine portfolio for average investors, this paper adds one more restriction to the
maximization problem mentioned above. That is, wines from all the eight regions must have
non-negative composition in the final optimal portfolio. With this restriction, we get a second
optimal wine portfolio that does not allow shorting. The Sharpe Ratio for this portfolio is 0.2580.
The composition of the adjusted optimal wine portfolio is demonstrated in Figure 6 and the
computation program is presented in Table 5.
0.00%
32.01% 26.35%
0.00% 0.00%
10.42%
0.00%
31.22%
100%
0%
20%
40%
60%
80%
100%
120%
A20 B50 BFG100 R50 C100 I25 P10 China Total
Figure 6: Composition of the Optimal Wine Portfolio w/o Short
14
Table 5: Excel Program for the Computation of the Optimal Wine Portfolio w/o Short
To illustrate the importance of China’s fine wine in the optimal global fine wine portfolio,
this paper also calculates two more optimal wine portfolios that do not include China. The
optimal wine portfolio that excludes China’s fine wine can only reach a Sharpe Ratio of 0.2617,
which is lower than the Sharpe Ratio (0.2842) of the optimal global fine wine portfolio that
includes China’s fine wine. Likewise, in a more realistic case where shorting is not allowed, the
highest possible Sharpe Ratio (0.2232) of a portfolio that excludes China is less than the Sharpe
Ratio (0.2580) of the optimal portfolio with China. The decomposition graphs and the
computation programs of these two optimal portfolios that exclude China’s fine wine are
presented in Figure 7, Figure 8, Table 6, and Table 7. From these empirical results, it is clear that
China’s fine wine can bring large diversification benefits to investors who used to only invest in
western fine wine.
Portfolio's Expected ReturnExpected Tracking ErrorPortfolio's Standard DeviationTracking Error Std. Dev.
Number of securities: 8
No Name Fraction Expected Standard Correlations 1 2 3 4 5 6 7 8
Return Deviation A20 B50 BFG100 R50 C100 I25 P10 China
1 A20 0.00% 0.382% 0.0610 1 A20 1 0.2363 0.3497 0.2298 0.4045 0.1147 0.3831 -0.0474
2 B50 32.01% 1.502% 0.0682 2 B50 1 0.5234 0.5782 0.3530 0.1329 0.3416 0.0058
3 BFG100 26.35% 1.849% 0.0837 3 BFG100 1 0.5142 0.6653 0.2711 0.2392 0.0126
4 R50 0.00% 0.923% 0.0845 4 R50 1 0.5313 0.3489 0.2476 -0.0574
5 C100 0.00% 0.446% 0.0505 5 C100 1 0.3639 0.1877 -0.0880
6 I25 10.42% 0.722% 0.0610 6 I25 1 0.2788 -0.0003
7 P10 0.00% 1.093% 0.1098 7 P10 1 0.0054
8 China 31.22% 1.200% 0.0752 8 China 1
100.00% Corr OK? YES
Results:
Portfolio's Expected Return 0.0142
Portfolio's Standard Deviation 0.0468
0.21%
0.2580
Risk Free Rate
Sharpe Ratio
© Ravi Jagannathan, Kellogg School of Management, NU, 1999-2001, Rev Fall 2004
Construct Tables Fill In Names
15
Table 6: Excel Program for the Computation of the Wine Portfolio w/o China
-19.00%
99.37%
125.46%
-36.97%
-128.52%
57.71%
1.94%
100%
-150%
-100%
-50%
0%
50%
100%
150%
A20 B50 BFG100 R50 C100 I25 P10 Total
Figure 7: Composition of the Optimal Wine Portfolio w/o China
Portfolio's Expected ReturnExpected Tracking ErrorPortfolio's Standard DeviationTracking Error Std. Dev.
Number of securities: 7
No Name Fraction Expected Standard Correlations 1 2 3 4 5 6 7
Return Deviation A20 B50 BFG100 R50 C100 I25 P10
1 A20 -19.00% 0.382% 0.0610 1 A20 1 0.2 0.3 0.2 0.4045 0.1147 0.3831
2 B50 99.37% 1.502% 0.0682 2 B50 1 0.5 0.6 0.353 0.1329 0.3416
3 BFG100 125.46% 1.849% 0.0837 3 BFG100 1 0.5 0.6653 0.2711 0.2392
4 R50 -36.97% 0.923% 0.0845 4 R50 1 0.5313 0.3489 0.2476
5 C100 -128.52% 0.446% 0.0505 5 C100 1 0.3639 0.1877
6 I25 57.71% 0.722% 0.0610 6 I25 1 0.2788
7 P10 1.94% 1.093% 0.1098 7 P10 1
100.00% Corr OK? YES
Results:
Portfolio's Expected Return 0.0326
Portfolio's Standard Deviation 0.1167
0.21%
0.2617Sharpe Ratio
Risk Free Rate
© Ravi Jagannathan, Kellogg School of Management, NU, 1999-2001, Rev Fall 2004
Construct Tables Fill In Names
16
Table 7: Excel Program for the Computation of the Wine Portfolio w/o Short & w/o China
Step 2:
For this part of analysis, I assume that all the wine indices are traded actively on an
exchange, and short positions on any wine index are easy for average investors to hold. I make
this assumption because the purpose of this paper is to demonstrate the potential gains that future
investors can obtain by holding a truly global wine asset. As the financial market for wine is
gaining more attention in recent years, it is expected that wine indices will be freely traded on
exchange like commodity indices in the future. Based on this assumption, the optimal wine
portfolio in this step refers to the optimal global fine wine portfolio that allows shorting and
includes China’s fine wine.
0.00%
46.31% 38.78%
0.00% 0.00%
14.85%
0.07%
100%
0%
20%
40%
60%
80%
100%
120%
A20 B50 BFG100 R50 C100 I25 P10 Total
Figure 8: Composition of the Optimal Wine Portfolio w/o Short & w/o China
Portfolio's Expected ReturnExpected Tracking Error Portfolio's Standard DeviationTracking Error Std. Dev.
Number of securities: 7
No Name Fraction Expected Standard Correlations 1 2 3 4 5 6 7
Return Deviation A20 B50 BFG100 R50 C100 I25 P10
1 A20 0.00% 0.382% 0.0610 1 A20 1 0.2363 0.3497 0.2298 0.4045 0.1147 0.3831
2 B50 46.31% 1.502% 0.0682 2 B30 1 0.5234 0.5782 0.3530 0.1329 0.3416
3 BFG100 38.78% 1.849% 0.0837 3 BFG100 1 0.5142 0.6653 0.2711 0.2392
4 R50 0.00% 0.923% 0.0845 4 R50 1 0.5313 0.3489 0.2476
5 C100 0.00% 0.446% 0.0505 5 C100 1 0.3639 0.1877
6 I25 14.85% 0.722% 0.0610 6 I25 1 0.2788
7 P10 0.07% 1.093% 0.1098 7 P10 1
100.00% Corr OK? YES
Results:
Portfolio's Expected Return 0.0152
Portfolio's Standard Deviation 0.0587
0.21%
0.2232Sharpe Ratio
Risk Free Rate
© Ravi Jagannathan, Kellogg School of Management, NU, 1999-2001, Rev Fall 2004
Construct Tables Fill In Names
17
To evaluate the performance of the optimal global wine portfolio, this paper is going to
compare the Sharpe Ratio of this portfolio with the Sharpe Ratios of the benchmarks. As
explained before, the Sharpe Ratio measures the risk premium per unit of return deviation of an
investment. An asset outperforms other assets only if it can produce more returns than other
assets without sacrificing the risk exposure, given that the returns of these assets exhibit normal
distributions. Thus, an investment with a higher Sharpe Ratio is considered superior in the two-
dimensional analysis framework of mean and variance.
The optimal global wine portfolio beats the benchmark of the wine auction market. Figure
9 depicts the normalized price trends of the optimal portfolio and the Fine Wine Index 250 from
2005 to 2010. In particular, Fine Wine Index has a Sharpe Ratio of 0.1712, which is much lower
than the Sharpe Ratio of the wine portfolio (0.2842). The global wine portfolio outperforms the
average wine auction market because of diversification benefits. Since the Fine Wine Index 250
is hugely concentrated on traditional French wine, this benchmark index involves more
individual risks that could be diversified away. As the returns of China’s fine wine are negatively
correlated with the returns of most western fine wines (shown in Table 2), the addition of
China’s fine wine in the global portfolio effectively reduces the individual risks in the traditional
wine auction market. This comparison demonstrates once more that the introduction of China’s
fine wine brings better investment results.
The optimal wine portfolio also outperforms the equity market in the period of Jan 2005-
Jan 2010. The Sharpe Ratios of the equity market benchmarks are listed in Table 8 against the
Sharpe Ratio of the optimal wine portfolio. The normalized price patterns of the four equity
benchmarks and the optimal wine portfolio are also plotted in Figure10. Although Asian stock
market generally performed better than the US stock market for the period of 2005-2010, it is
clear that the wine portfolio produces much higher Sharpe Ratio than all equity benchmarks.
0
50
100
150
200
250
300
Jan-05 Jun-05 Nov-05 Apr-06 Sep-06 Feb-07 Jul-07 Dec-07 May-08 Oct-08 Mar-09 Aug-09 Jan-10
Figure 9: Normalized Price Levels for the Optimal Wine Portfolio (OWP) and the Fine Wine 250 Index
OWP Fine Wine 250 Index
18
This result is probably due to the 2008 financial crisis, during which major equity markets
suffered tremendously and have not yet fully recovered. Since the wine market is quite separate
from the equity market and has low market risk factors (which Sanning, Shafffer and Sharratt has
shown in their paper), geographically diversified wine assets provide protection to equity
investors in financial crises and thus are good alternative investments to go with traditional
investment vehicles. This is another investment value of the geographically diversified fine wine
asset in addition to its diversification benefits. This comparison result contributes to the debate
started by Krasker (1979) about the investment value of wines.
In the commodity market, the Sharpe Ratio of DJ-UBSCI is only -0.0513 for the period
from 2005 to 2010. The optimal wine portfolio, with a Sharpe Ratio of 0.2842, definitely
outperforms the general commodity market. The poor performance of the commodity market is
probably also due to the 2008 financial crisis. Since the commodity market is fairly monetized,
the financial crisis may have bigger and longer impacts on this market than on the wine market.
The normalized prices of DJ-UBSCI and the optimal wine portfolio are depicted in Figure 11.
DJIA S&P 500Heng Seng
Index
Shanghai
Composite Index
Optimal Wine
Portfolio
Sharpe Ratio -0.0142 -0.0531 0.0951 0.1786 0.2842
Table 8: Sharpe Ratios of Equity Market Benchmarks and the Optimal Wine Portfolio
0
50
100
150
200
250
300
350
400
450
500
Jan-05 Jun-05 Nov-05 Apr-06 Sep-06 Feb-07 Jul-07 Dec-07 May-08 Oct-08 Mar-09 Aug-09 Jan-10
Figure 10: Normalized Prices of the Optimal Wine Portfolio (OWP) and Equity Market Benchmarks
OWP DJIA Shanghai Composite Index S&P 500 Heng Seng Index
19
From the empirical data of 2005-2010, the optimal global fine wine portfolio outperforms
all of the three traditional markets (the wine auction market, the equity market, and the
commodity market) in the mean-variance analysis.
Step 3:
The previous step has demonstrated that our wine portfolio is superior to other kinds of
investment vehicles in the period of 2005-2010 in the mean-variance framework. However, a
rational investor will never put his/her entire assets into a single class of investment vehicle.
Instead, a rational investor will hold a diversified risky portfolio that includes wines, and then
will decide how to allocate his/her entire assets between the diversified risky portfolio and the
risk-free asset. In this part of analysis, this paper is going to calculate the optimal share of wine
in a well-balanced risky portfolio.
This paper assumes that the diversified risky portfolio of an average investor consists of
the following three classes of investment vehicles: equity, commodity, and wine. Although an
investor may also buy Treasury bills or bonds, this paper regards such investments as risk free.
Thus, this paper is not going to consider T-Bills in the risky portfolio of an average investor.
Now, assume that the average investor holds benchmark indices of the equity and
commodity markets together with the optimal global fine wine portfolio. This paper uses the
modern portfolio theory to calculate the share of wine in the optimal risky portfolio. In this
specific optimization problem, as there is no convergence (which means that the Sharpe Ratio of
the risky portfolio can be made infinitely high), this paper decides to make the unconstrained
values non-negative in order to have a definite and convergent solution. Consequently, this paper
finds that an average investor should contribute 71.92% of his/her risky portfolio to the
0
50
100
150
200
250
300
Jan-05 Jun-05 Nov-05 Apr-06 Sep-06 Feb-07 Jul-07 Dec-07 May-08 Oct-08 Mar-09 Aug-09 Jan-10
Figure 11: Normalized Prices of the Optimal Wine Portfolio (OWP) and DJ-UBSCI
OWP DJ-UBSCI
20
diversified wine asset (Table 9). Figure 12 illustrates the decomposition of the optimal risky
portfolio. This result is quite surprising because too much weight is put on wine whereas the
traditional equity and commodity markets are ignored.
There are two possible explanations for this unexpected result. First, the optimal global
wine portfolio is too ideal. In reality, it is quite hard to construct such a portfolio because it is
hard to short wine indices currently. Thus, the ideal wine portfolio might have a too good result
for investors to even consider other types of realistic investment vehicles. Second, this
overweight on wine is result from the 2008 financial crisis. Due to the financial crisis, traditional
markets suffered tremendously. But the wine market remained separate from the financial market
from 2005 to 2010. Consequently, the performances of the traditional equity and commodity
markets are so poor that a rational investor, when given the alternative choice of wine
investments that remain robust in the financial crisis, sensibly invests a large portion of his/her
risky assets in wines to maximize his/her total gains.
In order to explore which of the two explanations account for the real situation, this paper
decides to replace the ideal wine portfolio with the more realistic Fine Wine 250 Index. If the
composition of this realistic risky portfolio resembles that of the ideal risky portfolio, the first
explanation is no longer valid and the 2008 financial crisis should be the main contributor to the
above strange result. Otherwise, the first explanation should be responsible for the strange
decomposition of the above optimal risky portfolio.
This paper includes the Fine Wine 250 Index, DJIA, S&P500, Heng Seng Index, Shanghai
Composite Index, and DJ-UBSCI in the realistic risky portfolio. The prices of the Fine Wine 250
Index from 2005 to 2010 are actual auction prices in the past. This paper then calculates the
optimal weight on the Fine Wine 250 Index with the modern portfolio theory. The Excel
program shows that this optimization problem does not have a convergent answer either. As
before, I decide to make the unconstrained values non-negative to find a definite result. Table 10
shows the Excel program that is used for computation and Figure 13 displays the decomposition
of the realistic risky portfolio.
In the realistic risky portfolio, a sensible investor should still invest 60.42% of its total
risky assets in wine and the rest of the risky assets in Shanghai Composite Index. This result
resembles the decomposition of the ideal risky portfolio. Therefore, the poor performances of
traditional equity and commodity markets, which are due to the 2008 financial crisis, should be
the main contributor to the huge weight on wine in the optimal risky portfolio. Such huge weight
on wine reinforces the fact that geographically diversified wine assets can effectively provide
protection to investors in financial crises. Thus, fine wine assets are worthy investments in
include in a portfolio along with the traditional investment vehicles.
21
Table 9: Excel Program for the Computation of the Ideal Optimal Risky Portfolio
0.00% 0.00% 0.00%
28.08%
0.00%
71.92%
100.00%
0%
20%
40%
60%
80%
100%
120%
DJIA S&P500 Heng Seng ShanghaiComposite
DJ-UBSCI Wine Portfolio Total
Figure 12: Decomposition of the Ideal Optimal Risky Portfolio
Portfolio's Expected ReturnExpected Tracking ErrorPortfolio's Standard Deviation Tracking Error Std. Dev.
Number of securities: 6
No Name Fraction Expected Standard Correlations 1 2 3 4 5 6
Return Deviation DJIA S&P500 Heng SengShanghai Composite DJ-UBSCI Wine Portfolio
1 DJIA 0.00% 0.140% 0.0509 1 DJIA 1 0.1364 0.5101 0.2840 0.2694 0.2102
2 S&P500 0.00% -0.030% 0.0465 2 S&P500 1 0.3720 0.2845 0.4570 0.1424
3 Heng Seng 0.00% 0.910% 0.0729 3 Heng Seng 1 0.6005 0.2108 0.2777
4 Shanghai Composite 28.08% 2.130% 0.1071 4 Shanghai Composite 1 0.1056 0.0868
5 DJ-UBSCI 0.00% -0.090% 0.0588 5 DJ-UBSCI 1 0.0896
6 Wine Portfolio 71.92% 2.275% 0.0727 6 Wine Portfolio 1
100.00% Corr OK? YES
Results:
Portfolio's Expected Return 0.0223
Portfolio's Standard Deviation 0.0625
0.21%
0.3238Sharpe Ratio
Risk Free Rate
© Ravi Jagannathan, Kellogg School of Management, NU, 1999-2001, Rev Fall 2004
Construct Tables Fill In Names
22
Table 10: Excel Program for the Computation of the Realistic Optimal Risky Portfolio
6. Conclusion
Wine has long been associated with western lifestyles. As an investment vehicle, French
fine wine market has been given the most attention. The Asian wine market, on the contrary, has
often been neglected in past studies about wine. With the rapid growth of China’s wine industry,
this paper has argued that the inclusion of China’s fine wine in the global wine portfolio will
bring significant diversification benefits to investors. Also, geographically diversified wine
assets are great alternative investment vehicles because their returns remain fairly independent of
the financial market. In the recent financial crisis, the optimal global fine wine portfolio
0.00% 0.00% 0.00%
39.58%
0.00%
60.42%
100.00%
0%
20%
40%
60%
80%
100%
120%
DJIA S&P500 Heng Seng ShanghaiComposite
DJ-UBSCI Fine Wine 250 Total
Figure 13: Decomposition of the Realisitc Optimal Risky Portfolio
Portfolio's Expected ReturnExpected Tracking ErrorPortfolio's Standard Deviation Tracking Error Std. Dev.
Number of securities: 6
No Name Fraction Expected Standard Correlations 1 2 3 4 5 6
Return Deviation DJIA S&P500 Heng Seng Shanghai Composite DJ-UBSCI Fine Wine 250
1 DJIA 0.00% 0.140% 0.0509 1 DJIA 1 0.1364 0.5101 0.2840 0.2694 0.2054
2 S&P500 0.00% -0.030% 0.0465 2 S&P500 1 0.3720 0.2845 0.4570 0.2318
3 Heng Seng 0.00% 0.910% 0.0729 3 Heng Seng 1 0.6005 0.2108 0.2299
4 Shanghai Composite 39.58% 2.130% 0.1071 4 Shanghai Composite 1 0.1056 0.1219
5 DJ-UBSCI 0.00% -0.090% 0.0588 5 DJ-UBSCI 1 0.0526
6 Fine Wine 250 60.42% 1.350% 0.0664 6 Fine Wine 250 1
100.00% Corr OK? YES
Results:
Portfolio's Expected Return 0.0166
Portfolio's Standard Deviation 0.0618
0.21%
0.2344
Risk Free Rate
Sharpe Ratio
© Ravi Jagannathan, Kellogg School of Management, NU, 1999-2001, Rev Fall 2004
Construct Tables Fill In Names
23
outperforms the traditional equity and commodity markets. Thus, globally diversified fine wine
assets are valuable investment tools not only because they enjoy significant diversification
benefits but also because they can provide protection to average investors’ risky portfolios
during financial downfalls.
This paper collected monthly prices of fine wines from eight regions from 2005 to 2010.
The eight regions include Australia, Burgundy, Bordeaux, California, Rhone, Italy, Portugal, and
China. In particular, China has a negative average correlation coefficient (-0.0242) with other
wine assets. This implies that the inclusion of China’s fine wine in the global fine wine portfolio
will bring large diversification benefits.
Based on the maximization model from the Modern Portfolio Theory, this paper
constructed an optimal geographically diversified fine wine portfolio. The Sharpe Ratio for this
global wine portfolio is as high as 0.2842. China’s fine wine constitutes 38.09% of the total
portfolio. The optimal wine portfolio requires investors to short certain wines. Since short
positions on wines are currently difficult to hold, an optimal portfolio that does not allow short
positions was also calculated. The Sharpe Ratio for the portfolio without shorting is 0.2580. In
order to illustrate the necessity to include China’s fine wine in the global fine wine portfolio, this
paper also constructed two more optimal portfolios without China’s fine wine (one in the
scenario that allows short positions and the other in the scenario that does not allow shorting
wine assets). The Sharpe Ratios for these two portfolios are 0.2617 and 0.2232 respectively.
This paper compared the performance of the optimal global fine wine portfolio, which
allows short positions on wines, with the performances of several benchmarks in the wine
auction market, the equity market and the commodity market. Mean-variance analysis shows that
the optimal fine wine portfolio (Sharpe Ratio: 0.2842) outperforms the wine auction market
(Sharpe Ratio: 0.1712), the equity market (highest Sharpe Ratio: 0.1786), and the commodity
market (Sharpe Ratio: -0.0513).
Finally, this paper calculated the optimal share of wine that an average investor should
hold in his/her total risky portfolio. From the 2005-2010 data, if one invests one’s total risky
assets in equity, commodity and fine wine, fine wine should constitute 71.92% in the optimal
risky portfolio. This huge weight on fine wine is due to the fact that both equity and commodity
markets suffered tremendously in the 2008 financial crisis whereas the fine wine market
remained fairly intact. This result implies that fine wine can serve as an alternative investment
vehicle especially in times of financial crisis to protect the return per unit of risk of an average
investor’s risky assets.
In conclusion, it is necessary to expand the traditional fine wine market (i.e. include
China’s fine wine) in order to achieve optimal investment outcome. In addition, geographically
diversified wine assets are worthy investment vehicles especially in a financial crisis because the
current fine wine market remains quite independent of the traditional financial markets. Further
research could investigate the feasibility for wine derivatives (such as wine indices) to be freely
traded on exchange and its subsequent impact on the investment value of fine wine. Another
interesting topic would be to treat wine as a derivative of weather statistics and construct another
geographically diversified wine portfolio based on the global weather information.
24
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