An Optimal Global Fine Wine Portfolio Mengyi Jiang (Melly) … · 1 An Optimal Global Fine Wine...

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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%

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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.



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


Results:



0.21%

0.2580

Risk Free Rate

Sharpe Ratio



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



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


Results:



0.21%

0.2617Sharpe Ratio

Risk Free Rate



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.


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


Results:



0.21%

0.2232Sharpe Ratio

Risk Free Rate



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


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


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


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.


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


Results:



0.21%

0.3238Sharpe Ratio

Risk Free Rate



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.


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


Results:



0.21%

0.2344

Risk Free Rate

Sharpe Ratio



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

References:

Ali H., Lecocq S., Visser M. (2008). The Impact of Gurus: Parker Grades and "En Primeur"

Wine Prices. Economic Journal, Royal Economic Society, vol. 118(529), pages F158-F173, 06.

Ashenfelter, O. (2008). Predicting the Prices and Quality of Bordeaux Wines. The

Economic Journal 118 (June), F174-F184.

Ashenfelter O., Ashmore D., Lalonde R. (1995). Bordeaux Wine Vintage Quality and the

Weather. Chance, 8: 7–14.

Ashenfelter O., Byron R.P. (1995). Predicting the Quality of an Unborn Grange. The

Economic Record 71, No. 212, 40-53.

Burton B.J., Jacobsen J.P. (2001). The Rate of Return on Investment in Wine. Economic Inquiry,

39(3), 337-350.

Cardebat J., Figuet J. (2004). What Explains Bordeaux Wine Prices? Applied Economics Letters,

Taylor and Francis Journals, vol. 11(5), pages 293-296.

Combris P., Lecocq S., Visser M. (1997). Estimation of a Hedonic Price Equation for Bordeaux

Wine: Does Quality Matter? Economic Journal, 107, 390-402.

Combris P., Lecocq S., Visser M. (2000). Estimation of a Hedonic Price Equation for Burgundy

Wine. Applied Economics, 32, 961-967.

CRI (China Research and Intelligence Co., Ltd.) Report: Research Report on Chinese Wine

Industry, 2010-2011; April 2012.

Haeger J.W., Storchmann K. (2006). Prices of American Pinot Noir Wines: Climate,

Craftsmanship, Critics. Agricultural Economics, International Association of Agricultural

Economists, vol. 35(1), pages 67-78, 07.

International Wine & Spirit Research: The IWSR China Wine Market Report 2011, September

2011.

Jaeger E. (1981). To Save Or Savor: The Rate of Return to Storing Wine. Journal of Political

Economy, 89(3), 584-592.

Jones G.V., Storchmann K. (2001). Wine Market Prices and Investment under Uncertainty: an

Econometric Model for Bordeaux Crus Classes. Agricultural Economics, Blackwell, vol. 26(2),

pages 115-133, November.

Krasker W. (1979). The Rate of Return to Storing Wines. Journal of Political Economy, 87(6),

1363-1367.

25

Kourtis A., Markellos R.N., Psychoyios D. (2010). Wine Price Risk Management: International

Diversification and Derivative Instruments. International Review of Financial Analysis

(forthcoming).

Mitry D.J., Smith D.E., Jenster P.V. (2009). China’s role in global competition in the wine

industry: A new contestant and future trends. International Journal of Wine Research 2009:I 19-

25.

Redfern Associates: The China Wine Market Sector Overview 2010, May 2010.

Research and Markets: China Wine Market Report 2011—A Comprehensive Analysis on the

Market Size and Share of the Wine Industry in China, June 2011.

Sanning L.W., Shaffer S., Sharratt J.M. (2008). Bordeaux Wine as a Financial Investment.

Journal of Wine Economics, vol 3, number 1, spring 2008, pages 51-71.

Weil R. (1993). Do Not Invest in Wine, at least in the US unless you plan to drink it, and maybe

not even then. Paper presented at the 2nd

International Conference of the Vineyard Data

Quantification Society, Verona, February.

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