The Diamond Investment Possibility

Published Date: 02 Nov 2017

This chapter covers two different topics in four sections. The first one covers a brief summary of the research methodology decisions and an explanation on how the research design responds to the research questions of this study. After that, the second, third and fourth sections describe the particular methods and models used in this dissertation. The following paragraphs present a description of these subsequent sections.

The research strategy studies the diamond investment possibility using a mixed method of quantitative/qualitative analysis. A quantitative analysis of diamond prices evaluates the potential return and risk that could be achieved with diamond investments on an annual basis. The qualitative analysis on its side provides an insight on the market perception of the current diamond market and the perspective of diamond investment.

Since diamonds in the high-end segment trade mainly in auctions this research uses a hedonic regression model to construct an index which allows performing the quantitative analysis. The second section of this chapter introduces the theoretical model and its adaptation to study diamond prices as well as the database used for this purpose. The third section presents the univariate analysis used to evaluate the performance of diamond returns. It also introduces the dataset used for the middle end segment of the diamond market. Finally the last section describes the qualitative survey used to measure the market perception of the current state of the diamond market and the use of diamonds as a financial investment.

Research Methodology

The selection of the research methodology involves four steps:

1.- Identifying the research philosophy and paradigm

2.- Selecting a research approach

3.- Defining the research strategy

4.- Elaborating the research design

The purpose of this section is to present and justify the decisions made in each step in the course of selecting the research methodology.

Research Philosophy and Paradigm

The selection of a research�s philosophy and paradigm determines the general background and world conceptions that guide the construction of the bridge between the research objectives and questions, and the subject of study (Cohen et. al., 2007). In their book on research methods for business students, Saunders et. al. (2009) identify four main research philosophies/paradigms: positivism, realism, interpretivism and pragmatism. The basic ideas behind these paradigms according to the authors are:

Positivism parts from the assumption of an observable social reality where the results of research lead to the discovery of �law generalizations� (Saunders et. al., 2009: 129) parallel to those obtained in experiments conducted by natural and physical sciences. This research philosophy implies an objective point of view where the researcher is independent.

Realism assumes that the social reality exists independently of the knowledge of it that the researcher has. It has two main branches direct realism and critical realism. The first implies that the observer can fully understand the reality of the data gathered through his senses, meanwhile the second assumes that the observer can only perceive an image of the reality affected by sensations that mix with his senses. Under this paradigm observations are objective but its interpretation is altered by the researcher�s cultural environment.

Interpretivism is a research philosophy characteristic of social sciences. Its main argument is that the researcher�s role in social reality creates knowledge and this changes when the role changes. The ontological position is then subjective as the researcher is inevitably part of the object of study

Pragmatism states that a multiple view encompassing the analysis of objective and subjective information is an adequate choice to answer the research question. To perform this task, pragmatism allows the combination of the views used in other philosophies. The paradigm also permits the employment of mixed and multiple research methods to collect and analyse data from the subject of study.

The research questions of this dissertation imply that the main subjects of study of this dissertation are the diamond industry and diamond price returns. In order to analyse the objective and subjective information gathered from them and to answer both questions this dissertation is conducted under the research philosophy of pragmatism. The objective interpretation of the data follows the logic of the direct realist paradigm while interpretivism guides the analysis of subjective information.

Research approach

In research there are two basic approaches: deductive and inductive. The deductive approach makes use of existing theory to prove or disprove a hypothesis by testing the collected data. This approach goes from general to particular. In contrast, the inductive approach seeks to understand the general by studying the particular. Inductive research analyses the collected data and makes generalisations from it to construct hypotheses and theories.

The general conception is that being opposites, deductive and inductive approaches should not be mixed in a single study. However Saunders et. al. found that contrary to this belief using both approaches is useful in research:

Not only is it perfectly possible to combine deduction and induction within the same piece of research, but also in our experience it is often advantageous to do so. (Saunders et. al., 2009: 127)

This dissertation corroborates the benefit of using both approaches in the same study. On one side, the deductive approach is used to answer the first research question in order to evaluate the suitability of diamonds as financial investments. On the other side, the investigation takes advantage of the inductive approach to propose a hypothesis that answers the second question of the reasons that had prevented the success of diamond investment in the past.

Research Strategy

Research strategy refers to the way in which the researcher answers the research questions. The main strategies which are described below are: experiment, survey, case study, action research, grounded theory, ethnography and archival research.

Experiment. First used in natural and physical sciences, this strategy allows finding causal relationship between variables. This is done through the comparison of an experimental (in which the researcher intervenes) and a control group (with no intervention).

Survey. This strategy allows the collection of standardised primary data with the aid of a questionnaire, structured observation or structured interviews.

Case study. Opposite to experiments, case studies analyse a phenomenon in its ordinary environment and allows for several methods of data collection.

Action research. This research strategy has a defined goal to change or promote on the subject of study. It is linked to research within an organisation or with theory development in the academic context.

Grounded theory. Usually linked with inductive approaches, this strategy parts from the data analysis to find (or develop) the theory that explains it.

Ethnography. Original to anthropological studies, this strategy requires a complete immersion of the researcher into the environment of the study subject.

Archival research. This research strategy gathers information from documents and data sets collected for the ordinary tasks and needs of the object of study.

The selected strategy for this investigation is the case study. The choice of the strategy follows its fittingness to make an evaluation on the current diamond market and on the performance of diamond returns against the performance of traditional investment assets.

Research Design

Research design refers to the selection of particular methods that in combination with the previous methodology decisions enable the researcher to respond the research question. As the introduction previously stated this investigation makes use of quantitative and qualitative methods. The following paragraphs present first the collected data and then the research questions and the methodology the study uses to answer them.

To study the diamond prices returns this study constructs its own primary data in the form of a dataset with the annual returns on diamond prices, the index level of the S&P 500, as well as the price of an ounce of physical gold. The database also includes the annual inflation of the US Consumer price index and the yields of the US 3 month treasury bill and AAA corporate bonds.

The raw material for this construction was secondary data of traditional market indicators obtained from EconStats� and of diamond prices drawn from proprietary databases obtained from Rapaport� using the researcher�s subscription to the diamond information service . The Rapaport group is one of the main information providers in the diamond industry. Established in 1976, it is mainly recognised for its publication of the Rapaport Price list�, a report launched in 1978 which has become the primary source of diamond price and market information. The investigation uses two databases from Rapaport:

The Rapaport Diamond Index� (available in the Rapaport Diamond Price Statistics 2011 and 2012) to study the prices of commodity type diamonds. This database was selected because it provides the researcher the opportunity to work with prime information about wholesale diamond prices obtained directly from the source which is a benchmark for the industry (PriceScope.com, 2013).

The Rapaport Auction Price Reports (2005 to 2012) from Sotheby�s and Christie�s to analyse the prices of high end diamonds. These reports present a comprehensive database of the prices and characteristics of all diamonds sold in the two most important auction houses of the world. This database was also the only resource accessible to the researcher to provide relevant information on diamond prices in this category due to time and information availability constraints.

As for the study of the diamond market this research relies on two sources of information: the literature review of the diamond market and the primary data collected by the researcher from industry members in a survey. The fourth section of this chapter presents detailed information on the elaboration of the questionnaire used in the survey.

Question 1: Given the diamond market characteristics and price returns, could diamonds be considered a financial investment?

The answer of this question is composed of two elements: the suitability of the diamond market characteristics to allow the use of diamonds as financial investments and the performance of price returns.

To analyse the diamond market characteristics a qualitative method based on a survey which measures the market perception on the subject and on the analysis of the current state of the diamond market. In turn, the performance of the return on diamond prices is evaluated using quantitative methods.

Question 2: What have been the reasons for diamond investment failure until now?

Just as in the analysis of the diamond the response to this question comes from the evaluation of the state of the diamond market but in a historical perspective and from the information obtained from the surveys used to measure market perception. This question is subordinated to the first one, as the current state of the conditions identified as the causes of failure in previous diamond investment attempts has a direct impact on the decisions of potential investors today.

Hedonic regression model for art and collectible type diamond prices

The literature review on high end diamonds, as well as the one studying the returns on art and collectible uses frequently hedonic regression models to construct price indexes which allow researchers to perform return analysis. The model used in this research was chosen as the best fitting approach according to Burton and Jacobsen�s (1999) research which compares the available methodologies for price index discovery for arts and collectibles.

A second reason to decide for the hedonic approach to construct the price index was to share the methodology used by Renneboog and Spaenjers (2011) in their study on the return of rare diamonds. This decision allows having a point of comparison for the obtained results.

According to Hill (2011) the earliest record of the use of a hedonic model is from a study on the effect of quality factors on vegetable prices from Waugh in 1928. However it was until the second half of that century when the method gained popularity when Griliches (1961, 1971), Lancaster (1966) and Rosen (1974) laid the conceptual frame of the approach.

The basic concept of a hedonic model is to determine the impact of different qualitative factors in the price of a product. A simple example of the model would be the housing market in a city. The city has a number of houses with different characteristics (bedrooms, bathrooms, garden, etc.) which sell in different prices. However in order to make a projection of the price of a particular house a hedonic model can be used to find the shadow price of each of the characteristics. The equation (4) represents the linear regression of this basic model.

ln?(P_k )=a+?�?�_m X_mk ?+e_k (4)

Where:

ln?(P_k) stands for the natural logarithm of the price of house k.

a represents an autonomous coefficient giving the base price for any house in that city.

X_mk stands for the value of the characteristic m of house k

�_m represents the attribution of a shadow price to characteristic m

Using a database with the sale prices and the characteristics of all the houses sold in the city, the coefficients obtained from the hedonic model would allow identifying the base price for any property plus the shadow price of each of the characteristics. With this information real estate agents in the city may be able to price new properties for sale. Markets which usually use hedonic models include the automotive industry, the healthcare system, real estate industry and the art and collectible market; the model is also used to adjust for quality some items in the US consumer price index (Hill,2011).

A variation of this basic model is used to create price indexes by including time considerations. In the basic example it would serve if real estate agents wanted to know the increase of house prices over a given period of time (Coulson, 2008). An important consideration is that the shadow prices of all characteristics are assumed to be constant during the whole period implying that the preferences of consumers remain unchanged. The regression for the new model is given in equation (5).

ln?(P_k )=a+?�?�_m X_mk ?+?�??_t d_kt ?+e_k (5)

Where:

d_kt stands for a dummy variable which takes the value of 1 if the house k was sold in time t and 0 otherwise, and

?antilog(??_t)*100 represents an index value of the price based on the first year. For this to work the omitted dummy should be the one representing the first year.

This time dummy variation of the hedonic regression model is the one the present research. Two separate models for colourless and coloured diamonds were built using a proprietary database obtained from Rapaport, this research models diamond price using auction results of diamonds sold at Sotheby�s and Christie�s between 2004 and 2012. The model structure is similar to the one used by Renneboog and Spaenjers (2011) in their research. The main differences between both studies are in observation periods, the frequency selected for the creation of time dummies and the exclusion of observations from colourless diamonds of less than 5 carats.

The specification of the models is given by equation (6) for colourless diamonds and equation (7) for the coloured ones.

ln?(P_colourless )=a+�_1*ln?(carat)+�_2* ?ln?(carat)?^2+�_3* round (6) +�_4*E +�_5*F+�_6*G+�_7* H +�_8*(I-J) +�_9*( K-L)+�_10*( M-Z)+�_11*FL+�_12*VVS +�_13*VS +�_14*SI+�_15* other clarity +�_16* Hong Kong +�_17*New York +�_18*London +�_19*St.Moritz +�_20*other city +�_21*Christie^' s + ?_1 d_05+ ?_2 d_06 + ?_3 d_07+ ?_4 d_08+ ?_5 d_09+ ?_6 d_10 + ?_7 d_11+ ?_8 d_12+e_k

ln?(P_coloured )=a+�_1*ln?(carat)+�_2* ?ln?(carat)?^2+�_3* round (7) +�_4*brown +�_5*blue+�_6* green+�_7* orange +�_8* pink+�_9* other colour +�_10*VVS +�_11*VS +�_12*SI+�_13* other clarity+�_14* Hong Kong +�_15*New York +�_16*London +�_17*St.Moritz +�_18*other city+�_19*Christie^' s+ ?_1 d_05+ ?_2 d_06 + ?_3 d_07+ ?_4 d_08+ ?_5 d_09+ ?_6 d_10+ ?_7 d_11+ ?_8 d_12+e_k

Where:

ln?(P_colourless) Stands for the natural logarithm of the price in each auction point,

ln?(carat),ln??(carat)?^2 Are the natural logarithm and squared natural logarithm of the carat weight in each observation,

E,F,G,H,(I-J),(K-L),(M-Z) Represent dummy variables for colour in the colourless diamond dataset with D being the omitted value.

brown,blue,green,orange,pink and other colour Represent dummy variables for the coloured diamond database. In this case the omitted variable was yellow. Also an important consideration for this category is that in those cases where two hues were identified the hue of the most valuable or rare colour prevailed.

FL,VVS,VS,SI and other clarity Represent dummy variables for clarity. In the colourless database the omitted variable was IF (internally flawless), in the coloured dataset the omitted variable was a joint category of FL and IF.

Hong Kong,New York,London,St.Moritz and other city Represent dummy variables for the city in which the auction was held. The omitted variable was Geneva.

Christie's Represents a dummy variable with value of 1 if the auction was made in Christie�s. The omitted case was Sotheby�s.

d_05 to d_12 Are dummy variables for the years 2005 to 2012. The omitted case was 2004.

The output of the model and the analysis of the results are presented in chapter VI.

Univariate analysis to evaluate return performance and middle commodity type diamond prices

The univariate analysis is designed to study each variable in a dataset on its own making use of descriptive statistics. The application of the analysis in the research follows the basic concepts presented by the modern portfolio theory.

The analysis evaluates the performance of the price indexes in the following items:

Mean as a measure of the expected return

Standard deviation as a measure of risk

Return to risk ratio

Sharpe ratio as a measure of excess return

Holding period return

Correlations with the returns of traditional market indicators:

Change of the US consumer price index to evaluate the potential of inflation hedging benefits

S&P 500 as a proxy of equity performance

3 month treasury bill as a proxy risk free asset

AAA US corporate bonds as a proxy of fixed income

Physical Gold, a traditional alternative investment

A similar univariate model was used by Small et. al. (2012) in their study on the potential of diamonds as an alternative asset class. The authors apply the model to a database conformed of a diamond index and four sub-indexes (two for quality and two for size) obtained from Thompson Reuters DataStream for the period 2002 to 2011.

The source of the index used by Small et. al. PolishedPrices.com and can be obtained through the subscription services of Thompson Reuters DataStream� or using a Bloomberg Terminal�. An important consideration on the use of this database is that the developed of this index based on the price information provided by approximately fifteen companies involved in polished diamond trading. It is therefore an index constructed from secondary data and is not as well-known as other diamond indexes which are currently used in the diamond market.

This study uses the index constructed with the hedonic regression model to analyse the performance of high-end diamond prices for the available timeframe of 2004 to 2012.

For the middle-end diamond prices this research evaluates the performance of nine indexes grouped in three categories in four timeframes (5, 10, 20 and 30 years). The index categories are presented below.

Investment grade diamonds or RDI for 0.5, 1 and 3 cts. This group corresponds to the prices of the Rapaport Diamond Index. The prices in this group represent the average price of diamonds in the D-H colour and Fl-VS2 clarity ranges.

D-IF top quality diamonds for 0.5, 1 and 3 cts.

1 carat diamonds in three quality ranges: F-VVS2, H-VS2 and K-S12. The D-IF index is not present in this group as it is included in the top quality diamonds category.

A qualitative approach to evaluate market perception

Since its origins the diamond market and the diamond industry have been synonyms. However the potential introduction of financial investors to the market would inevitably mean an alteration in this social construction. It would mean that the diamond industry would pass from being the owner to just being a player in the diamond market. This fact makes understanding the perception people in the industry have of diamonds as an investment a crucial aspect of the analysis of the readiness of the market to accept financial investments in diamonds.

The selected methodology used to measure this perception was to gather information from a multiple response questionnaire. The multiple response format was selected because its ability to capture the views and attitudes of the respondents towards the question and its preselected answers (Santos, 2000). The survey targeted individuals involved in the diamond industry. It was comprised of 15 standardised questions distributed in four sections, namely diamond price and value, diamond market, diamonds and investors and a respondent profile.

The distribution of the survey was made through two channels: internet and face to face. The internet compiler was posted on LinkedIn as a link available to members of the Gemologist group. Face to face surveys were collected in London and in Mexico City during December 2012. A sample of the distributed questionnaire is available in Appendix C. The survey used a non-probability sampling technique due to time and access constraints. As the survey was designed as an exploratory tool to evaluate the perception of the industry the self-selection sampling is an appropriate method for this research (Saunders, 2009).

Data and Results Analysis

Hedonic regression model

The results from a hedonic regression model provided information for two important aspects of the high end art and collectible type diamond prices: its price determinants and an index which allows the comparison of the return performance against traditional investment assets.

Both regressions were estimated through using the ordinary least squares method. The goodness of fit in both models was assessed using the global significance F-test as well as via the adjusted R2 statistic. The significance in both models was confirmed by the result of their F-statistics. The results of the analysis of the adjusted R2 were that the specified model for colourless diamonds explained the variation in prices in an 85%, but barely over 50% of the variation in the case of coloured diamond prices.

The lower explanatory power in the second regression responds to the fact that the demand for coloured diamonds is determined by the personal preferences of consumers (whether they prefer blue over green) and the omission of a variable which measures the colour intensity. This variable was deliberately omitted to obtain a model with results comparable to the one used by Renneboog and Spaenjers (2011).

The samples included 1247 and 983 price point observation from auctions of colourless diamonds over 5 cts. and coloured diamonds respectively. Graphs 5 and 6 present the frequency distribution of the sample for all the price determinant variables.

A summary of the main findings for the price determinants and in the diamond index for both colourless and coloured diamonds is presented afterwards.

Graph 5: Frequency Distribution for the Price Determinant Characteristics in the High-End Colourless Diamond Sample

Graph 6: Frequency Distribution for the Price Determinant Characteristics in the Coloured Diamond Sample

Price determinants

In this model, the price determinants of high end diamond prices included five groups, one for each of the 4 C�s and one for auction details. The regression results for this category and the impact of each individual variable is presented in table 1 for colourless diamonds and in table 2 for the case of coloured ones.

Carat

The coefficients of the variables measuring carat weight had a positive sign for Ln(carat) and a negative sign in the squared term. The positive coefficient in the first one implies that the price increases in larger stones. In the case of colourless diamonds it was also larger than one, implying that the increase in value is more than proportionate to the increase in carat weight. The implication of the low negative signs in the squared coefficient indicates that in the effect is slightly reduced in the largest stones of the sample.

Colour

Colour is the characteristic with the highest impact in price for both samples. The reason for this might well be that after the apparent size of a diamond colour is the most evident trait of the 4 C�s. In the colourless sample the results confirm the expected decrease in price as the grades get lower. In the case of the colourless sample, yellow (which was the omitted variable) commands prices only higher to those of brown diamonds. The highest prices are paid for blue and pink diamonds.

Clarity

Just as in the case of colour grades the results confirm that diamonds with higher clarity grades fetch the highest prices. The premium for colourless flawless diamonds is of almost 30% over internally flawless ones.

Cut

The results show that round shaped diamonds sell for higher prices than the average of all other fancy shapes. The statement is particularly in the case of round colourless diamonds which have a premium of over 30%.

Auction Details

According to the regression results the auction house where a diamond is sold has no impact on its final price as the coefficients of the dummy variable for Christie�s were not significant in both cases.

As for the cities where the gemstones are sold in the case of colourless diamonds Geneva, London and New York make no difference in diamond prices. Hong Kong however pays a premium for those diamonds while other cities purchase diamonds at a discount compared to the prices in Geneva. The coloured diamond market in turn pays similar prices in Geneva, London and St. Moritz while other cities buy at a discount from those.

Diamond index

The time dummies of the model specification served to construct an index which allowed the discovery of the return of high end diamond prices.

During the whole period covered in the sample the average return of colourless diamonds at 13.96% doubled the 6.24% observed by the prices of coloured diamonds. Also if an investor had purchased one diamond of each category in 2004 to sell it by the end of the observation period the return for the holding period of the colourless diamond would have been almost four times the return he would have achieved with the coloured diamond (with HPRs of 151.8% and 43.5% respectively.

If only the last five years are counted the same relationship holds for the average returns, but the hypothetical investor would have received a larger HPR with the coloured diamond.

Table 1: Hedonic regression results for colourless diamonds auctions

Table 2: Hedonic regression results for coloured diamonds auctions

Table 3 Real returns and index values for high-end

art and collectible type diamonds

Univariate analysis

The purpose of this univariate analysis is to compare the performance of diamond returns against that of traditional market indicators such as the S&P 500, the US 3 month treasury bill, the average yield of Moody�s Aaa corporate bonds and physical gold oz. prices. Another variable included in the analysis is the US CPI in order to evaluate the inflation hedging potential of diamonds. The elements of the univariate analysis are statistics useful in the analysis of financial assets according to the MPT.

The time periods analysed for each diamond type responded to the availability of data. In the case the high end type diamonds the covered periods are five and eight years. In turn commodity-type diamonds were analysed in four time frames: five, ten, twenty and thirty years.

High-end art and collectible type diamonds

Table 4 presents the statistics used in the univariate analysis for both diamond indexes and all the traditional market indicators.

The first important observation is that in both periods the average return of diamonds was higher than the average inflation giving indication that high end diamonds can be used as inflation hedging tools. Also by just comparing the average returns in the last five and eight years, colourless diamonds were just outperformed by gold.

In terms of risk diamonds present a standard deviation similar to the one experienced by S&P 500. As for the excess return the Sharpe ratio for diamonds falls below the ones of gold and Aaa corporate bonds, but it clearly outperforms the S&P 500. The conclusion from this observation is that in the last years diamonds would have given investors a better reward over risk performance than traditional equities.

Table 4: Descriptive statistics on high-end Diamond and traditional market indicator Returns

A key element drawn from Markowitz�s portfolio theory is the achievement of risk minimisation by including assets with low correlations in the same portfolio. Table 5 shows the correlations between diamond and other traditional market indicator returns. It also includes the correlation between diamond and market variables and the US CPI to evaluate their inflation hedging performance.

The table demonstrates that over the last years the returns of diamonds have had a negative correlation with those of gold and the S&P 500. The correlation with the fixed income proxies is positive but, the coefficient is less than 0.5 which still could be useful for diversification purposes.

Table 5: Correlation between high-end diamond and traditional market indicator returns 2005-2008

After evaluating the performance of high-end colourless and coloured diamonds the results point out that diamonds in this category provide a better risk adjust performance than traditional equities with which they are negatively correlated. Also the analysis demonstrated that the returns of large colourless diamonds have a better performance in financial terms than those from coloured diamonds. The conclusion of this analysis is that a potential investment in high-end colourless diamonds could provide an interesting tool for portfolio diversification.

Middle-end commodity type diamonds

Table 6 presents the descriptive statistics used in the univariate analysis for the four time periods considered. The most relevant findings obtained from this analysis for each period are presented hereafter.

5 year period (2008-2012)

In the period starting in a year marked by the beginning of the last financial crisis all the diamond sub-indexes presented average returns over the inflation mean for the period. Also the mean return diamonds of 1 and 3 cts in the investment and top quality sub-indexes were only outperformed by the returns on gold prices.

In terms of risk, the standard deviation for the period was comparable between gold and all diamond variables. The highest standard deviation was observed in the returns of the S&P 500. In respect of risk adjusted returns all diamond indexes performed better than the S&P 500 but were outperformed by gold and corporate bonds.

10 year period (2003-2012)

In the last 10 years the average returns of the sub-indexes for diamonds of 0.5 cts. were lower than the mean inflation for the period presenting the lowest means of the sample. The returns for 1 ct. diamonds were similar to that of the US corporate bonds in both cases while those of 3 carat stones were only exceeded by the returns of gold prices.

Regarding risk considerations, the standard deviation of all diamond sub-index returns (with the exception of top quality 3ct diamonds) were lower than the one for gold returns. Finally, concerning the risk adjusted performance diamonds of 1 and 3 cts performed better than the S&P500.

20 year period (1993-2012)

This period includes the stabilised diamond prices that followed the recovery from the important fall in the early 1980s, which resulted in a less attractive performance on price returns. In this case only larger diamonds (1 and 3 cts.) were able to beat the inflation for the whole period. The average returns of the sub-indexes for investment and top quality 1 ct. stones of better qualities were very similar to the one of the Treasury bills. The sub-indexes for the largest stones of the sample showed mean returns higher than the one of the treasury bills but lower than the other traditional assets.

Regarding risk considerations, the standard deviation for all the diamond variables was lower than the ones presented by gold and S&P500. Despite this fact in terms of risk adjust performance diamonds were outperformed by all the other variables due to their overall low average returns

30 year period (1983-2012)

This period begins in 1983, a year in which prices were still dropping after reaching their highest level in 1980. The falling trend stopped in 1985 and after that diamond prices recovered in two ways depending on their sizes. The prices for smaller stones (0.5 and 1ct.) increased slow but relatively steady afterwards. In contrast, larger stones increased their prices around 20% per year between 1986 and 1989 reaching a stable point which continued until prices started rising again in 2004.

In both cases for the last 30 years diamond prices have had long periods with low annual growth. The result of this was a low average return where only the sub-indexes for 3 ct and the lower qualities of 1ct stones were able to exceed the average inflation for the whole period. Also only the average returns of 3 ct. stones were higher than that of the government bonds. The risk and risk adjusted performance of all diamond variables was the same that in the 20 year period.

Summarising these statistics show that over the past 10 years diamonds had a better risk adjusted performance than the S&P 500. The performance was not as good in longer periods due to the long price stability that followed the recovery from the acute price fall of the early 1980s. Considering these results investors may be interested in including diamonds in their portfolio taking into consideration the particular correlations of their returns with those of other assets.

Table 6 Descriptive Statistics for Middle-end Diamond Price Index and Traditional Market Indicators Returns

Tables 7 to 9 show the correlations between the three groups of diamond sub-indexes and traditional assets. In almost every case the correlation between diamond and US consumer price indexes was above 0.8 (the only exceptions being 0.5 ct. and the lowest quality of 1ct. stones, which still had positive coefficients) showing that this type of diamonds are effectively good tools for inflation hedging.

Compared with other assets diamond variables have negative correlation with the S&P 500 in all cases and low or negative correlation with all the other variables. These correlations confirm that diamonds of this type are inflation hedging and due to their low and negative correlations with traditional assets they represent an opportunity for diversification.

Table 7: Correlations between Middle-end Investment Grade Diamond Index and traditional Market Indicator Returns

Table 8 Correlations between Middle-end Top Quality Diamond Price Index and Traditional Market Indicator Returns

Table 9 Correlations between Middle-end 1ct Diamond Price Index on Various Qualities and Traditional Market Indicators Returns

Conclusions and limitations

The univariate analysis confirmed that diamonds are assets with inflation hedging characteristics. It also showed that they have a negative correlation with traditional equities (measured with the S&P 500 as a proxy), and low or negative correlation with traditional assets such as fixed income (which used 3 month Treasury bills and Aaa US corporate bonds as proxies) or gold.

Regarding the general performance of diamond returns, the conclusion from the model results is that in on the past 10 years both types of diamonds had a better risk adjusted returns than the S&P 500, but lower than gold or Aaa bonds.

Comparing the performance between the two types of diamonds, on average middle-end diamonds, (mainly those of 1 and 3 cts.) have the best risk adjusted performance. High-end diamonds have a good performance against traditional equities, but are riskier. This is particularly true for coloured diamonds which have a low average return compared to their standard deviation. This result was expected as high-end diamonds are sold mainly in auctions and its pricing is less consistent than middle end diamonds which follow a benchmark price.

The main limitations on this analysis are related to the data availability. In the case of high-end diamonds the lack of information of the returns of 2003 and 2004 prevented the possibility of making a proper comparison with the returns of middle-end diamonds where there was available information. Also the results of the regression on coloured diamonds could have been better if a variable of colour intensity had been used.

In the case of middle-end diamond the main limitation was the use of only annual data which could not properly reflect the price variations during the year. The main impact of this is that the standard deviation of the returns of this type of diamonds might have been underestimated.

Diamond Research Survey

This section presents a compilation of the responses obtained from the 40 individuals who answered the survey. Each question is presented in the form of a table presenting the possible answer options, followed by a graph illustrating the responses and a commentary with the interpretation of the responses to each one. In some cases the average number is reported as the questions allowed for multiple choices and the percentage of each of the answer choices only reflects its relative position.

Section 1: Diamonds Price/Value

Table 10: Question 1. - In your opinion, people buy diamonds for:

Graph 7 Question 1

The aim of this question was to evaluate the trade�s perception on the relative moneyness of diamonds for final consumers. The options attempted to compare the attractive diamonds have as an investment asset against other common purchasing reasons. The result showed that according to the respondents less than half of the buyers acquire a diamond thinking that they might sell it in case of need (relating to the precautionary motive of money demand), and only one quarter purchase them as an investment (relating to the speculative motive).

Table 11: Question 2. � In your opinion, the value of diamonds is?

Graph 8 Question 2

This question looked to obtain information relating several aspects of diamond prices. The first two options aimed to evaluate if diamond prices reflect an intrinsic value or if they are valuable just because their status as conspicuous goods. In this case the number of respondents who thought the diamond value is intrinsic was twice the number of people who thought it was extrinsic.

The third option relates to the potential diamonds have to produce returns and surprisingly just under a half of the answers considered that diamonds could hold or increase their value in time. The final option tried to measure the transaction potential of diamonds, it received a positive answer from just a quarter of the respondents.

Table 12: Question 3. � In your opinion, the price of polished diamonds is determined by:

Graph 9 Question 3

This question tried to identify the market conditions that affect diamond prices. According to the trade perception the most important factor is the price and production of rough diamonds. Consumer demand and Diamond price lists were also considered important price determinants.

Table 13: Question 4. � Do you think diamond prices are volatile?

Graph 10 Question 4

This question tried to measure the perception of volatility (and hence risk of investments) of diamond prices. The response showed that just over a half of the surveyed individuals consider diamond prices volatile.

Section 2: Diamond Market

Table 14: Question 5.- Do you think diamond lab reports/certificates are:

Graph 11 Question 5

Diamond grading evaluates the 4 Cs and set the basis for standardisation in the diamond market. The only way to certify these characteristics is with the use of laboratory reports. For this reason evaluating the perceptions people in the trade have about these documents is crucial for understanding the diamond market. The responses show that more than half of the respondents think that these documents are trustworthy compared to less than 10% who think they are not.

Table 15: Question 6. � Please name the 3 institutions you trust more for lab reports:

Graph 12 Question 6

Considering that half of the respondents answered that laboratory reports should only be issued by trusted institutions it is important to know which institutions are considered trustworthy in the industry. An interesting thing was that even when people were asked to give the name of three institutions, in some cases two or just one institution was mentioned. All the responses excluding the one which said �none�, mentioned GIA (GIA certificates can be obtained in various laboratories based around the world) as their first response. After that the second and third places as trustworthy certificate issuers were HRD (Hoge Raad von Diamant) which is based in Antwerp and IGI (International Gemological Institute) which started in Antwerp but has offices in cities worldwide.

Table 16: Question 7 In your opinion, which of this changes in the industry have impacted the diamond market?

Graph 13 Question 7

The responses to this question showed that the most significant changes of the diamond industry have been the internet and the entrants of new market players in the trade. According to the comments received on this question the internet has allowed consumers to compare diamond prices with sellers that can offer lower prices as they do not have to pay as many fixed chargers as brick and mortar retailers.

Table 17: Question 8. � In your opinion, what are the main threats the diamond industry is facing today?

Graph 14 Question 8

This question tried to identify the main problems of the industry today. According to the responses the main threats are synthetic diamonds and poor ethics of some participants. From the feedback received from the survey the main problem with synthetic diamonds is that it has affected the consumer confidence as the poor ethics of some participants who have sold them as natural has been exploited and oversized by the media.

Table 18: Question 9. � Would you like to be able to protect your business from the volatility in diamond prices?

Graph 15 Question 9

This question attempted to measure the exposure businesses have to volatility in diamond prices. The graph shows that two thirds of the respondents would like to protect their businesses from volatility. The implication of this is that there could be a good reception if a derivative market proposed an instrument to hedge the risk.

Section 3: Diamonds and Investors

Table 19: Question 10. � What do you think about the relation between the diamond market and the financial markets?

Graph 16 Question 10

According to the answers to this question there is more rejection than acceptance to the mixing of diamond and financial markets among people in the trade. However the option of allowing investors in the diamond market was well received among the respondents while the option of having diamonds traded in the financial markets was less popular.

Table 20: Question 11. � What do you think would be the impact of allowing financial investors to trade in the diamond market?

Graph 17 Question 11

The response to this question shows that two thirds of the respondents think that allowing financial investors would have a positive or neutral impact in the diamond market. An interesting fact was that almost 30% of the people surveyed said that the markets should not be mixed in the previous question but said that the general impact would be positive or neutral. This shows that people in the trade may be open to the idea of receiving financial investors as competitors in the market.

Table 21: Question 12. � In your opinion, opening the diamond market to financial investors:

Graph 18 Question 12

According to this question only one third of the respondents think that opening the diamond market for financial investors is unlikely to happen. The survey shows that the main consequences of this opening would be that it would complicate transactions in the trade but also it would promote an increase in the transparency of diamond prices.

Section 4: Respondent Profile

Table 22: Question 13. � Are you involved in the diamond/jewellery industry?

Table 23: Question 14. � If you do, how long have you been involved?

Graph 19 Question 14

Table 24: Question 15. � In which country or countries does your business operate more frequently?

Graph 20 Question 15

This profile section shows that the sample included a relatively even distribution regarding the experience of the respondents. It also illustrates that the respondents operate in almost all the major markets involved in the diamond industry. Based on these results even when the size of the sample is not large enough to make definite inferences for the whole industry, at least its composition is unbiased.

Conclusion

Diamonds are a pure carbon crystal with unique properties that make it useful in the industry but also desirable as decorative items. Used as symbols of love or status, gem quality diamonds are an example of a conspicuous consumption good. Conspicuous goods were first described by Veblen in 1889 who defined them as luxury items which purpose is the public display of their owner�s wealth or social status.

There are three factors that affect the value of diamonds: their relative quality measured by the 4 C�s (Colour, Clarity, Cut and Carat weight), their origin and the certificates they have to prove the accurateness of the other factors. According to their colour diamonds can be either colourless (mistakenly but commonly referred as white) or fancy coloured.

The variations in each of the four C�s may have a significant effect on the overall diamond price. According to the results obtained in this research the two C�s with more weight determining diamond prices are carat weight and colour. In terms of origin diamonds might be natural or synthetic and legitimate or blood/conflict diamonds. The survey showed that in today�s market synthetic diamonds pose a more significant threat to the industry than blood/conflict diamonds.

Until now the diamond market and the diamond industry have been practically synonyms. The main reason for this is that traditionally the diamond operated under a cartel and private club structure (led by De Beers and the orthodox Jewish community) which controlled all the aspects of the diamond market by controlling the diamond supply and price information. Today these conditions do not persist. Recent changes in the industry demoted De Beer�s from its leadership position as the company no longer dominates the rough market. Other important factors in this change are the emergence of India and China as labour and consumer forces alongside the development of the internet. These elements have respectively changed the participant structure and the price transparency in the industry.

Considering diamonds as an investment is an idea that attracts investors in times when the performance traditional markets is slow or uncertain. That was the case of the first diamond �investment boom� towards the end of the 1970s and the first years of the 1980s. On that occasion investors were looking for an alternative to the weak dollar that followed the abandonment of the gold standard in 1971. This quest for alternatives sent investors to look into traditional hard commodities like precious metals, and also alternatives like art and diamonds.

Meanwhile the first alternatives operated in free markets diamonds at the time were under the tight control of De Beers� pipeline. By that time the company dominated the market regulating the supply with their 85 to 90% market share. However in the early 1980s two factors detonated a quick drop in diamond prices: on one side an increase in the supply with filtered diamonds from the Soviet Union and, on the other side a decrease in the consumption of luxury goods due to the financial recession that took place in the decade.

After the soaring prices driven by investor demands in the late 1970s these two exogenous shocks in the diamond market led to a price fall that hit investors and industry traders alike. As the market operated under conditions lacking of price transparency those involved were unable to foresee or afterwards fully understand the reasons of the price collapse.

Today the financial markets are turning again into diamonds, apparently forgetting or disregarding the previous crash on the perspective of achieving better returns. In contrast, traditional players of the diamond trade have not forgotten and some of them still blame investors for what happened.

From an analysis of the conditions that surrounded the collapse in diamond prices during this time, this investigation answered its second research question. The hypothesis this investigation proposes for the reasons that prevented previous diamond investments to succeed is that until very recently the structure of the diamond industry prevented the development of a free diamond market. Until recently the diamond supply was almost entirely controlled by one company which operated the industry like a monopoly. Also the private club structure of the diamond traders kept price information from the market.

In conclusion the previous attempts on diamond investment failed because the diamond market lacked of two key characteristics in efficient markets: competition and complete information. An important note is that these conditions of the diamond industry have changed over the last decade. Today the market is no longer controlled by De Beers, and the new competition level of the industry is reflected by the fact that industry giants are restructuring their participation in the industry. Another current event that is key evidence of the end of the diamond monopoly era was the separation of the Oppenheimer family from the diamond industry by selling their controlling stake in De Beers. This is a relevant sign as the Oppenheimers were to the diamond monopoly what the Rockefeller�s were to oil during the monopoly of Standard Oil.

The main research question of the investigation was if diamonds could be considered a financial investment. To answer it, this dissertation analysed two things: the conditions and characteristics of the diamond market and the performance of the potential returns of diamond prices. The first part of the answer used a survey to measure the market perception on the subject and the changes in the conditions outlined in the answer of the second question. As for the performance of diamond price return the investigation used a univariate analysis of the returns on diamond indexes.

The results of the survey showed that players in the diamond industry do not have a clear perception of the impact financial investors could have in the diamond market. More than a half of the respondents stated that the diamond and financial markets are different entities that should not be mixed. A third part of the sample considered that opening the diamond market for financial investors is unlikely to happen and in case it happened indeed it would complicate the transactions for the trade.

In contrast to those answers, around 40% of the respondents thought that the overall impact of financial investors in the diamond market would be positive and 30% said it would be neutral. The main concern of mixing the diamond and financial markets, measured through the commentaries received to the survey is that having diamond prices quoted as commodities would confound consumers who would not understand the difference between the quoted prices and the prices paid in retail level. Also over 60% of the survey participants consider diamond prices volatile and would like to have tools to protect their businesses from this volatility. This need could be targeted through the development of an OTC derivative market for diamonds.

This research evaluated the return performance of diamond prices according to the principles stated in the modern portfolio theory. Using an univariate analysis the investigation compared the performance of diamond returns against that of traditional market indicators such as the S&P 500, the US 3 month treasury bill, the average yield of Moody's Aaa corporate bonds and physical gold oz. Also to evaluate the inflation hedging characteristics of diamond it compared diamond prices with the US consumer price index as a proxy to measure inflation.

The results showed that both high-end and middle-end commodity type diamonds represent an inflation hedging asset which had better risk adjusted performance than the S&P 500 over the past 5 and 10 years (8 years in the case of high-end diamonds).

The analysis revealed that compared with other assets diamond variables have negative correlation with the S&P 500 in all cases and low or negative correlation with all the other variables. Also, comparing the performance between the two types of diamonds, on average middle-end diamonds have a better risk adjusted performance than diamonds in the high-end type.

The main conclusion of this analysis is that diamonds may be an attractive investment option for investors in terms of the key elements highlighted by the modern portfolio theory.

Recommendations

Further Research

As topics for further research this investigation identified the following potential subjects:

The impact of De Beers� strategy change in the diamond industry.

The new industrial organization in the rough diamond market.

The impact of internet based retailers in the diamond industry.

The impact of synthetic diamonds in consumer perceptions.

A deeper study of the determinants of diamond prices.

The impact country politics have in the diamond industry.

The potential the development of emerging countries have in the consumption of luxury goods.

Evaluate the diamond trade�s perception of diamonds as an investment asset using a wider sample.

Diamond investment

Also, based on the analysis of the current state of the industry, the available trade and academic literature, and the results of the quantitative models and the market survey; the researcher would advise that the diamond industry should allow the entrance of financial investors to the diamond market.

The recommended method to achieve this opening would be the formalisation of the existing trade exchanges as OTC markets. According to the research this opening would be beneficial to both investors and trade members. Investors could benefit from the inflation hedging and diversification opportunities offered by the returns of diamond prices. They would also provide liquidity and risk hedging to the industry in the process.

An important requirement for this potential market to succeed is the guarantee of price transparency. In order to provide such security to the market the exchanges should try to obtain a qualification from a major rating agency such as Moody�s or Standard and Poor�s.

The reason for selecting the opening of the existing exchanges to investors rather than listing diamonds as a commodity or creating financial instruments such as funds is that the complexities of diamond pricing require specialist knowledge to be fully understood. By having the financial investors entering into the existing exchanges, it can be guaranteed that the investors fully understand the risks of investing in diamonds and the complexities of the market.

If these conditions are met, there is no reason for which diamond could not become an investor�s best friends.