Introduction
The present Master thesis is aiming to show the trends of increased volatility of the
commodity prices, under conditions of increased Globalization and Financialization in the
last decade. The subject was provoked by personal experience, working as marketing
analyst in major steel producing companies for many years, but also from the financial
crisis, caused by the failure of the derivative market in 2008, which caused world financial
crisis. The results could be interesting to any representative of the iron ore and steel
industry, different institutions related with anti-trust regulation, and fighting with financial
frauds on the financial market, or any other person interested in the reasons for the world
financial crisis, caused in 2008
The thesis is separated in two main parts - Theoretical and Empirical Analysis. The first part
is outlining the major differences in the theories about commodity pricing and the supplydemand relationships on the real and financial markets, and is clarifying some of the major
macro factors, which are influencing the price levels. The Empirical part is separated in two
parts - the first is analyzing big quantity of macroeconomic factors, trying to find the major
drivers for the commodity price volatility, based on statistical information from World bank,
UNCTAD, OECD, and other information sources. The second Empirical part is analyzing in
details the volatility of the iron ore prices, caused by the new pricing system in the iron ore
and steel industries. Analysed are the Global Iron ore Supply- Demand balance, the
Consolidation process in the iron ore and steel business, and its effect over the profitability
of the companies. At the end, is explained the nature of the change of the pricing system,
and is calculated and analyzed the volatility of major export iron ore benchmark prices.
We have also summarized the main results from the analyzes at the end of each part –
Theoretical and Empirical.
1
Theoretical Analysis
In the theory exposed below, we would like to outline some major macro economic factors,
related with the supply and demand on the real and financial markets, affecting to higher
extend the price volatility of the commodities. Besides that, we would like to delimitate the
real and financial markets, and show the differences, similarities, and links between their
supply- demand relationships. Considered are also some main theories related with the
pricing of the commodities on the real and the financial market . At the end of the
theoretical analysis, we have outlined our results.
1.Definitions
In this first paragraph from the thesis, we would like to outline some major definitions from
the economics, related with the subject of our study – Commodity prices, Price Volatility,
Globalization and Financialization.
1.1.Price formation and Volatility of commodity prices
Prices of commodities on the physical market, are formed from fixed, variable costs and
profit margin. The costs are usually related with buying of factors of production - labor,
machinery, raw materials, lands, and etc ( Besanko, 20071). In the international trade the
commodity pricing is formed under different terms of trade according to Incoterms transport, insurance, import/export taxes, payment and etc. On the financial market
( called also “paper” market), the commodity prices are formed by different price
indices, based on spot mid- and long- terms. From main importance about the price trends,
are the market trends and information about the underlying physical commodity market.
There is almost never any real delivery of commodity on the financial market, but the main
idea is to hedge the price risk on the physical market with derivative contracts.
The price volatility is a “measure of dispersion of prices, higher when prices are more
disperse, and lower when prices are more concentrated. Volatility does not measure the
direction of the price changes, but the magnitude of the fluctuation itself”( International
Cotton Advisory Committee, 20102). The price volatility could be measured in different
ways: through the relative price spread, coefficient of variation, and standard
logarithmic deviation of prices. Burda( Burda, M., 1997)3 considers, that measure of the
price volatility could be the coefficient of variation, measured by a standard deviation of a
price, divided by it’s mean.
According to studies of the financial market, the price volatility of commodities, is in many
cases explained by the level of inventories ( Geman, 2005)4. After studying a world
database of futures of commodities, Geman is considering that the price volatility is exact
inverse function of the inventory. The study shows that the inventory levels for major
base metals in almost all cases are coincided with high price levels. Fama and French also
1
2
Besanko, “ Economics of strategy”, Whiey and Sons, 2007, p.12
“World Cotton Situation: Record prices and Hugh volatility”, International Cotton Advisory Committee, 2010
Burda M.,Wyplosz C, “Macroeconomics A European Text”, Second Edition, Oxford University Press,
1997,p.9
4 Geman, Helyette, “Commodities and Commodity Derivatives : Modeling and Pricing for Agriculturals, Metals
and Energy”, John Wiley & Sons, 2005, pp.25-26
3
2
have detected that the variance of the prices decreases with the inventory levels, while
Williams and Wright discovered that the price volatility increases after the harvest for
agricultural commodities.
The results from the studies mentioned, are confirming the theory of storage and
convenience yield of commodities. The theoretical link between the price volatility and
the storage and convenience yield theories could be listed in several points: 5
- The price volatility is closely related to the global stock, since in case of shifts of
supply and demand, the inventories should provide the buffering effect.
- The commodity price and price volatility are correlated, and negatively related to the
inventory level.
- The volatility of forward prices is decreasing reaching their maturity date, assuming
that everything else being equal.
- The different shapes of the forward contracts are explained with the convenient yield
and storage theories, thus with the dependence between commodity stocks and
price volatility
Many authors are arguing that prediction of commodity prices is possible if the quantities
produced and stored are known. For some commodities with limited reserves, the
quantities of proved reserves should be also considered in long- term calculations. This
way it would be possible to predict shifts in the supply side and detect the supply- demand
equilibrium, which is primary dependent on the inventories. Using similar methodologies Ng
and Pirrong found out that the metal prices return variances from spot and forwards, are
increasing with low inventories ( Geman, 2005).
Geman is also stating that after 40 years of different financial studies related with the
connection between the news arrival, trade activity , changes in prices and volatility,
several main relationships are detected:
- The news arrival is generating more active trading
- The price volatility is increasing with the higher trading trends
- Unexpected changes in the volatility ( stochastic volatility ) is occurring both with
higher volumes of trade and with increasing of the individual trades.
1.2.Globalization
The term Globalization could have different meanings according to the context, but in
economic context, according to Neary ( 2002) it means “Increased interdependence of
national economies, and the trend towards greater integration of goods, labour and
capital markets” ( Marrewijk6). The trends of globalization in the world economy have
increased after the Second World War, and especially from the last decades of the last ,
and the beginning of the 21st century. Main reason for this trend was the increasing
international trade regionally and globally. The increased dynamic of people migration,
globalization of capitals, and corporations, have created new strategies and views about
the world economy and company management. The next steps for market development
and integration in the global economy, after the international trade, are the licensing,
franchising, contract manufacturing, outsourcing, joint venture, mergers and
acquisitions, Greenfield investments and many other variations( Kotabe, 20087). This
Geman, Helyette, “Commodities and Commodity Derivatives : Modeling and Pricing for Agriculturals, Metals
and Energy”, John Wiley & Sons, 2005, p.28
6
Marrewijk Ch., “ International Economics, Theory, Application and Policy”, Oxford University Prss, p.17
7
Kotabe, M., “ Global Marketing Management”, John Wiley and Sons, 2008, p.312
5
3
way were created many multinational companies, and their cross- border activities,
mergers and acquisitions, have created new global practices in the management and
marketing, as well as bigger market concentration and oligopoly structures. The
globalization trend in the international business, was the main reason to rearrange and
expand all the classic theories in global view, creating global market competition, global
finances, global marketing and management strategies, global synergies and etc. Together
with the globalization paradigm, the increasing of the global demand, have created global
markets and global pricing. The main tool for global pricing remains Internet, which
provides cost transparency, since everybody could check the price levels for almost
every product and service worldwide on-line ( Kotabe, 20088). Another dimension of the
global pricing are the price quotes on the financial markets, which fluctuations are causing
big changes in the prices on daily basis, for example the oil prices.
1.3.Financialization
The financialization of the economy is in many cases interpreted in many ways, in general
associated by the dominance of the financial market over the real economy, or any way to
receive profit without through financial speculation, rather than using real commodity trade
( Krippner)9. According to Epstein, the term financialization of the economy could be
explained with the increasing role of the financial motives, financial markets, financial
actors and financial institutions, in the operation of national and international economies.
Other authors like Ozturk ( Ozturk, 201010), are considering different dimensions of the
financialiaztion such as: priority investments in financial equities, than to fixed investments
by companies and individuals, detachment of finance from production, comodification of
the finance and the substitution of the labour by capital, use of the corporate profit for future
mergers and acquisitions.
2. Delimitations between the Real and Financial Economy ( Markets).
It is very important to determine what means the real economy (physical/real market) and
the financial economy (financial markets) as economic terms, because further a deeper
analysis of them will be done. For us it is important to determine how are both markets
functioning, what factors are determining the supply and demand, how they differ from each
other, and at the same time how are they linked together.
The real economy is concerned with production and consumption of goods, services and
resources, and the incomes associated with the productive activities. i.e. the real economy
is related with the real/product markets and their functioning. The Financial side of
the economy is reflectied on the paper/ financial markets, where assets - monetary and
financial instruments as stocks, bonds are traded, exchange rates, interest rates and
indexes. (Burda M., 1997, pp. 9-10)11
The main participants on the real markets are individual consumers and households,
business firms and governments on state and local levels. Their motivation to participate
in the real market is to maximize their utilities, profits and general welfare. The main
8
Kotabe, M., “ Global Marketing Management”, John Wiley and Sons, 2008, p.611
9
“ Epstein, G.” Financialization of the World Economy”, 2006, p.1
Ozturk, O. “ The question of financialization” ,Ondokuz Mayıs University
10
11
Burda M.,Wyplosz C, “Macroeconomics A European Text”, Second Edition, Oxford University Press, 1997,pp.9-10
4
function of the real market and their participants is to specialize in some production and
exchange goods, energy and resources in optimized way. The most important financial
market’s participants arethe financial intermediaries and institutions such as banks,
pension funds, and other intermediaries representing business firms, households
and governments entities. Their rational activity is aiming to increase the capital invested
through profits and risk premiums. (Schiller, 2008)12. All those market participants on the
financial market could be considered as traders, differentiating in three groups – hedgers,
speculators and arbitrageurs13( Hull, 1997). Hedgers are facing the risk related with the
price of the asset, using the derivatives to reduce and eliminate the risk. The speculators
are betting on the future movement in the price of an asset to get extra leverage.
Arbitrageurs target is to take advantage of the differences in prices of the same derivatives
in two different markets. The services the financial market and it’s participants are providing
is reducing the cost of loanable funds, and decreasing savers costs to find suitable lending
or investment opportunities. Thus the financial markets are allocating financial resources
more efficiently, reducing the search and information costs of the participants.
In a summary, the main determinants of the Real and Financial markets are shown on Fig.A
below. There are main differences, as well as some linkages between them. Both type of
markets are connected directly ( marked with bolded letters) through their scope of trade
(Goods/Resources-Commodity derivatives), the market participants (Households,Business
Firms,Governments and their intermediaries) and their interests (Profits). The other
determinants listed below (non-bolded letters), are differentiating for both markets, even
though they might be also connected through the prices, interest rates, exchange rates and
investments.
Fig.A. Determinants of the Real and Financial markets14
Determinant
Real markets
Financial Markets
Scope of trade
Goods, Services,
Resources
Market participants
Households, Business
Firms and Governments
Main Functions
Specialization in production
and optimizing the
exchange of goods,
services and resources
Maximizing the Utilities,
Profits and Welfare
Assets, Stocks, Bonds, Exchange and
Interest Rates, Indexes, Commodity
derivatives
Financial Intermediaries- Banks,
Pension/Investment/Insurance Funds,
Intermediaries representing Households,
Business Firms and Governments. All
participants could be classified in three
groups- hedgers, speculators and
arbitrageurs.
Specialization in efficient financial resources
allocation trough search and exchange of
information about loanable funds and
investment opportunities
Maximizing the Risk premiums, leverages,
Profits
Main target of the
market participants
Schiller R.Bradley, “ The Economy Today”, Eleventh Edition, McGraw-Hill Irwin, 2008, pp.639-641
Hull C. John, “ Options, Futures and other derivatives”, Third edition, Prentice Hall International , 1997, pp.10-13
14
Schiller R.Bradley, “ The Economy Today”, Eleventh Edition, McGraw-Hill Irwin, 2008, pp.639-641
12
13
5
3.Major financial macro factors affecting the volatility of commodity prices
The interest, exchange currency rates, and the inflation are inter-related, and very
important financial macro factors, influencing the volatility of the commodities on the real
market. They could change the bargaining power of the market participants, according to
their market fluctuations. At the same time, these are financial factors, and actively used
on the financial market, both for lending loans, and executing international settlements, as
well as for derivative trade. Usually those three factors are interrelated, and especially the
correlated increase of increase of interest rates and inflation, could cause increased price
volatility, and even commodity or asset bubble. On the opposite, when the inflation and the
interest rate are decreasing, the volatility of the commodity prices, is also decreasing.
3.1. Interest rate
The interest rate is called the price to use money, usually taken with a bank loan. In
macroeconomic frame, the interest rate is related with the cumulative money supply,
representing the currency held by the public, their balance accounts, savings, and money
market mutual funds ( Schiller, 200815) The level of the real interest rate, depends on
difference between the nominal interest rate and the anticipated inflation rate, which
creates additional volatility for the commodity prices.
According to Frankel16, the main mechanism for influence of the interest rates on real
commodity prices is called “The carry trade”. He considers that high real interest rates are
reducing the demand for storable commodities, or increasing the supply, thus decreasing
the commodity prices. He claims that the reason for the decrease of the prices is directed by:
- Incentive of the producers to produce today rather than tomorrow, having in mind the
increasing cost of the credits, resulting in oversupply of production.
- Decreasing motivation to carry inventories, due to increasing costs of carry
- Encouraging the speculators to switch from spot commodity contracts to treasury bills.
On the other side Frankel is considering that the lower interest rates are raising the commodity
prices, because they are an incentive to increase the carrying inventories, for producers to
delay production, and for speculators to be more involved into spot commodity contracts.
3.2. Exchange currency rate
The exchange currency rate is the price of the currency of one economy, expressed by
price of the currency of another country, or could also be referred as domestic price of a
foreign currency (Schiller, 200817).The levels of the exchange currency rates are depending
to higher extend by the national trade deficit and the balance of payment, because the
currency is used in import and export operations for buying and selling commodities or
services. The levels of the exchange rates could be appreciated or depreciated due to
some classic supply- demand changes in the incomes, prices, product supply, relative
interest rates, and speculation. The value of the exchange rate could also depend from the
levels of the gold reserves of a national economy, as guarantee for buying a currency.
15
Schiller R.Bradley, “ The Economy Today”, Eleventh Edition, McGraw-Hill Irwin, 2008, p.300- 302
Frankel A.Jeffrey, “ The effect of the monetary policy on real commodity prices”, Working paper 12713, National Bureau
of Economic Research, Cambridge, 2006, p.4
17 Schiller R.Bradley, “ The Economy Today”, Eleventh Edition, McGraw-Hill Irwin, 2008, p.716.
16
6
Besides that , the currency exchange rates are very often pegged, manipulated,
devaluated, or left free from the national governments. The pegging is usually done by
agreement between IMF and some national government, the Euro and the USD are
example for free- floating exchange rates, and the Chinese Yuan is an example for
devaluated ( depreciated) currency. The role of the governments for the levels of the
exchange rates is very big, and could influence the general economic development of one
country, through increase or decrease of imports/exports. This could mean, that the
strengths or depreciation of certain currency, could affect the level of comparative export
and import prices.
3.3. Inflation
The inflation represents an average increase of the level of prices ( not of a specific price),
while the deflation is the decrease of the same average price. Usually it is measured by the
Consumer Price Index ( CPI), which represents the average price change of a basket of
goods and services (Schiller, 200818). The impacts of the inflation levels are many. It
redistributes incomes by alternating relative prices, income and wealth, because the
inflation is not affecting equally and at the same time all the members of the society. At
macro level, the increasing inflation is reflecting negatively over the total output, because
increases the price uncertainties. On the other side the anticipation for increasing prices,
could stimulate the spending, forcing the government to initiate restrains, which are
threatening the full employment. According to the Philips curve, there is a negative
relationship between the inflation and unemployment: when the unemployment is low, the
actual inflation is increasing, and when the unemployment increases, the inflation drops
down ( Burda, 199719). There is also another phenomena called “wage- price inflation
spiral”, when both sides are bargaining increasing of their incomes, and the inflation is
increasing ( Hazlitt20). The production costs are separated to labour and non- labour, and
depending on which one first increases, the inflation shows positive or negative effect over
the unemployment, and/or prices.
4. Supply and demand on the real and financial markets
The Supply and Demand Concept, which could predict the market price, is established by
Marshall in 1890, and is fundamental concept in economics is valid for all types of markets.
The Demand is determined as “ The ability and willingness to buy specific quantities of
good at alternative prices in a given time period ”21 . The Supply is “ the ability and
willingness to sell (produce) specific quantities of good at alternative prices in a given time
period” ( Schiller, 2008). The market price is determined when the quantity demanded
equals the quantity supplied, known also as “Equilibrium” point of the supply- demand.
In the present paragraph, first a short overview of the supply and demand on
macroeconomic level will be done, focusing on the circular of the supply and demand
between the Real and Financial Markets. This way the linkage between them will be
presented from another point of view, in addition to those presented in paragraph 1. For
18
Schiller R.Bradley, “ The Economy Today”, Eleventh Edition, McGraw-Hill Irwin, 2008, p.130- 132
19
Burda M.,Wyplosz C, “Macroeconomics A European Text”, Second Edition, Oxford University Press, 1997,pp.312
20
Henry Hazlitt, “ What do you now about inflation?”, Mises Institute
21
Schiller R.Bradley, “ The Economy Today”, Eleventh Edition, McGraw-Hill Irwin, 2008, p.45
7
deeper understanding of the linkage, the factors impacting the supply and demand on the
Real and Financial Market will be presented on a second stage. At the end of the
paragraph the microeconomic theory behind the supply and demand on both markets will
be represented, in search for some principal differences or similarities.
4.1. Overview of the circular flow of the supply and demand, between The Real
and Financial markets and their participants.
All the participants from the real/product markets and the financial/paper markets are linked
together supplying and demanding either goods, services and resources, or factors for
production. The financial market is a part of the factor market, which is organizing the flow
of land, labor and capitals between the consumers, business firms and governments. In
the present study we will not focus on the land an labor factor markets, but only on the
financial one and it’s interaction with the product market trough the supply and demand. On
figure B. is represented an overview of the product and factor markets, and the circular flow
of the demand and supply of goods and services from one side, and the production factors
from the other, between the market participants. Business firms demand factors for
production from the factor markets and at the same time supply with goods and services
the product markets. The product markets are supplying the consumers with the goods and
services, while the consumers themselves are supplying capital, land and labor to the
factor markets. The factor market itself is directly connected also with the governments,
which acquire resources from the factor market, and provides services to the business
firms and consumers directly or indirectly and without explicit price (education, national
defense, highways)22 (Schiller, 2008).
Focusing deeper on the circulation of financial market ( Fig.C), we can say that the financial
intermediaries such as banks, insurance companies and stockbrokers, are transferring the
purchasing power between factor and product markets trough optimizing their spending
and savings23 ( Schiller, 2008).
22
23
Schiller R.Bradley, “ The Economy Today”, Eleventh Edition, McGraw-Hill Irwin, 2008, pp.43-45
Schiller R.Bradley, “ The Economy Today”, Eleventh Edition, McGraw-Hill Irwin, 2008, pp.640-641
8
Fig.B. Circular Flow between Product and Factor Markets, Government, Business
firms and Consumers.
Real /Product
Markets
Goods and
Services
demanded
Consumers
Goods and Services
supplied
Governments
Business Firms
Factors of
production
demanded
Factors of
production
supplied
Factor Markets
(Capital, Land,
Labor)
Fig.C. Circular flow between the Financial, Factor and Product markets.
Income
Real /Product
Markets
Factor Markets
(Capital, Land,
Labor)
Spending
Saving
Spending
Financial markets and
intermediaries
(Banks, stock and bond markets
collecting consumer and business
savings, state and local budget)
)surpluses)
9
4.2.Equilibrium price and shifts in supply and demand on the real (physical) market
The prices determined on the real market are called also spot prices. They are fixed
usually between suppliers, buyers and traders for immediate delivery of a commodity/goods
or with some minimum lag depending on the technical constrains of the delivery
( Geman,2005).24 Any deal with lag longer than the technical one, becomes a forward
contract where the seller and buyer declare their rights and responsibilities about the
delivery. The risk related with the real/spot market depends on the dynamic and variability
in prices, delivery, quality and financial resources. The spot price dynamic depends from
one side on the stock availability or the production possibility of the supplier. On the other
side it depends on the terms of delivery agreed according to Incoterms between the buyer
and the seller. The cost and the risk of the transportation is sometimes also covered by an
insurance. The risk concerning the quality is related with the possibility of variability of the
quality of the product. The credit risk also exists in the sport market since the financial
resources are always needed to bring one deal to the final stage.
As we already have mentioned in previous paragraph, that the market demand depends on
the number of the potential buyers, and their tastes regarding a certain and the alternative
goods, incomes and changes in expectations. From the other hand, the market supply is
determined by the number of the sellers, the technology, factor costs, other goods, taxes
and subsidies and expectations. The change in those factors could affect shifts in the
supply or demand on the market, and respectively – in the equilibrium price. Those shifts
could be both in the quantities supplied/demanded ( along a given supply/demand curve),
or shifts in the supply/demand (shifts of the supply/demand curves themselves) 25. The
Equilibrium price is “The price at which the quantity of good demanded in a given time
period equals the quantity supplied” ( Schiller, 2008)26.
In case the quantity supplied on the market is more than the quantity demanded, there is a
market surplus existing (Surplus S′/D′, Fig.5). In the opposite case, when the demand is
bigger than the supply, we have a situation of shortage of quantity ( Shortage S/D, Fig.5) To
overcome the surplus, buyers and sellers would decrease the prices until, the equilibrium
price adjusts on a lower level ( from E2 to E1, or to S2, D2) When a shortage exists, the
market participants, would do the opposite- will increase prices to adjust them at higher
equilibrium level (from E1 to E2 or to S2, D2) On Fig.5. is shown the change in equilibrium
price due to shifts of the supply and demand curves – changes of the curves themselves
and changes along the curves. We can see that when the demand increases and the initial
and the new demand curves- D and D′ are shifting to the right, the initial equilibrium price at
point E1, is moving along to the supply curve S to the next higher equilibrium price D2. The
equilibrium price is also increasing when the supply is decreasing ( from S to S′ ), and the
new equilibrium price is S2. At Equilibrium point E1 we have surplus quantity in the area
above E1, and shortage below the same point. The same way the surplus and the shortage
are above and below in the second equilibrium moment- E2. ( Schiller, 2008 )27
Geman, Helyette, “Commodities and Commodity Derivatives : Modeling and Pricing for Agriculturals,
Metals and Energy”, John Wiley & Sons, 2005, p.2-3
25 Schiller R.Bradley, “ The Economy Today”, Eleventh Edition, McGraw-Hill Irwin, 2008, pp.48-59
26 Schiller R.Bradley, “ The Economy Today”, Eleventh Edition, McGraw-Hill Irwin, 2008, p.56
27 Schiller R.Bradley, “ The Economy Today”, Eleventh Edition, McGraw-Hill Irwin, 2008, p.56-59
24
10
4.3.Price Elasticity of demand – Real market
The price elasticity of demand is measuring the sensitivity of the quantity demanded, to the
change in the price. The formula used for calculation of the price elasticity of demand is as
follows ( Besanko, 2007) 28:
ή= ΔQ/Q0
ΔP/P0
;
ΔP= P1- P0, ΔQ = Q1 - Q0
Where, ή is the price elasticity of demand, P- prices for the periods 0 and 1,
and Q- quantities for periods 0 and 1
When ή is less than 1, the demand is inelastic, and when it is more than 1, the demand is
elastic. On fig.D, we could follow the changes in the demand and the supply ( green and
orange lines) , and their respective price changes ( points. E1 –D2, and E2- S2)
Fig.D. Equilibrium price and Supply- Demand Shift- Real market
70
60
50
Initial Demand
40
New Demand
Initial Supply
30
New Supply
20
10
0
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95 100
Source: own calculations
28
Beasnko,” Economics of Strategy”, John Wiley and Sons, 2007,p.24
11
4.4.Price Equilibrium between Hedgers and Speculators on the Financial market
The idea behind the theory of the Capital Asset Pricing Model (CAPM) introduced by
Sharpe and Lintner in 1964-65, is that “ the value of an asset today depends on the
difference between the expected terminal value of the asset, and an appropriate risk
adjustment discounted to the present at the riskless rate of interest ” ( Stoll and Whaley,
1993)29.The model is featuring that futures require no investment, and the expected return
equals only the future contract’s market risk premium ( no riskless return is earned). In
other words, CAPM is indicating the possibility for speculators to receive risk premium for
holding future contracts. Since the future contract is a zero- sum game, possibly the
hedgers will be likely to pay the risk- premium to the speculators, in order to eliminate the
risk of holding the commodity. In fact, the hedger needs to consider the correlation
between the future price and the price of the underlying commodity, but also the futures in
his entire portfolio of assets. Fig.E below is showing how the hedgers and speculators are
interacting between the current and expected spot price, determining the equilibrium future
price.
Fig.E. Equilibrium of Future prices – Hedgers and Speculators
Future price Fo
S
Eo ( S̃ т )
H
F*o
S
H
Short
Long
Hedgers Short
Position
Futures
position
Speculators Long
Position
Stoll H., Whaley R., “ Futures and options – Theory and Applications”, South-Western Publishing Co., 1993,
pp.66-72
29
12
The equilibrium future price determination assumes that the hedgers and speculators share
homogenous expectations about the market, and a systematic risk exists. It is assumed
that he hedgers have position in the underlying commodities, and the line HH depicts their
position on the future prices. HH crosses the vertical axis of Future prices below the
expected spot price, because hedgers want to transfer the risk of storing the commodity.
The slope and the position of HH depends on the price risk of the commodity itself and the
degree of willingness of hedgers to take a risk. The SS line from the other side, is showing
the position of the speculators to accept future prices. SS is crossing the vertical axis at the
expected spot price in the future. In case the expected spot price is the same as the
expected future price (Eo ( S̃ т ) = F*o ), the speculator is not motivated to take neither long
or short position. He will be motivated to take long position and earn a risk premium
when the future price falls below the expected spot price (Eo ( S̃ т ) > F*o ). In such
situation, he would earn a risk premium equal to the line fixed within Eo ( S̃ т ) and F*o (
see fig.E). If the future price F*o falls above the expected spot price Eo ( S̃ т ),
speculators earn risk premiums by taking short positions. The slope of the SS line is
depending on his willingness to take the risk and earn larger risk premium. On fig.E the
equilibrium price F*o is determined in such a way, that that the short positions of the
hedgers equal the long position of the speculators. Thus, for speculators the difference Eo
( S̃ т ) - F*o is the risk premium they receive from hedgers for the risk of holding the
commodity asset.
Hull is also commenting the equilibrium future prices30, saying that according to Hicks and
Keynes, the future price will be always below the expected spot price (normal
backwardation), if there is a trend for hedgers to hold short position, and at the same time
speculators prefer the long position. Thus, the speculator would trade only if the
expectation is that the future price will rise and he would get a risk premium. Hedgers from
the other side prefer to enter slightly negative payoff for reducing the risk of commodity
price fluctuations and keeping a storage. In case the opposite situation occurs : when
hedgers are tending to hold long positions, and the speculators – short, the future price will
be above the expected spot price (contango). The reason for this, is again because
speculators expect compensation for the risk they are bearing, but in order to get it, the
future prices should decline over time.
On the other side Dusak 31 is arguing, that there is no systematic risk in the future
contracts. He is assuming that there are no upward or downturn trends in the futures over
time, and there is no need to compensate the risk. He thinks that the future prices are
unbiased predictors of the expected spot prices, and that speculators do not make profits.
According to Tesler, the systematic risk exists, but the speculators earn no risk premium.
The lack of profit is possible if there is a zero profit game between amateur speculators
who make losses, and professional speculators who earn premiums from the market. If we
try to synthesize the views of Tesler and Dusak, it seems like a positive risk exists, but
there is no risk premium and the hedgers would receive risk insurance at no cost.
Under this assumption, the line SS on fig.E would be horizontal and would cross the
vertical axis at Eo ( S̃ т ).
Hull C, John, “ Options, Futures and Other derivatives”, Third Edition, Prentice Hall International Inc., 1997,
p.68-69
31
Stoll H., Whaley R., “ Futures and options – Theory and Applications”, South-Western Publishing Co.,
1993, pp.68-72
30
13
When we compare the equilibrium supply- demand models both on the real and financial
markets, we could see the difference. While the price on the real market is fixed in one
moment between both parties, and requires physical delivery., the deals on the financial
markets are done for future periods, they are not binding for arbitrage, and are in general
not related with any physical delivery of goods.
More details on the main derivative contracts, could be found in files attachments, copied
on a cd.Below, we will expose only the summarizing table, extracting their main features.
5. Comparison between Spot, Future, Option, Forward and Swap contracts
In order to summarize the major financial instruments for commodity derivatives, fig. F is
representing the spot, futures, options, forwards and swaps in one table according to their
similarities and differences. The information about the spot prices is given from one side to
relate the real market pricing with financial market pricing. From the other side the spot
prices in the table include information also about the price indices traded daily on spot
basis on the financial market.
Fig.F. Comparison between Spot, Future, Option, Forward and Swap contracts
Similarities and differences
Spot
Traded on the exchange ( clearing house used as
X32
Future
X
Option
Forward
Swap
X
mediator between both parties)
Traded on the OTC market ( between two parties)
X
Standardized contract
X33
Non standardized contract
X34
Spot price of underlying commodity used for hedging
X
X
Other derivative/financial instrument used for hedging
One delivery date
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X35
X
Range of delivery dates
X
Settled at the end of the contract
X36
X
Settled daily (or on smaller periods before maturity)
X
X
Real delivery of commodity - option
X
X
X
X
Exchange of cash/ margin differences- option
X
X
Opportunity to be closed before maturity
X
X
No opportunity to be closed before maturity
Source: Hull, 1997; Geman 2005; own analysis
X
X
X
X
X
X
37 38
32
Spot prices quoted on the exchange are reflecting the spot prices on the real market, or are indices formed on the
base of information about the dynamic of spot prices from the real market
33
Means the spot price or index is quoted according to standard formula determining the quality, location of delivery,
size of the lot and etc.
34
Means spot price according to contract for delivery on the real market, which could be customized between the
buyer and seller of the commodity
35
The European options have one delivery date and are exercised at the end of maturity, can not be closed before that
36
The American options can be settled daily, exercised before maturity and closed before maturity
37
Hull C, John, “ Options, Futures and Other derivatives”, Third Edition, Prentice Hall International Inc., 1997,
p.40
14
From fig.F., we could derive the main similarities between futures, options, forwards and
swaps as commodity derivatives as follows:
- Most of them could be applied on the OTC market
- The contracts are in general not standardized
- All of them are using the spot price of the underlying commodity for hedging
- In most of the cases, range of delivery dates are possible and contracts could be settled
daily or on shorter periods, against exchange of cash settlement.
- Most of the commodity derivatives are giving opportunity to be closed before maturity
- The options and swaps are the most flexible commodity derivatives and do not imply the
delivery of physical commodity
The main differences among the commodity derivatives mentioned are as follows:
- Forward and swap contracts are in general not or rarely traded on the exchange, while
futures are traded predominantly there
- Only the options and swaps could use other derivatives as underlying for hedging
- Only the forward applies only one delivery date. ( plus some of the different types of
options and swaps )
- The Forward is settled at maturity, while the future is settled daily
- The Forward is the only derivative that can not be closed before maturity.
Relating this analysis to the spot prices and the real market, we could summarize that the
only commodity derivatives, which could be associated with real delivery of physical
commodity, as option in their contracts are the futures and forward contracts. Though in
practice, the futures are rarely used for delivery of commodity, since they could be closed
before maturity and usually are leading only to exchange of cash settlement. In the case
with the forwards, at their maturity, buyer and seller agree either to deliver the commodity,
or to exchange only cash settlement difference between the forward price and the current
spot price at maturity. Comparing the spot prices with futures and forwards, we could also
say that the prices formed on the real market, are driven more by the idea of the industry
based added value chain and the marketing concept of delivering value for the customer.
On the other hand the motivation of pricing on the financial market is only partially related
with creating some added value for the suppliers in case of hedging physical commodities
on the financial market and exercising delivery. However in most of the cases futures,
forwards, options and swaps are only financial instruments bringing eventual added value
to market players based on the spot price of the underlying commodity. Those financial
instruments do not add real value to the customers, but only to the financial players. Those
opportunities are avoided when the spot price at maturity date is on average the same as
the future price in the contract.
Geman, Helyette, “Commodities and Commodity Derivatives : Modeling and Pricing for Agriculturals, Metals
and Energy”, John Wiley & Sons, 2005, p.6
38
15
6. The Convenience yield, the Storage theories and the Black- Scholl model
From the formulas of the theory of Cost of Carry, copied as attachment on the CD, we could
summarize that the profit from the futures could be negative, positive or neutral depending
on the level of the future prices, spot prices and the cost of carry. Hull is dividing the futures
and forwards as investment assets in three main categories – providing no income,
providing known dollar income, and providing known dividend yield. In case the assets are
for consumption, it is not possible to obtain future prices as a function of the spot prices and
other variables. For such cases the term convenience yield is valid. The convenience yield
measures the extend to which one commodity user feel that the benefits from ownership of
physical commodity, are more than those which the they could obtain by owning future
contract. Such benefit could be a profit from local shortage or keeping the production
process. The convenience yield is representing the market’s expectation about future
availability of the commodity. If the possibility of shortage during the time of future contract
increases, the convenience yield is likely to be bigger. On the opposite- if the inventories of
the user are high, the possibility for a shortage is low, and thus the convenience yield
decreases.( Hull, 1997 )39
During the 1930’s and 1940’s economists as Kaldor and Working were studying the
Storage and yielding theories.40 The theory of storage is focusing on the potential benefits
of holding a storage of commodity – their productive value to meet certain demand, and
eliminating difficulties with disruption of the supply- chain for production. Later Tesler is
defining the convenience yield as “timing option of the commodities”, which allows the
holder of the commodity to put it on the market when the prices are high, and keep it in
store when prices are falling.
According to Geman, the convenience yield could be defined also as “ a positive gain
attached to the physical commodity minus the cost of storage”.41The convenience yield
might be positive or negative, depending on the type of the commodity, the period and the
level of inventory. The different values of the convenient yield – y, compared with the
interest rate, could explain the different forms of future and forward curves. When the future
price is below the expected future spot price, the situation is called normal backwardation.
On the opposite, when the future price is above the expected spot price, we have so called
contango.( Hull, 1997) 42
Another major theory explaining the derivative trade is the Black- Scholl model for
evaluation of options and futures. The model is representing linear parabolic partial
differential equation, including the influence of the hedging ( eliminating the risk), and the
no- arbitrage option. Besides, the model includes variables like the underlying commodity
price, time and the volatility, but there is no information about the drift rate. This turns the
model into replicating an option by buying and selling the underlying asset in a complete
market, which is not the case with the financial market.Some of the assumptions of the
Black- Sholl model are also not very reliable – the underlying is following a random walk,
Hull C, John, “ Options, Futures and Other derivatives”, Third Edition, Prentice Hall International Inc., 1997,
p.67
40
Geman, Helyette, “Commodities and Commodity Derivatives : Modeling and Pricing for Agriculturals, Metals
and Energy”, John Wiley & Sons, 2005, pp.24-25
41
Geman, Helyette, “Commodities and Commodity Derivatives : Modeling and Pricing for Agriculturals, Metals
and Energy”, John Wiley & Sons, 2005, p.25
42
Hull C, John, “ Options, Futures and Other derivatives”, Third Edition, Prentice Hall International Inc., 1997,
p.69
39
16
the risk free rate for the future is unknown, the hedging is done continuously, there are no
transaction costs on the underlying, and there are no arbitrage opportunities ( Willmot,
2007)43 All those assumptions, are leading to decreasing of the reliability of the model, and
discriminates in general the derivative market, which is based on it.
7. Meaning of the investment risk on the real and financial markets
Investments done both on the real and finance market are sponsored by the banks.
However, there is a difference between the investments on the real and financial market.
On the real market, investments are aiming to develop business, deliver goods and
services on the market, which contains big risks. For exchange of their delivery, the
business receives money from their customers. We could be interpreted as: business
needs finances to produce, sell, and get more profit. On the other side, the finance sector
and banks are using the money to increase their profits, mainly through the derivative trade
interest and exchange rates, and price indices, not producing and delivering any physical
good. At the same, the interest an exchange rates traded on the derivative market, are
circulating trough loans and bank transactions on the real market, increasing the cost of the
real investments. This way , part of the increased cost of the interest and exchange rates,
used on the real market, are due to the profits from derivative trade of the financial players,
who in fact didn’t take the risk to work and deliver anything to the real market.
Another example could be, that the investments in the real economy, financed by banks,
usually require some guarantees – percentage of own financing, lands, machines, longterm contracts for production and delivery of goods, etc. providing liquidity of the loans
trough liquidity assets. For distance, the investments in derivatives, are given to
speculators without guarantees and real delivery of some commodity or asset ( disuse of
the Black - Scholl formula for options and futures). Thus, the investment in derivatives is
not providing liquidity nor to the banks, nor to the real sector, and increasing the risk for
crash in the finance and the real sectors.
On the other side on the financial market, the risk of investments in commodity or other
derivatives is also done, based on the assumption of the risk in the economy. Traders on
the financial market are analyzing different industries, the connection between them, their
development, business cycles and etc. Using this analysis, they are trying to diversify their
investment portfolio and risk in the same way, as the corporations and firms are diversifying
their business in different industries.
8.Criticism of the derivatives
In the last decades a lot of economists - scientists, politicians and business people have
criticized the derivatives on the financial market to be the cause for many of the major
financial and economic crises in the second part of the 20th and the 21st century.. Some of
the major crises are connected with basic goods and commodities like oil, real estates,
food, energy and others, traded also on the derivative markets. Since the invention of the
derivatives on the financial markets, all those crises occurred, and currently in 2012 we are
still living in one of the biggest global crises, which started in 2008 with the real estate
bubble in the USA and caused domino- effect on all other sectors of economy not only in
43
Wilmott Paul,” Introduces Quantative Finance”, John Wiley and Son, 2007, p. 144-146.
17
the USA, but in the whole world due to the globalization of the world economy. As we all
see the effects from the global crises are not concerning only the economy, but also many
political and social issues related with the high rate of unemployment all over the world, due
to the crash of the banks, companies and whole countries.
It was back in 1999 when Nasser Saber wrote his book “ Speculative Capital”, where he
explained the real nature of the derivatives and some major issues related with wrong
or contradiction assumptions in the analysis and theory of the derivatives. Saber is
stating that “ The time lag between inception of contract and delivery time in derivatives
lends itself to betting”44 He argues that the main definition of the derivative contracts is
focused on the buying and selling the underlying, not taking into account if the
buyer or the seller does not own the underlying asset, thus turning the derivative
contract into an official bet. This way the hedging function of the derivatives and the
hedgers as facilitators of the commerce is in doubt. In fact if they do not own the
underlying commodity traded, they are turning the risk- hedging function into even
higher risk of non- delivering the underlying. Another speculative feature of the
derivatives contracts is their cash- settlement side option. It is again concerning the fact
that the product on which the contract is based does not change it’s ownership as in
the real trade. In fact, only a profit or loss is exchanged based on the difference in the
buying, selling and spot price. This way the basis focus of the price to be linked to the
volume and quantity of the underlying, is rather transformed into linkage of the price to
it’s own price fluctuations. Thus in cash- settlement, the commodity price becomes more
a tool determining the winner or loser in the transaction. Besides that the cash- settlement
side of the derivatives is an incentive for increasing the volume of trading, without
any regard of the real output of the underlying commodity. For instance in the real
market the main motivation to change the price are the changes in the demand and
supply, while in derivatives, the motive is the fluctuation of the price itself. At the same
time the cash settlement method is allowing traders to gain the same or much bigger
amounts of money with less costs comparing to the real commodity market of the
underlying. Initially the cash settlement was invented for forward contracts only, when a
real delivery was supposed to take in place and the price risk would be hedged from the
price differences. In reality the Cash settlement was included in trading of all OTC
derivatives and is settled only in cash, without real delivery of commodity. This
difference brings more opportunities for speculators, than for producers. It is also
mathematically proved that it is more profitable to sell option than to exercise it,
simply because the real delivery requires more money to buy and deliver the commodity. Of
course, this brings more and more speculators to the derivative market, increasing
enormously the volume of trade, which is in times higher than the trade of the underlying
commodity on the real market. No doubt this huge volume of derivative trades reaching
billions of dollars, is also deforming a lot the balance between the amount of money
in circulation and their real coverage with goods and services provided. In addition,
the fact that the derivative price includes not only the eventual spot price, but also the
cost of carry is manipulating and boosting its size even more. The additional cost of
carry includes not only eventual inventory costs (which is meaningless in case of non –
delivery of goods), but also interest rates, insurance, as well as fixed taxes paid to
the exchange platforms. One of the most interesting parts is that all those transactions
Saber N., “ Speculative Capital- The Nature of Risk in The Capital Markets”, Financial Times Prentice Hall,
1999, p.6,7,9,10
44
18
between traders are usually settled trough credits. Afterwards, we do not need special
formulas to understand that the derivative trading is leading to overexposure of banks
and credit institutions to enormous credit risk, allowing them to finance deals for
billions dollars fed with almost 100% of risk, using coverage in non- delivering real
commodities, or unreal deals – bets. The derivative trade is also increasing the
circulation of the interest rates, including them into their costs because the credits taken
to finance the bet should be paid. We can understand than why banks were preferring to
finance and invest in those deals even if they were risky – because the huge
derivative boom of trading became such massive business for speculators, that
banks were feeling calm to finance the traders, who have been diversifying their
investment portfolios within more than 70 kinds of derivatives, which were
representing something like a mirror of the real economy with all subsector
industries and their financial relations. The derivative market was and is still increasing
in more sectors of the real economy, as well as a volume of trade. This increasing market
was appealing to the banks who were financing this risk- deals of traders, who took the
obligation to pay the interest rate through implying it in the derivative formula for price
determination. Unfortunately the derivative market can not continue growing forever,
because technically and statistically the probability for crash of the real economy
exists over time due to the business cycles, and the bets that the prices of futures
and options will always grow is not sustainable. The big problem here is also the
herding behavior and the motivation for bigger profit of the majority of the speculators, who
in some periods are concentrating on certain high- risk assets expecting higher yields. This
gambling behavior in one moment is causing saturation of the risk for huge amount
of investments, and when the moment of the real uncertainty and risk appears, than
the money invested are simply disappearing from the banking sector, because there
is no real risk coverage with underlying assets in the business with derivatives. We
all know now how this bank crash is causing further crisis in the real economy. The
question is how the banks and the government have permitted the existence of such
official gambling business to exist together with the real business, and to
overexpose their assets to such risk without any coverage and any other guarantee
from the side of the derivative speculators.
9.The Market concentration –Oligopoly, Mergers and Acquisitions.
The level of market concentration is also very important for the price settling of the
commodities. Under conditions of monopoly, and oligopoly, the probability the prices to
increase are higher, because of the lack of strong competition. Usually on the oligopoly
markets there are few big sellers, keeping the majority of the market share. The
competition on such market is usually based on the Cournot and Bertrand models,
competing either by changing quantities, or prices ( Besanko, 2007)45. Another way to
decrease costs and increase the profit margins and prices, is the vertical and horizontal
integration through mergers and acquisitions. This way the companies, involved in the
process, are gaining either decreased raw material costs ( vertical integration), or
decreased distribution costs ( horizontal integration). The increased gains from economies
45
Beasnko,” Economics of Strategy”, John Wiley and Sons, 2007,p.24
19
on scale and scope, are increasing the profitability of the companies, and increasing their
market power. The process of mergers and acquisitions is related with many market
restrictions – high cost barriers, anti- monopoly investigations and etc. Still, many of the
market integrations, become successful after the integration process, usually creating
higher market concentration, and increasing their market power in pricing of the products
(Shy, 199546)
Summary
In the outlined above theory, we have explained the major differences, similarities and
relationships between the supply- demand drivers on the real and financial markets, trying
to identify the sources of the increasing price volatility of the commodities. We could
summarize, that the interest and exchange rate and the inflation are among the most
important factors for the price volatility on both markets. The difference is that, on the real
market those factors are acting only as macro economic drivers, while for the financial
market those factors are also subject of business and trade on the derivative market and
within the bank system. The pricing of the commodities on the real market is also related
with responsible risk for production and delivery between the trading parties, while on the
derivative markets the commodity trading is only on paper. It is not related with binding
agreement for delivery, but it has character of a price betting in the future, which could be
also abandoned, when it is not profitable. The industry consolidation on the real market,
could also increase the market prices, creating global market leaders, suppressing the
industries acting like buyers. In this aspect we could say that the process of market
globalization and consolidation is affecting positively the volatility of the commodity prices.
The financial market from the other side, with the intensified global volume of derivative
trade, is causing additional price volatility on both derivative and real markets, because the
real market prices, are in many cases based on price quotes from the financial market. It
could be also said, that in terms of pricing, the major industries have blurred the distance
between the real and derivative trade, which is a big reason, to criticize both the
globalization and financialization pricesses. The basis theories and effects of the derivative
trade have also been criticized, for creating increasing risk, financial instability, asset and
economic bubbles worldwide.
Empirical Analysis - 1
Commodity prices and their relation with macroeconomic factors, derivative
markets, financialization, and globalization of the world economy.
This analysis takes into consideration big and complex dataset of macroeconomics, finances and
globalization factors, aiming to find and outline which of them are positively and negatively related
with the volatility of the commodity prices. The strengths of those connections would be difficult to
be detected, because most of the factors and variables are interconnected, due to the complexity of
the information, financial and structural flows between them. It was a big challenge to collect all this
data for the last period of 5-10 years, from different reliable information sources ( Worldbank,
OECD, UNCTAD, BIS, etc.) Yet, the data format and the many missing values for this period does
not give possibility to perform full statistical and reliable analysis, but it could be a good starting
46
Shy O.,” Industrial Organization – theory and applications”, MIT Press, p.169- 206
20
point for future investigations. Many economists worldwide are outlining that the economic problems
and situations since the beginning of the world financial crisis are detecting, that the world economy
is entering an absolutely new challenging phase, which is difficult to be analyzed precisely with all
its causes and effects. That’s why in present analysis we are only trying to identify major trends
related with the volatility of the commodity prices before and after the financial crisis from 20072008. We will not go into deep details, identifying specific strength of dependencies between those
trends, because the analysis considers very small period of time in a unique world economic
situation, which will be maybe analyzed for decades after. We will focus mainly on finding
similarities in the peaks and downturns of trends from the macroeconomics, finances and
globalization, and will try to relate them to the dynamic of commodity prices.
1. Commodity prices and macroeconomic factors
In general the prices of commodities could be affected by many factors. Usually the wars, natural
disasters, increase of the population, economic growth, and crises are affecting the price trends in
long term. Other factors like exchange rates, inflation, trade on the real and financial markets, levels
of incomes are affecting the commodity price levels mostly in short- terms.
In this first part of the Analysis of the commodity prices, a special focus is paid on the
macroeconomic factors as exchange rates, inflation, interest rates, the money supply and
GDP (incomes). The main goal is to outline the dynamic of the commodity prices, and find some
relation in the pattern of development of the macroeconomic factors and the commodity prices.
1.1.Commodity prices
On Fig.1 from the Annex we could see increase of commodity prices during the First and Second
World Wars, and the Oil Shock from the 70-ties of the last century. At the same time the prices are
dipping during the postwar or other economic depressions. In general the commodity prices have
fallen by almost 50% over the past century, but increased sharply since 2000, erasing all the
declines of the 20th century.
On Fig.2 from the Annex, we could see that the volatility of the commodity prices has increased
enormously with the beginning of the world financial crisis in 2007. The general average
monthly Commodity index for the period 2000 – 2006 was 78, while for the period 2007 – 2012 it
has increased on average by 202%, reaching an average level of 158. The biggest increase was for
the Metals Price Index – 227 % , Fuel (Energy) Index – 224 %. Smaller but still significant is the
increase also for Food and Beverage Index (166 %), and the Agricultural Raw Materials Index
(123 %). On Fig.2a we could notice that the Resource price volatility is at all-time high, with the
exception of energy in the 1970s.
On Fig.2 we could see the similar volatility pattern among the levels of the different commodity
prices, which is related partially with the production input cost- value chain. According to
McKinsey47 there is a correlated demand across resources, which causes increase of the
linkages between price levels of the different commodities ( see Fig.2b). The Agricultural raw
materials index is reflecting prices of commodities, which needs the smallest amount of energy or
other materials. The processed Food and Beverages have higher value- added cost structure than
agricultural products, but lower than the Energy Index. The Metal Index has the highest cost
structure, because the production of metals requires big quantities of Energy and other expensive
Dobbs R.,Oppenheim J.,” Resource Revolution: Meeting the world’s energy, materials, food, and water
needs”, McKinsey Global Institute, Nov, 2011.p.50-53
47
21
raw materials. There is a general suggestion that the improvement of the productivity is
reducing the volume intensity of most of these linkages, but the increasing global demand is
currently diminishing this effect. In addition the technological advancement and the
resource scarcity are boosting the substitution between different resources, which
increases even more their price interconnection and volatility. Last, but not least, the
interconnections between the global markets are increasing, which is also causing fast
correction of prices in distant parts of the world. The globalization is in fact giving bigger priority
in pricing to major world market forces, than to local ones. Commodity prices are no longer
determined only by major local producers and traders, because they are all part of the world
market.
1.2.Exchange rates
The level of the commodity prices on the physical international trade is related with the
levels of the exchange rates between the trading partners. There is a negative relationship
between the Commodity price indices presented on Fig.2 and the Exchange rates to USD,
shown on Fig.3. This means, that whenever there is a devaluation of the exchange rate of the
USD, there is an increase of the commodity prices. The opposite relationship is also detected- the
Commodity prices decrease, as the USD exchange rate is increasing. Besides that, on Fig.3 we
could notice that all major currencies, except for the Chinese Yuan are following the same pattern.
It is important to mention that the EUR, USD, GBP, BRL are traded on the financial markets,
because they are free- floating exchange rates. On the other side the Chinese Yuan have been
fixed to the USD untill 2005, and afterwards it has been fixed and managed by the Government of
China. The Chinese Yuan has increased by 20 % till 2008 compared to the USD, but the general
government policy is the currency to be under valuated. This helps the Chinese exports and China
to form big currency reserves, while at the same time, the US economy is accounting big deficits
(Herrmann)48. Besides, the capital market and currency trade in China is very limited or restricted,
prohibiting or allowing in some cases financial transactions only to authorized institutions or
enterprises, and requiring particular procedures for approval. Especially the derivative market is
very restricted both for inwards and outwards flows, and for local and residents from abroad. (ECB,
2008)49.
Another main reason for the similar trends of the major currencies to the USD, could be the fact that
the USD is a dominant currency used for international and financial trade, and is also used as base
reserve currency by the governments worldwide, as heritage from the collapsed Bretton Woods
system of the 20th century. Even though the major currencies are called “free floating”, their trend
reflects the general trend of the trade of the dominant USD currency on the global trade and
financial markets. This dominant position of the USD is in fact giving advantage to the US economy
in their exports and imports, and development of the national economy. After the Bretton Woods
system, the creation of the Euro was another international currency experiment, used for
international trade and government reserves, which gave more advantage to the European
international trade, even though now with the financial crisis, the success of the Euro is under
48
Herrmann Christoph, “Don Yuan: China’s “Selfish” Exchange Rate Policy and International Economic Law”,
European Yearbook of International Economic Law, 2010, p. 2-5
Cappiello L., Ferrucci G., “ The Sustainability of China’s Exchange rate policy and Capital Account
Liberalization”, ECB, 2008, p.37
49
22
question. Possible reason for the similar trade trends between the Euro and the USD, and their
mutual collapse with the financial crisis, might be also their tight trade relation on the financial
market through the foreign currency trade.
More about the manipulation of the currency rates and their influence on the price volatility, could
be read in the paragraph “Criticism of the regulation of the currency rates, the boosting of free
market and the globalization”50.
1.3.Inflation, money supply and GDP
The Inflation is very important financial factor for the commodity prices and their dynamic.
The increase of the inflation is usually correlated with the increase of the commodity prices.
Comparing the dynamic through the years on Fig. 2 and Fig.4, we could confirm this relationship
between both parameters – the peak of both commodity prices and inflation were during 20072008, followed by downturn during the financial crisis in late 2008 and 2009, but raised again from
2010.
As main inflationary triggers are considered the increase in the money supply, the inflation
expectations, decrease of unemployment, the increase in the economic activity, increases in
commodity prices and workers wages (Shostak)51. Mainstream economists consider that the
inflation is stimulating speculative buying, which generates waste, as well as misallocation of
financial resources, eroding at higher level the incomes of the low- income earners and pensioners.
It is also often argued that the inflation undermines the real economic growth.
According to ECB, the commodity prices react fast to changes in the money supply. The inflation
appears when commodity prices need to adjust to the equilibrium levels between short and
long- run periods, and with prices of other commodities, consumer goods, and services.52
Other economists from the Austrian Economic School as Hazlitt and Shostak, also agree about the
power of the money supply regarding the inflationary process and increase of prices. Hazlitt is
stating that any substantial increase in money supply is decreasing the purchasing power of
the money, and thus leads to increase in commodity prices. However, the Inflation is
spreading unevenly between different industries and groups of people, depending on where
came first the supply of new money.53 Shostak is arguing that “irrespective what people's
expectations are, if the money supply hasn't increased, then people's monetary expenditure
on goods cannot increase either. This means that no general strengthening in price increases
can take place without an increase in the pace of monetary pumping”.54
On Fig.5 We could see the dynamic of the money supply in the major world economic regions.
Comparing the money supply expressed by the Broad money index M3, with the inflationary trends
shown on Fig.4, we could confirm the relationship between the money supply and the
inflationary trends both in the developed and developing countries. We could see that the
OECD countries as EU, USA and Japan have lower inflation and money supply, while the
developing countries as China, India and Brazil have higher money supply and inflation. The
exception here is Australia, which is showing higher money supply and inflation than the other
50
See as file attachments
51
Shostak F., “Commodity Prices and Inflation: What's the Connection?” Mises Daily,July, 2008,
http://mises.org/daily/3018
52 Browne F., Cronin D.,” Commodity Prices, Money and Inflation”, ECB, March 2007, p.9-10
53 Hazlitt, H., “ Economics in One Lesson”, Harper and Brothers, 1946, p. 175,183-185
54 Shostak F., “Commodity Prices and Inflation: What's the Connection?” Mises Daily,July, 2008,
http://mises.org/daily/3018
23
OECD countries, but it could be explained by it’s regionally export related economy with the
developing countries in Asia.
Still, the money supply could not explain all the details in the inflationary trends and shocks as the
downturn of the inflation in 2009 ( Fig.4). For this reason we are going to examine the trends in the
GDP, which are reflecting better other triggers related with the inflation – the economic
activity and unemployment, the cost/wage- price inflationary spiral, related with the costs of
production and the incomes of the consumers.
According to Hazlitt, the inflation changes the relationship between prices and costs. He
assumes that prices increase in relation with adjusted wages, corrected with the rise in the
consumer products prices, and other production costs raised. The companies still want to sustain
their profits, so this reflects in their increased (inflated) prices. What companies often do, is to
reduce or not increase the labour wages, thus reducing the purchasing power in economy with
rising prices.55 In addition, Shostak considers, that the inflation expectations are the key driving
factor behind increases in general prices – from one side people are expecting higher prices and
increase their demand for goods, bidding for higher prices. On the other hand, the anticipations of
the workers for higher prices, makes them demand higher wages, which moves up the costs of
production and prices of final products and services, further passed to the consumers on the
market.56
On Fig. 6 we could see that the trend in the GDP per Capita per different economic regions of
the world, are coherent with the trends of the commodity prices and the inflation ( Fig.2 and
Fig.4). We could suggest that the dynamic of the commodity prices and inflation depends mainly on
the dynamic of the economy. Still, following the cost- price inflationary spiral theory, we could also
suggest that the reason for the downturn in the world economy could be an effect from the
increased incomes and prices during 2005 – 2007, and the world economy needed some
adjustment at lower levels in 2008- 2009. In addition to this suggestion, on Fig.6 we could notice
that the developing countries are having GDP Annual growth 2 to 5 times bigger than the
developed countries, which might suggest increasing wages and costs, followed by higher
price levels of the final products, big quantities of which are delivered to the markets of the
developed countries.
On Fig. 7 we could also notice that the incomes in the developing countries are rising faster
and on a greater scale than any previous point in the history. According to McKinsey57, UK has
doubled its GDP per capita from 1300$ to 2600$ in PPP terms, for 154 years with population less
than 10 millions, from the beginning of 17th century till the middle of the 18th century. USA has
doubled the same income for only 53 years in the 18th century with approximately the same quantity
of population (10 mln). Similar are the results for Germany, Japan and South Korea until year 2000
– shorter periods of doubling the GDP with less population needed proportionally to the GDP.
Today India and China with combined population of more than 2.5 billion, are doubling their GDP
every 12 or 16 years. This fact is leading for sure to faster tightening of the cost/wage – price
inflationary spiral and volatility of prices in global aspect, when we consider the world as
one global economy, where the production is mainly concentrated in the developing
countries, and the consumption markets – in the developed countries. In this aspect, the lower
economic development of the OECD countries in combination with the financial crisis, is a very
Hazlitt, H., “ Economics in One Lesson”, Harper and Brothers, 1946, p.183-185
Shostak F., “Commodity Prices and Inflation: What's the Connection?” Mises Daily,July, 2008,
http://mises.org/daily/3018
57
Dobbs R., Oppenheim J.,” Resource Revolution: Meeting the world’s energy, materials, food, and water
needs”, McKinsey Global Institute, Nov, 2011.p.34
55
56
24
important factor for the global economy, where the production of the developing countries with
rising incomes and costs, could not rely for very long time of increasing of the market in the OECD
countries.
1.4. Interest rate
The importance of the interest rates is a very complex subject, reflecting the dynamic of the
commodity prices, and in general - both the financial markets and real economy. There are many
mechanisms of the interest rates influence.
1.4.1. Connection between Interest rates and commodity prices, cost structure of prices,
inflation and business activity
If we compare Fig.2 showing the trend of the commodity prices and Figures 8 and 9, detecting the
interbank interest rates, we could see that the dynamic of both commodity prices and interest rates
have similar pattern of development until 2009 : increase until 2007 – 2008, and drop in 2008-2009.
On the other hand, in the development of the commodity prices and interest rates after year 2009,
we notice decrease or very slight increase in most of the interest rates in OECD ( but not in the
developing for Brazil, China and Australia), while the commodity prices are raising.
Possible reason for the decreasing the commodity prices during the crisis in the end of
2008 and beginning of 2009, is the real decrease in the demand and inventory levels due to
the financial crisis, which caused stagnation of the consumption and business activities.
The crisis was also a reason for the banks, to decrease their interest rates in order to
stimulate the business, and its own activities even at a lower turnover.
It is also a well known, that the production and trade, are financed and settled by bank loans,
requiring payment of interest rates, which are further calculated in the final price of the
commodities. On the other side, the levels of the interest rates affect the financial, business
investors and consumers through different credits and credit products, and interest rates
provided for savings and investments. If we compare the trends of the figures showing the
Inflation ( Fig.4) and the Annual growth of the GDP ( Fig.6), with Fig 8., showing the Interbank
interest rates both for Developing and OECD countries, we could see that the trend patterns are
similar. The increasing trend duration is until 2007, followed by drop in 2008 – 2009, and further
upraising in 2010 and 2011. This coherence in the trends is showing the direct connection
between the levels of interest rates, price levels expressed by the inflation, and the GDP
growth representing the trends of development in the real economy.
1.4.2. Interest rates and Financial Markets
The interest rate dynamic is influencing directly also on the speculators on the financial markets,
leading the investment behaviour and decisions to diversify their investments portfolios. In general
lower bank interest rates could intensify financial, investment deals and purchases, while
higher interest rates would stagnate them. The same rule applies when some investors want to
switch from one type of risk investment to another – the decision depends on the level of risk in
each security.
In terms of commodity trade and prices, we could notice that the prospects for lower levels of
interest rates, have intensified the activity on the derivative markets, thus increasing directly
or indirectly the price levels of commodities. This happens through the cost structure of the
commodities, including financial expenses such as exchange rates, interest rates, credit
down payments, interest rates and dividends, all traded with increased volatility on the
25
derivative markets after the start of the financial crisis. ( Fig.11 and Fig. 12). The total
derivative trade, measured by the amounts outstanding has increased tremendously by more than
300% from 2006 to 2011 - from app.8000 Bill. USD to more than 25 000 Bill. USD. There is a huge
increase of the trade and the outstanding amounts of all derivative contracts comparing to year
2006, especially in interest rate contracts ( 413 % steady increase from 2006 to 2011), commodities
(increasing by 300 % in 2007 compared to 2006, but again decreasing 33% below levels of 2006 in
2011), credit default swaps ( steady increase of 330 % from year 2006 to 2011), and etc.
Comparing the trends on Figures 11 and 12 with those on Figures 8 and 9, we could confirm the
opposite trends between the dynamic of the interest rates and the dynamic on the financial
market. The trend of the interbank interest rates in the OECD ( Fig. 8, 9) as well as developing
countries , were in peak during year 2006. Later at the time of the financial crisis between 2007 and
2009, interest rates dropped by more than 3.15 % for the Euro Area, and 5.12 % for the US. The
interest rates in other countries from Asia and Latin America dropped less than those in EU and US,
but also showed more or less declining trend until 2009. Later in the period 2010- 2011, when the
main interest rates in OECD and developing countries, are staying almost unchanged or increasing
very slightly, the derivative markets are developing rapidly.
Recently another interesting phenomena was also detected by the main European and US financial
regulators – the interbank interest rate LIBOR ( Fig.10) have been proved to be manipulated
by main European and US banks between 2005 and 2009. Similar investigation is under way
also about the interbank interest rate EURIBOR. 58 Officials of the EU Regulator stated that the
manipulation of financial indices such as LIBOR should be assumed by law as a crime,
because it is a basis for lending money and derivative contracts around the world.59
According to BIS, the manipulation of LIBOR also undermines the trust in the world financial
system, because hundreds of trillions euro operations all around the world are based on LIBOR,
including buying of homes and mortgages.60 This fact could also explain the huge increase of the
derivative trade with interest rate contracts since 2007 (Fig.12), because the manipulation of LIBOR
could have given more confidence to banks and their financial representatives on their positions on
the derivative market. As already explained, the increased derivative trade produces volatility
also in commodity prices, through the cost structure of the prices, including financial expenses as
interest rates, exchange rates, dividends and etc., usually traded on the derivative markets.
2.
Commodities and Derivative markets in the context of the Financialization of
the world economy
In the second part of this analysis, we would like to find out, if there is a relation between the
volatility of commodity prices, and the dynamic in the trade of commodities and other derivative
contracts on the financial markets. On the other side we will focus on the impact of the financial
markets over the macroeconomic development of the world economy, often referred as
financialization of the global economy
58
http://www.businessweek.com/news/2012-07-16/libor-collusion-cant-be-excused-by-bank-crisis-almunia
59
http://www.telegraph.co.uk/finance/newsbysector/banksandfinance/9386132/EU-regulator-Barnier-wantsto-make-Libor-abuse-a-crime.html
60 http://www.bis.org/review/r120723a.pdf?frames=0
26
2.1. Commodity trade and Derivative markets
As already explained together with the analysis of the interest rate, and it’s influence over the
commodity prices in the previous chapter, the derivative markets have developed enormously
since 2007. On Figures 11 and 12, we could notice the outstanding gross market values of the
main derivative contracts on the OTC ( Over- The - Counter, non- regulated) markets. The data
represents the contracts which are not closed and are containing big financial risk for the
market players, and the liquidity of the financial markets in general. Usually they are
proportional to the volume of trade on the OTC markets. The OTC Markets are even more
important for the Financial market than the Organized Market, because they contain much more
liquidity risk for the financial system, representing about 90 % of all Outstanding derivative
contracts ( Fig.13). On Fig.13 we could also see that the risk on the financial markets in
general has increased by 98% from 2005 to 2011. At the same time the share of the risk
exposure of the OTC markets have increased by 8 %, while on the organized markets it has
decreased by 8 % for the same period.
We have already explained the impact of the increasing volume and outstanding derivative
contracts on the OTC market, over the commodity prices in the previous chapter. We have
noticed that the majority of the derivative contracts traded there are interest rates, equities, credit
defaults swaps, exchange rates, included directly or indirectly in the cost structure of the commodity
prices.
The derivative trade expressed by the outstanding amounts of commodity contracts on the
OTC markets increased by 300 % in 2007, compared to 2006, but decreased by 33% below
2006 - levels in 2011 (Fig.12). While the increase and decrease trends of the outstanding
commodity contracts on the OTC market are not quite similar to the dynamic of the commodity
prices shown on Fig.2, the trends of the outstanding commodity contracts on the organized financial
markets have bigger similarity (Fig.14). The outstanding commodity contracts on the organized
financial markets in 2007 have increased by more than 560 % comparing to 2005. In 2008 we
could detect sudden drop during the crisis, the same way as the commodity prices. In the
period 2009 – 2011 both the commodity prices are increasing, as well as the outstanding
commodity contracts on the organized financial market ( still 53 % less than year 2007, but 305 %
more compared to year 2005 (see Fig.14). We suggest that the number of the outstanding
contracts and amounts ( Fig. 14 and 16), are proportional to the volume of trade of
commodities on the financial markets ( Fig.15 and 17), but represent better the market risk
and price expectations, because the trend of the outstanding contracts and amounts have
similar pattern as the commodity prices ( See Fig.2 ). As mentioned before, the increased
volume of trade and outstanding amounts of commodity contracts, are related with the
expectations of the financial players about the prices on the physical markets. But since, the
main commodities in each industry are priced through financial indices, subject many times
to manipulations through information agencies or banks, we could understand how the real
commodity prices are in fact manipulated by the financial markets. (See LIBOR manipulation
from the previous paragraph 1.4.3.).
In addition to the information about manipulation of LIBOR and eventually of EURIBOR, where
major US and European banks were accused, we could say that about 75 % of the outstanding
amounts in commodities, and approximately around 60 % of the yearly turnover of commodity
futures and options contracts were made also on the US financial markets. (Fig.14, 15). US is also
leading in the derivative trade in all kinds of futures and options trading ( Fig.16 and 17),
representing 55-60 % of the world’s outstanding amounts and 50-55 % of the global yearly turnover.
27
Europe is representing around 34-37 % of the world financial market, Asia and Pacific- nearly
6-7 %.
On Fig.18 and 19 we could see the increasing importance of the derivative trade, including of
commodities, and especially on all major London- based market exchanges. NYSE Life and
ICE Futures Europe had increased the volume of derivative trade approximately by 890 % for
the period 2000- 2006. For the period 2006- 2010 the three biggest derivative exchange
markets in London ( NYSE Life, ICE and LME) have increased their trade approximately by
another 180 %. ( Fig.18 ) The total derivative trade of all kinds of contracts in the pre- crisis time in
2006 had increased by 700%, compared to year 2000. For the period 2006- 2010 the total
derivative trade in million contracts have increased by another 171 %. In similar pattern, the
commodity derivative trade between 2000 and 2006 had increased by 367 %, while in the
period 2006- 2010 the increase was 187% ( Fig.19). If we compare the trend of the derivative
trade (incl. commodities) shown on Fig.19, with the trend of the average commodity price
index shown on Fig.2, we could see the similarities in the trends. Both trends have increasing
pattern for the whole period between 2000 and 2010, with some decrease in the trend around year
2007. In both cases we have approximately the same percentage of increase during the period after
2007. The general average monthly Commodity index (Fig.2) for the period 2007 – 2012 has
increased on average by 202%, while the increase of the commodity derivative trade in
London- based financial markets was 187 %. From this data, we could confirm correlation
between the increase of commodity prices and the frequency of their trade on the derivative
markets. We could suggest that this is one major pattern in the total financialization of the
world economy.
2.2. Financialization of the World Economy
As already outlined in the previous paragraph, the dynamic on the derivative markets is related
with the global increase of commodity prices. Another dimension of the financialization of
the global economy we could find, if we compare the Annual Growth of GDP per Capita by World
Regions ( Fig.6 ), and the Annual Change in the Standard and Poor Global Equity Indices by major
world regions ( Fig.20). An observer could notice that the peak and bottom patterns for S&P
equity indices for both Developed and Developing countries, are preceding the peak and
bottom trends of the GDP per capita growth with one year. As we know, the equity indices are
derived from the development of the real economy and the prospects for major equity- listed
corporations. From both figures we could see, that the financial prospects for development, are in
fact preceding the real development of the economy with one year. In such situation, the investment
initiatives of the major corporations aiming to gather capital through equities on the financial market,
are depending directly on the analysis of the financial market specialists. This way the investments
are channeled in regions and business areas that are considered as profitable only by the
financial analysts, and decreasing the chance for development of whole national economies,
industries or companies which might be underestimated, or are just outside of the usual
investment risk portfolio of the financial traders.
When we are interested to know how and why was developed the financialization of the world
economy, and how it is spread among different regions, we could be interested in terms such like
Financial depth ( Fig.22), Value of stocks traded by countries as % from the GDP ( Fig.21), and
Share of the World Insurance and Financial services from the world commercial export and import (
Fig.22a, 22b, 22c). On Fig.21 an observer could detect the huge volume of stock trading as % of
the GDP of major global regions and countries. For the period 2005- 2010 US have traded
28
with stocks on the financial market in value on average 286 % from their GDP. There was an
enormous increase in the value of stock trading ( 447 % from the GDP of US) in year 2007 –
just before the beginning of the big world financial crisis, which started from US. Other big
traders with stocks are China, East Asia and Pacific area, Australia and the Euro Area, with
average value of stock trade as percentage from their national GDP, respectively 124%, 125%,
107% and 78%. It is interesting to notice that the peak of the stock trade for all those areas was in
2007 and 2008 – before or in the beginning of the financial crisis. This is not a coincidence, but a
very high financial risk for any country with developed stock market. The fact that the money
circulating in one national or regional economy, are in sharp imbalance between the real
economy ( represented by the GDP ) and the financial market, and at the same time huge
priority is given on the financial deals, which are derived from the functioning of the real
economy, is a very risky situation. This could mean that if for some reason the real economy
experience difficulties, the financial system will suffer in times more, depending on the
correlation with the problem sector of the real economy.
Both on Figures 21 and 22, we could notice that the development of the financial market is stronger
in the OECD countries, while other emerging and developing countries are catching up the trend of
the developed countries faster. According to McKinsey61, the financial stock in the emerging
economies is growing faster than that of the developed countries, increasing by 13.5 %,
compared with 3.9 % growth in the developed countries. This trend for developing countries
have last since year 2000, and at the end of 2010, the emerging markets account for 18 % of the
world financial stock market, with prospects to become an important global player. Financial
markets in developing countries are smaller, but have all fundamental drivers for financial growthincreasing of the population, high saving rates appropriate for investments, need for capital
investments such as infrastructure, housing, commercial real estates, factories and machinery.
There is more room for development of the financial trade on the emerging markets, because
they have lower financial depth, expressed mainly by absence of corporate bond and
securitization markets ( Fig.22).
The process of financialization of the world economy is very well depictured also on Figures 22a,
22b and 22c. We could see that the trade with insurances and financial services, as part of the
global trade with commercial services, was steadily increasing in the period 2005 -2010
Minor decrease of exports of around 1% is detected since the financial crisis from 2008, but
despite that, there was continuous increase of the imports by 2%. For the considered period of 5
years, the overall increase of the insurance and financial services, as part of the world trade
with commercial services, was around 1- 1.5%, despite of the world financial crisis.
According to data sourced from the Worldbank62, the levels of the imports of insurance and
financial services, as part of the trade with commercial services, both in OECD and
developing countries have reached levels between 7- 10 %, with exclusive share of 11-12%
in the developing countries from Latin America. For the period 2005 – 2010 these imports in
OECD and the developing countries from East Asia and Pacific have increased on average about
1-2 %, while in the rest of the developing countries have decreased by about 0.3%. It is interesting
to mention that for the same period US have increased their imports of financial services by
7.7 % ( see Fig.22b), while all other major countries kept their levels almost unchanged
during the financial crisis.
The exports of insurance and financial services have increased for the same period in all
world regions on average between 0.2 and 2 %. Strong was the presence of the OECD and
61
62
“ Mapping global capital markets 2011”, McKinsey Global Institute, p.4
Worldbank databank
29
Latin American developing countries, with shares of the financial services around 8 % from
the trade with commercial services. Solely US have increased their financial services
exports by 4.7 %, and Brazil by 4 % ( see Fig. 22c). The exports of financial services and
insurances from the developing countries from East Asia and Pacific and Europe and Central Asia
accounted between 1 and 3% from their trade with commercial services.
When we are talking about the relationship between the financial markets and real economy and
their drivers, we have also noticed that this link could be expressed by the GDP, growth of the
population, growth of the savings, the need for new infrastructure projects and etc. Another
interesting aspect of the connection between the real economy and the financial market is
the level of the government debt, which is also traded on the financial markets in form of
different securities. The increase of the national debts, is related also with the increasing financial
depth, especially in the developed countries. (see Fig. 22 and 23). According to McKinsey 63 the
Global public debt has increased by 24.6 trillion USD between 2000 and 2010, reaching 69% of the
GDP in 2010. This increase represents 23% higher global debt in 2010 compared to 2000. General
reason for this long- term tendency in many advanced economies is the ageing of the
population, which increases the cost of the healthcare and pension funds in the national
budgets. The national budgets need to be restructured in order to change this trend of increasing
the national debts. On Fig. 23 we could see that the situation with the public debt in the emerging
economies is smaller – their debt is between 30 and 50 % of their GDP. At the same time, the
public debt in the developed countries is between 50 and 220 % from the national GDP. Those
huge debts could be restructured through spending cuts and higher taxes, but if the population in
the main developed countries, and already in some emerging markets is ageing and decreasing its
growth ( see in next paragraph 3), even those hard measures would not be efficient enough.
Another expression of the problem with the ageing and the decreasing growth of the
population, is the decreasing of the working force (Fig.31), which lowers the chances of the
developed countries and some of the emerging markets, to be competitive in the world economy.
The global trends of increasing the GDP and decreasing of the working force means higher
costs for wages, and at the same time decreasing number of consumers, even though their
incomes might become higher with the time. This process is leading also to higher prices
posed by the corporations, which would compensate themselves for the shrinking global
market. And again, the pressure from the higher prices would affect the public spending and the
cost of life, which would make much more difficult to compensate the increasing public debt trough
cuts and higher taxes. From this point of view, the trade with the public debt on the financial
market, is just a temporary solution of a much bigger problem in the real economy, related
with social issues and restructuring of the economy. The increasing of the trade on the
financial market with government debts and securities is in a way expression of those
national social and economic problems, but from another side, if the trade with national
debts on financial markets becomes in times bigger than the volume of the real economy (as
we see this from fig.22), this creates another fiscal risk on global level for collapse not only
of the national economies, whose debt is traded, but also for the countries, where those
debts are traded. In fact this is an expression of the total globalization and financialization of
the world economy, where all the factors of the macro and micro economy are traded on the
financial market as in a casino, and the real economy has become just a commodity on
which some financial analysts would bet. Unfortunately this casino- mania called financial
market has infected the global economy, and currently we see how difficult it is to get rid of it,
because most of the money flows are depending on it, even in the real economy. And today a crash
63
“ Mapping global capital markets 2011”, McKinsey Global Institute, p.21
30
on the financial markets means automatically crash of the fiscal system, which further reflects on
the real economy. We see how this mania about the financial markets have shifted the drivers in the
economy – in the beginning the real economy was a driver for the financial market, while now the
financial markets have become a driver, but also a big threat to the global real economy on
macroeconomic level.
3.Commodities Supply and Demand Analysis in the context of Globalization of the
World economy
As mentioned in the beginning of the analysis, the increased volatility of commodity prices is very
affected by the development of the global markets, increase of the demand with the growth of the
world population, and the technological advancements, which are causing substitution among
different commodity types. We are facing a new era of economic, technological and social
development, which increases the probability for even higher volatility of commodity prices, despite
the chances to create more sustainable way to use resources through new technologies and create
new materials. There are many challenges to create sustainable supply to the increasing
demand for resources, energy and materials, which are related with change in the paradigm
of the supply- demand model.
3.1. The Old, and the challenges of the New Model for Supply and Demand of Commodities
During the 20th century the global growth was based on intensive use of resources, but the
prices of resources and commodities were not so volatile. The governments kept low the
prices of the general resources like energy and water through subsidies, thus encouraging their
inefficient use (McKinsey)64. At the same time corporations benefited from the declining resource
prices, increasing their efficiency, and focusing mostly on the capital and labor productivity, to
sustain lower prices. It is interesting to notice that even though during the 20th century the
world population increased 4 times, the global economic output multiplied more than 20
times, and the demand for different resources jumped between 600 and 2000 percent, the
commodity prices declined or stayed flat. (see Fig.2a). General role for that played the faster
technological progress and the discovery of new low- cost sources of supply, or the
mispricing due to the government subsidized resource prices like energy and water.
According to McKinsey, the demand for resources in the last 100 years grew more slowly than the
GDP. As reason for this fact, they consider that after reaching a threshold of GDP per capita in PPP
of 15 – 20 000 $, the income is spent less on resource- intensive consumption, and in the last
century the global GDP was formed in richer countries which have income above this threshold. As
another reason for the slower increase of demand than the GDP, is outlined the improved end- use
productivity of resources due to implied technological innovations, as well as government subsidies
to industries.
In the last decades, the volatility of commodity prices has increased, and a new challenging
model to deal with the global supply and demand of the major resources and materials is on
it’s way of development. The major factors that would affect the future volatility of
commodity prices depends of several factors according to McKinsey 65:
Dobbs R.,Oppenheim J.,” Resource Revolution: Meeting the world’s energy, materials, food, and water
needs”, McKinsey Global Institute, Nov, 2011.p.4, 21-30
65
Dobbs R.,Oppenheim J.,” Resource Revolution: Meeting the world’s energy, materials, food, and water
needs”, McKinsey Global Institute, Nov, 2011.p.5, 10-15, 29, 118-120
64
31
1. Global demand for resources will be fueled enormously in the next 20 years, expecting emerging
of up to 3 Billion more middle- class consumers (especially in India and China), and additional
billion consumers from developing countries, who lack basic needs as energy, food and water.
2. Difficulties related with requirements for new investments in order to expand the global supply.
Additional logistic and political problems might be an issue.
3. Interlink between the global resources on the global markets, which leads to fast spreading of
price shocks from one resource and market into another.
4. Shrinking of the supply due to additional environmental restrictions
In regard of the above mentioned challenges in dealing with the global demand and supply, many
steps could be initiated:
- On a global level new regulation mechanisms and institutions for coordination of the
interconnected resources is needed. Additional efforts are necessary in order to shift from highcarbon to low- carbon and renewable energy resources, and increase the energy sustainability
in the transport, agriculture and manufacturing with regard with the carbon emissions.
Governments need to create in their institutions integrated approach towards resources, and
this way to increase the public awareness and the resource productivity. Governments and
institutions also need to strengthen the market- price signals through effective policy regimes,
which would impose higher taxes for carbon emissions, and motivate the business to use
renewable energy and new less carbon emitting technologies. There is a need to decrease the
administrative bureaucracy and clarify and optimize some legislation regarding the new
regimes and policies. Another new efficient global intelligence early- warning system related
with national and global demand and supply of different resources is needed, in order to
access potential risks related with climate change, economic growth and etc.
- Corporations need to adopt new joined- approached methods towards their needs of
different resources, so that they could produce growth without new disruptive innovations. In this
process they should avoid creating of new risks for supply of resources, competitive asymmetries,
or changing the regulative context. Firms strategies should consider their strategies according to
the resource- related risks and opportunities, and focus not only on the increased productivity of
labor and capitals, but also on resource productivity.
- Meeting the increased global demand in the future will require around 3 trillion $ to meet all
the capital, infrastructure and geopolitical challenges. This demand could be partially
absorbed through different opportunities to boost the productivity of the resource
extraction, conversion, and end- use. According to McKinsey such productivity measures with
resources like land, energy, water and materials could cover between 13 and 29 percent from the
global supply in 2030 (See Fig.24). At the same time between 75 and 80 % of the productivity
potential is in the developing countries ( See Fig.25). Unfortunately, the productivity model to
increase the supply is more costly than the capital costs of the pure expansion supply
model, due to the fragment application of the productivity model. The pure investment model for
expansion of the resource supply is suggested to decrease the volatility in a long- run, creating
more jobs, increasing the economic growth and encouraging new innovative investments. Still,
there is a need to reduce the use of imported resources through increased resource productivity, in
order to increase the competitiveness of the business.
According to McKinsey, within the next 20 years, globally it is unlikely to be an absolute
shortage in resources, but the main problem is that the demand in a short- run is moving
much faster than the limits of the supply, which has become inelastic, thus driving to greater
price volatility. In addition the increasing of the correlations between the price volatility of
different resources, will have shocking spillover effect over other use and market related
32
resources. From macroeconomic and political point of view, the increased price volatility could
slow the economic growth and the welfare of the citizens, block the public finances and
create geopolitical problems. From microeconomic point of view, the rising commodity prices
would increase of the production costs, which will create higher prices and inflation, and
this way reducing the households consumption and slowdown the economic growth.
Volatility of prices could also affect the investment decisions of the business, creating
higher uncertainty, discourage and delay the investments due to increasing the costs of
hedging, against the risks related with resource supply.
3.2. Analysis of the Supply and Demand factors, affecting the dynamic of the Commodity
prices.
Since we want to analyze the potential increase or decrease of commodity prices, we would
generate a global approach towards the world economy, considering the dynamic of the major
regions in the world, the OECD and developing countries. We will evaluate their demand and
supply potential as market size, number of potential consumers (population, ageing, employment),
GDP per capita and by economic sectors, possibility for future economic growth, urbanization,
industrialization, trends in the globalization ( Exports and Imports, Cross- border Investments,
Mergers and Acquisitions), labor division and production costs and etc.
3.2.1. Population
When we want to estimate the general market demand potential, we want to understand if there is
an increase or decrease of the population, where and by how much. When we take a look at the
data shown of Figures 26, 27 and 28, we see that the total world population has increased by
6 % only for the period between 2005 and 2010, and by total of 30 % for the period between
1990 and 2010. This might be striking news for increase of the global demand, as McKinsey have
suggested in their analysis, but at the same time, if we look at the Annual growth rate of the
world population and by regions, we could understand that there is also a general trend of
slowing down, or decreasing of both the global population and the global markets. This
slowing-down trend might not effect suddenly in the next 20 years, but could exersise its
tightening effect on the global market, together with the process of ageing of the population
( See Fig. 33 and 34). On fig.26, 27 and 28 we see the world annual growth rate of the population
for the period 1990 -2010. The developing countries are representing about 76- 80 % of the world
population, while the developed and transition countries represent the rest of the world population
( 4-5 % for transition, and 15-16% for the developed countries). For the same period of 20 years,
the transition economies have decreased their share in the world population by -1,56%, as well as
the developed counties decreased theirs by -2.23 %. The increase in the population ( and the
market demand) in the last 20 years is coming progressively from the developing world, which has
increased its population by 3.79 % ( See fig.27). More detailed trend in the population growth for the
years 2005 -2010, we could see on fig.28, where we could notice the slow- down of the world
population growth in the last years from 1,20 % to 1,15 %. Similar are the regional trends all around
the world- both for the OECD and developing countries
( with exception for developing countries
in Europe and Central Asia). The decrease of the annual growth of the population in the OECD
countries for the considered period is - 0.09%, and the decreases for the developing countries in
East Asia and Pacific, Latin America and Caribbean and Middle East and North Africa, are
accordingly - 0.1 %, -0.13%, and - 0.07 %.
33
If we compare the trends in the population growth of the developing countries for the last 20,
and for the last 7-10 years, we could notice, that in the past since 1990, the developing
countries were increasing their population, and were major driver for the world economy
growth. Since the first decade of the 21st century, the trend has changed, and the developing
countries started slowly decreasing their population growth, which already have, and will
further affect the tightening world demand in mid – and long- term. At the same time the
developed countries are also decreasing their market attractiveness, increasing their
population very slightly in absolute terms, and continuing decreasing as share from the
world population. The transition economies are showing unstable market demand trends
with continuously decreasing population since 1990, and slight improvements since 2005.
3.2.2. Labor force and incomes
If we want to explore in details the potential of the global markets, we would be interested also in
the trend of development of the working force, which is the main driver of the economic growth.
Besides that, the number of the working force will give the economic potential of the markets,
showing both the potential economic demand, and potential labor costs, when we consider also the
GDP per capita and incomes. On figures 29 and 30 we could estimate the economic potential of the
demand by world economic regions. The adjusted Annual income growth (Fig.29), is reflecting
better the real income dynamic, since it has deducted the income taxes, the exchange rate and
price fluctuations of the commodities, usually included in the PPP. As we have already mentioned
before, during the period 2005- 2010 the incomes in the developing countries were increasing
in times faster (5-10 % annual growth) , than those in the developed countries ( 2-4% annual
growth). Even during the financial crisis in 2008- 2009, when the income growth in OECD countries
changed to negative, most of the developing countries kept relatively high levels of positive growth
between 2,5 and 15 %. Still, on Fig.30 we see that the GDP per capita in PPP terms referred to
2005 prices, are showing that the developed countries are about 2 times richer than the
developing countries, with stable GDP around 3000 USD. But if we want to compare those
incomes with the population data, and try to estimate their effect on the global demand, we
could conclude that the developing countries combined, are bringing larger global effect on
the increasing demand, than the OECD countries. This way we could understand also the global
inequality between the outnumbered population of the developing countries, and the outperforming
incomes of the OECD countries. This fact from the cost perspective of prices, is still giving
opportunities for the developed countries to outsource their production and services, in
order to reach better profits. Yet, keeping in mind the trends of the decreasing and ageing
population and the working force from one side (see next paragraph), and the fast increasing
incomes of the developing countries from the other, those opportunities would decrease in
mid- and long-term, tightening the production costs, and possibly increase the global prices
further.
On Figures 31, 32 and 33 we could follow up the trends in the world and regional labor force. On
Fig.31 we could see amazing reduce of the world and regional working force in the period
2000- 2010. For the first five years from the 21st century, the global working force has
reduced by app. 9- 10%, and between 2005- 2010 the decrease was only 0.72%. Regionally,
the biggest decrease is detected in the second period in the developing countries ( minus 3-4 %),
and by 5 % for the developed countries between 2000 and 2005. Transition economies had
negative growth of the working force in 2000, but progressed till 4 % in 2010. On Fig.32 we could
see that USA has biggest problem with the employment which has decreased by 4.3 % between
2005 and 2010, while China has decreased its employment to population ratio for the same period
34
by 1.1%. The data for Australia, Brazil and EU are more or less stable. When we consider figures
33 and 34 however, another situation is revealed - ageing of the global population and the
working force. For the period 2005- 2010, there is a global trend of increasing the old age
dependency ratio ( from 11.29% to 11.58%), and at the same time decreasing of the young
dependency ratio of the working force ( from 43,82% to 40,92%). From Fig. 33 we could see that
the situation with the ageing of the population referred to working force is worst in the OECD
countries, while in the majority of the regions with developing countries, the situation is the
opposite. Other reserves of the labor force are revealed on Figures 35 and 36, where the
dynamic of the urban and rural labor force between 1990 and 2010 is exposed. The situation
with the OECD labor force is worst, because there are no reserves for increasing of the labor
force through transition from rural to urban, because 100% of the working force is already
urban since year 2000. Transition economies have decreased rural working force reserve
gradually from 19% to 12 % since 1990. The developing countries have also reduced their rural
labor force by app.10% for the same period, but still have about 50% reserve of working force in
the rural areas, which could transit into urban, in case of further industrialization and
economic development through urbanization.
In a summary, we could say that the global working force is in general decreasing, ageing
and losing reserves for transfer from rural to urban, in case of a need. Those trends could
tighten the global demand for commodities, because the labor force represents the main
consumer group of the population. From supplier’s point of view, the decreasing of the labor
force and its ageing would bring requirements for higher wages and compensations, which
will increase the prices and their volatility in mid and long- term. Last, but not least, the
ageing of the population could bring additional limitations of the public finances and the
government balances, increasing the pension funds, which will require higher taxes in one
form or another, which will again reflect the economic growth and the commodity prices.
3.2.3. Growth drivers – Urbanization and Industrialization
As already mentioned in the previous paragraphs, the developing countries are keeping to
be the main driver of the world economic growth, representing about 80 % of the world
population, only 45 % from which is urban, and having the lowest level of urbanization of the
labor force of about 50% ( Fig. 35, 36, 37). At the same time the developed countries seem to
have reached the top of their growth, representing only 15-16 % of the world population, which is
not showing trends of big increase, but more of ageing and decreasing. Besides, the average
urbanization of the population in the OECD countries have reached 77%, and the urban labor force
is 100 %. There is a very small room for world economic growth coming from the transition
economies, which represent about 4-5 % from the world population, showing trends of decrease. At
the same time they have high levels of urbanization – stable about 63% from the population in the
last decades, and their labor force have reached nearly the top of their urbanization- of about 88%.
On figures 38, 39, 40 and 41, we could follow the global industrialization process among the
developing, developed and transition economies, and summarize the potential of the
different regional markets for growth of demand.66 As we could see from Fig. 38, only 1-2 % the
total value- added in the GDP of the developed countries is coming from agriculture. The
industrialization trend in the developed countries has also shrunk by app.5% in the last two
decades, reaching 15 % of their GDP ( Fig.40), and at the same time they have the lowest
66
The data shown on fig.39 and fig.40, are representing the difference between the trends in the
development of the manufacturing (fig.40), and the resource availability for industrialization, including
industries like mining and extraction of different materials and resources used in the manufacturing process.
35
development of other resource providing industries, representing only 10 % of the value- added of
their GDP ( Fig.39). If we combine this information with data given by figures 41 and 22,
representing the share of the services and the financial depth of the national economies, we could
see that the OECD countries have the top- development and increasing of the services by app.10
%, up to 74 % from their GDP in the last two decades ( Fig.41). At the same time they have the
highest financial depth in the world ( see Fig.22 and the analysis from paragraph 2 ). Since, the
real economy and industrialization are the main drivers of the services and the financial
markets, we could consider that the developed countries, whose real economy (agriculture,
industry and manufacturing) is representing only about 25- 30% of their GDP added- value,
should be seriously disturbed about the development of their economic growth, based
predominantly on financial and other services. This means that the industrialization process
in the developed countries have been transformed into financialization process, and
development of service- oriented economies. Outlined this way, the structure of the
developed economies would lead to stagnation of their regional markets and risk of financial
crash, followed further by downturn and restructuring of the real economy. Since the crash
of the financial system is already bringing huge problems for the real economies in EU and
US, we could suggest that the volatility of the prices would increase even stronger with
eventual problems with the Euro and the Eurozone.
The developing countries have the most balanced economy compared with the developed
and transition economies, even though the share of the services is also quite high,
representing 47-50 % of the value- added of their GDP, it is still the lowest among others
( see Fig. 41). The process of financialiazation of their economy is not so strong yet - the financial
depth in the developing countries67 is about 150- 200 % of their GDP, while in the developed
countries this share is moving between 400 and 450 % ( see Fig.22). The developing countries
are also better provided with resources for developing of their manufacturing – the share of
the agriculture is stable about 10%, and the industries related with extracting of resources
are giving about 15 % of the value – added of their GDP (see Fig.38,39). The share of the
manufacturing, representing the process of the industrialization is about 22- 24%, which is
about 8- 10 % more than the levels in the developed and transition economies. ( see Fig.40).
All those facts are giving us reason to consider the developing countries as the most
industrialized countries in the world, especially China, where the manufacturing is
representing 38 % of the value- added of their GDP ( see fig. 40). China is also having the highest
financial depth among others developing countries ( see Fig.22), which shows the process of
financialization of the economy, moving together with the industrialization not only in China,
but in general across all economic regions. All those perspectives for economic growth and
further industrialization, based on own resources, together with the perspectives outlined in
the chapter considering the population and employment trends, we could consider that the
developing countries will remain the main driver of the increasing world demand, and global
price volatility in the next one or two decades.
The transition economies have the most unbalanced economy development, showing
decreasing of the agriculture and manufacturing ( manufacturing plunging from 29% to 15 %
in the last two decades), and increasing the extraction of resources, as well as development
of the services sector ( figures 38, 39, 40, 41). This could mean that they are supplying mainly
with resources the manufacturing of the developing and some of the developed countries,
67
Regional depth and equity outstanding, divided by regional GDP
36
decreasing their GDP added- value. At the same time the services are giving quite high share of
value- added from the GDP – 60 % ( see fig.41), but the financial depth is the lowest among all
world regions – around 142 % of the regional GDP (see fig.22). This means that the economies of
the transition countries are not so finacialized, as in the developed and some of the
developing countries. Possibly the development of service–oriented transition economies is
related more with transport, communications, international trade and retail, which are
compensating partially the decreasing agriculture and manufacturing. Since in the economies of
the transition countries, the markets are depending more on imports, than on own
development of agriculture and manufacturing, we could suggest that eventual price
volatility created either by increased demand in the developing countries, or by financial
crisis in the developed countries, would definitely influence also the market prices in the
transition economies.
3.2.4. Material Resources, Technologies and Science
The availability of material resources such as land and agricultural products, mining materials,
chemicals and other natural resources, are a key driver for the development of the real economy
and the industrialization. In the era of fast increasing population and demand, the limitations of the
natural resources and their extraction in global aspect, is an obstacle for the industry to catch
up the growing demand. This problem could reflect in higher price volatility, which is difficult to
be dealt with without breakthrough innovations in material science, and technologies
improving the productivity of the material resources.
During the last century, the global growth was based on intensive use of resources, but the
prices were not so volatile, because of the faster technological progress and the discovery of
new low- cost sources of supply. In the last decades, the new resource supply model is
challenged not only by the increasing demand, but also by many technological
advancements, which are causing substitution among different types of resources, used for
production of different type of commodities ( for example agricultural crops are used both for food
and bio-fuels production, substituting other carbon-based fuels), which intensifies the price
volatility among those commodities ( see Fig.2 and 2a and the analysis in paragraph 1.1.). This
fact imposes developing of new complex resource-based strategies both for corporations and
governments, which need to estimate their resource availability and innovation technology
capacities in a new environmental point of view. The new strategy should avoid the
implementation of disruptive innovations, that would cause big misbalances in other
resources, but should also improve the resource productivity through implementation of
new technologies. As mentioned before, according to McKinsey, with implementation of measures
for increase of the productivity of the land, energy, water and materials, could be covered
between 13 and 29% of the increased global demand in 2030 (see Fig.24). At the same time,
between 75 and 80 % of this productivity potential is in the developing countries ( see
Fig.25), mainly because of their lower productivity related with lower technology levels,
compared to the developed countries. It is interesting to stress that this analysis results does not
take into account eventual reduce of welfare, possible with behavioral changes of
consumption ( living in smaller houses or reducing the meat consumption). According to
McKinsey, the largest potential for such kind of productivity increase is in the developed
countries.68 Still, the potential of the productivity increase will not be enough to cover the majority
Dobbs R.,Oppenheim J.,” Resource Revolution: Meeting the world’s energy, materials, food, and water
needs”, McKinsey Global Institute, Nov, 2011.p 17-19
68
37
of the global growing demand, so eventual new technological breakthrough innovations are needed,
related with new investments.
The global process of transfer of innovations and technologies through foreign direct
investments is depictured on figures 42,43,44 and 45. We could notice, that the major outflows of
investments are from the OECD countries ( 3-6 % of their GDP), with highest value for EU –
app. between 4 to 9 % for the period 2007 – 2010. At the same time the major beneficiaries of
those investments are the developing countries ( 3-5 % of their GDP), some countries from the EU
and China with 3 to 7 % of their GDP ( and Australia which is economically closely tied with
Chinese and Asian economies).
As main driver for the process of the innovation and technology transfer through
investments, are the research and science government expenditures (see Fig.46,47). On
average around 2.25- 2.50 % from the GDP of the OECD countries is dedicated to the
Research and Development expenditures, with predominant role of the US (2.5-2.75%) and
EU (1,75–2%). From the developing countries biggest R&D expenditures are detected in Asia, and
especially China: around 1.25 – 1.50 % of their GDP. All other developing countries have smaller
R&D expenditures below 1 % of their GDP.
As a summary from the data exposed, we could say that the uneven patterns of the innovation
and technological development across different regions, could be considered as general
challenge for the new supply model. The equal global diffusion of innovations would ease
the supply of resources and decrease the price volatility, but on the other side this equal
technological diffusion is difficult to be applied. General reason for this, is the fact that the
investments in R&D activities are considered as investments from the parties which have done
them, bringing competitive advantage to certain governments or corporations, and they would not
agree to spread their knowledge or results at low price or share them free with other competitors. In
addition, there are other production, market and political constrains, related with dynamic shift of
technologies, markets, labor force, legislation and etc, which requires certain technical time for
whole new concepts and mechanisms to be accepted and applied. But for sure, in the current
situation of fast growing global demand, those processes should be speeded up in any form,
otherwise the high volatility of prices would cause even bigger economic problems.
3.2.5. Globalization process in business
The development of the international trade and the parallel process of globalization of the world
economy, were also main drivers for the price volatility of the commodities. The increase of the
global demand was progressively satisfied by supply from multinational and cross- border
corporations, as well as by new entrants on the global markets. This fact have intensified the
competition, but also formed many global oligopoly market structures, which played role of pricesettlers and moved up the general price trend through the years.
3.2.5.1.
International trade
The World trade in the pre- crisis period have increased by 4-5 % between 2005 and 2008,
reaching 59% of the World’s GDP, but later plunged by app.10 % in 2009, and recovered again with
increase of 55 % in 2010. The distribution among the Exports and Imports of Goods and Services
was almost equal, and the share of the services solely was around 11- 12% from the worlds GDP
(Fig.48,49,51and 53). Regionally, the exports were dominated by the developing countries, whose
export share in GDP was between 25% and 45 %, while the share in the exports of the OECD
countries was on average below 25 % of their GDP (see Fig.50). According to data from the World
bank, the developing countries from East Asia and Pacific (especially China), had the World’s
38
highest regional export share: around 35- 40% and more from their GDP. Among the OECD
countries, EU is the leading exporter with steady exports of nearly 40 % both before and after the
financial crisis, while US and Brazil were accounting only for 10- 15 % of export from their GDP for
the period 2005 -2010.
According to data from the World bank, the global Import is driven by the majority of the developing
countries, EU and China with average share of imports about 35- 30 % of their GDP. At the same
time US, Australia and the developing countries from Latin America, have lower Import share of
about 5- 15 % from their GDP.
If we compare the trends of the Annual Growth of the GDP ( Fig.6) and the Index of the
Commodity prices ( Fig.2), with the Annual growth of the International trade ( Fig.51 and 53),
we could see that all the trends are well related both in amplitude, and regionally. The
similarity of the trends could prove also, that the intensity of the global trade is strongly
connected also with the volatility of the commodity prices: there is a downturn in the prices
when the trade is low, and the opposite trend of increasing prices when the trade is
growing.
3.2.5.2.
Mergers and Acquisitions and market concentration
The mergers and acquisition (M&A) process in global perspective is a consequence of the
increasing competition between multinational and cross-border corporations. Their aim is to
integrate vertically and/or horizontally with competitors, suppliers and distributors, in order
to get economies in scale and scope, which would allow to decrease or keep the costs
down, and increase their profits and prices. Other major reasons for the transnational
companies to focus on M&A are : better chances for funding of business expansion, consolidation
of the business and ability to strengthen both the core activities and resources, faster achievement
of business growth through investments and M&A instead of organic activities ( IMAP 69).
According to data from major M&A consultants as KPMG 70 and IMAP, EMEA71 countries are
accounting for the majority of 55- 65 % from all M&A deals (see also Fig.59). The countries from
South and North America are the second biggest region with M&A deals – about 30- 34 % from the
total worldwide, and the share of the Asian and Pacific countries is about 7%.
The globalization process in the business is clearly depictured on Fig. 54. The numbers of the M&A
deals worldwide for the last 25 years has increased by 1000 % reaching range of 45-50 000
deals/year in the last 5-6 years. The value of the M&A deals in the last years has also increased
between 600 and 1200 % comparing to the levels from 1985. Another interesting trend in the M&A
process worldwide according to data from IMAP and KPMG, is the decreasing of the numbers of
the deals, but increasing of their values. On Fig. 57 and 58, we could see that the IMAP’s M&A
deals for the period 2006 – 2010 above 10 Million USD have increased by 18.6 %, and the number
of the deals have decreased by 15.6 %. The average value of M&A deals have increased by 205 %
from $29 087 156 in 2006 to $59 841 200 in 2010.
The information about the increasing importance of the M&A process worldwide is affecting
also the market segmentation, creating stronger oligopoly structures which are settling the
price trends. At the same time, more new market players are entering the markets, attracted
by the higher prices. On Figure 55, we could see that the trend of the Global import and export
concentration indices are clearly following the trends of the M&A process worldwide (Fig.54) . The
69
70
71
“IMAP Transaction and Pricing report 2010”, p.23-25, www.imap.com
“M&A Predictor, February 2012”, p.2, www.kpmg.com
EMEA includes countries from Europe, Middle East and Africa
39
similarity of the trends is most obvious between the numbers of the M&A transactions
( fig.54) and the level of the import concentration index (fig.55) – both have peaks in 2000 and
2006, and are decreasing in 2002 and 2008- 2009. This fact signifies that with the increasing of
the M&A deals, the concentration on the import market increases too ( the closer is the index
to 1, the bigger is the market concentration).
On the other side, on fig.56 we could follow the increasing trend of the Structural change index,
explaining the change in the composition of the exporters and importers on the market. Both the
export and import structural change indices are increasing for the period 1997- 2011,
signifying change in the composition of the exporters and importers on the market, or
otherwise – increasing of the competition on the global market. According to the economic
logic, the increased competition should suppress the prices on lower levels. Unfortunately
this is not the case, and as more important drivers for this price increase in the last decades,
we could blame the increased global demand and the increasing M&A process. As we already
proved in the previous paragraph, M&A are also related with the concentration on the market,
forming many oligopoly structures Besides that, if we compare the structural change index with the
trend of the commodity prices ( fig. 56 and fig.2), we could also notice that the trends between 2000
and 2012 are similar – constantly increasing, with short decrease during the financial crisis in 2008.
Possible reason for the increased number of exporters and importers could be the constant
increase of the prices in the last decades, which attracts new market entrants.
In general, those increasing trends in M&A, market concentration, structural change of the market
and commodity prices, could be also explained by the complex effect of increasing of the global
demand, related with the increasing of the world population ( fig.26), the GDP, urbanization and
industrialization processes, explained in the previous paragraphs.
3.2.5.3.
Cross- border Investments
The cross- border investment flows and their dynamic are a very good measure of the globalization
process and its trends, together with the processes of internationalization of the trade and the
Mergers and Acquisition worldwide. The intensification of the global cross- border investments,
business and trade, is bringing intensification in the redistribution of the financial, natural
and human resources across countries and continents. On the other side, globalization
intensifies also the supply and demand patterns, raising the price of the resources and
products worldwide.
As already mentioned in the paragraph concerning the material resources and technologies, the
free direct investments (FDI), are also helping to transfer the innovations and technologies with the
new facilities established across different regions. On Figures 42,43,44 and 45, we could notice
that the major outflows of investments are from the OECD countries ( 3-6 % of their GDP), with
highest value for EU – app. between 4 to 9 % for the period 2007 – 2010. At the same time the
major beneficiaries of those investments are the developing countries ( 3-5 % of their GDP), some
countries from the EU and China with 3 to 7 % of their GDP ( and Australia which is economically
closely tied with Chinese and Asian economies). Another interesting trend that we could notice,
is that the FDI outflows are increasing from the developing countries and China, while those
from the OECD countries ( especially EU), are decreasing ( fig.44 and 45). This last trend is
signifying a new pattern in the globalization. While in the last decade the FDI direction were
more from the Developed to the Developing countries, in the last years, there is an
intensifying change of the main FDI direction from the Developing to the Developed, and
other Emerging markets.
40
On figures 60 and 61 we could see more clearly the change in the global investment flows in the
last decade according to McKinsey72. In 1999 ( fig.60) the global financial integration have already
been running for about 5-10 years, and the global stock of foreign investments accounted for about
28 trillion USD, or 79 % from the global GDP. The major investment ties were between the
developed countries – USA, Western Europe and Japan. USA accounted for 50 % of all global
cross- border investments. At that time, the cross- border investments in the developing countries (
Asia, L.America and Eastern Europe) accounted for less than 1 trillion USD.
The cross- border investment flows have become more complex in the last few years, with the
increasing wealth of the developing countries, which started moving their financial resources on
other emerging markets, and even in some of the developed countries. The cross- border
investments from US in 2009 had shrunk to 32% from the global flows, compared to 50 % in 1999.
This situation was caused mainly because of the creation of the Euro and the invasion of Western
European capitals on the emerging markets of Asia, Eastern Europe, Africa, Missle East and
L.America. In parallel with the accumulation of capitals in the developing countries, the level of the
cross- border investments between emerging markets ( Asia, L. America and Middle East)
increased about 39 % annually, which is much faster than the development of their investment ties
with the developed countries.
This new trend in the globalization of the emerging markets, and decreasing of the strong
role of the developed countries, especially after the financial crisis from 2008, is suggesting
new challenges to the supply- demand model, which was valid for the last decades. From
one side, the increasing demand from the developing countries is moving the prices to
higher levels, and the processes of increasing of prices is intensified by the closer ties of
the regional markets under the new conditions of globalization. On the other side, the
weaken economic situation in the developed countries and the fast improvement of the
economies from the emerging markets, and the change in the direction of the cross- border
investments, would bring additional price pressure for the developed countries, which still
have close investment ties with the emerging markets. The fast increase of the GDP and
prices on the emerging markets will definitely reflect on the investment and production
costs of the developed countries on those markets, and will erode the profits of the
multinational corporations in a long- run, which are also focused on the shrinking markets in
the OECD countries.
Summary
Exposing the main factors for the volatility of the commodity prices on the global market, we could
summarize, that the sources of this volatility are very complex. Three main groups affecting the
price volatility could be outlined from the analysis – macroeconomic, finance- based and
globalization- based.
The dynamic of the commodity prices increased seriously in the last decade. While commodity
prices have fallen by almost 50% over the past century, the volatility of the commodity prices has
increased a lot since year 2000, and especially with the beginning of the world financial crisis in
2007-2008. According to different sources, some of the main reasons for the increased price
volatility are:
72
. “Mapping global capital markets 2011”, McKinsey Global Institute, p.32,33
41
-
Increasing of the world population in the developing countries
Correlated demand across resources, which causes increase of the linkages between price
levels of the different commodities
Technological advancement and resource scarcity, both boosting the substitution between
different resources,
Increasing Interconnections between the different regions from the global market
Trying to find in details other reasons, for the volatility of the commodity prices, and ways to
improve it, we have analyzed first, the macroeconomic factors like currency exchange rates,
inflation, GDP, interest rates.
The role of the currency exchange rates on volatility of commodity prices is very big and
complex in its character. The analysis showed that there is a negative relationship between
the commodity prices and the currency rates referred to USD. This means, that whenever there
is a devaluation of the exchange rates of the USD, there is an increase in the commodity prices.
And on the opposite – commodity prices are decreasing, as the USD exchange rate is increasing.
The volatility of the prices which at present is strongly related with the global trade, is
seriously affected by manipulations of currency rates through the governments and the
financial markets. The market and financial interests of the USA, Europe and China, and global
financial market players, are forming the major trends of the global trade and currency rates, which
are replicated in the prices.
Our analysis have proved, that there is a positive relationship between the inflation and the
commodity prices, which means that part of the price volatility is caused by the inflation. The
inflation is spreading unequally among industries and groups of people in short and longterm periods, since it is a macroeconomic factor, related with many economic issues like
money supply, unemployment and wages, inflationary expectations and economic activity.
These complex economic relationships are reflected also in the national GDP, and the
analysis showed that GDP per capita is also positively related with the trends of the inflation
and the commodity prices. In global aspect of specialization of the developing countries in many
industries with global market impact, the faster increasing of their GDP ( 2 to 5 times bigger,
compared to the developed countries), is causing tightening of the global inflationary cost/wageprice spiral, spreading worldwide and increasing the volatility of commodity prices globally.
The interest rates, similarly to the exchange rates, have very complex impact both on the
real and financial markets, and are manipulated by the financial market, and the
governments. But unlike the exchange rates, interest rates are positively related with the
commodity prices and the GDP growth. In general, lower interest rates are stimulating the
development of both real and financial markets, while higher interest rates are stagnating
them. There are many mechanisms of the interest rates influence. From one side, interest rates
are affecting the real economy growth, stimulating or stagnating the business and
investment activities, inventory levels and consumption through different credits. On the
other side, lower levels of interest rates are intensifying trade on the derivative markets, with
currency rates, interest rates, credit default swaps and commodities. The intensification of
derivative trade is bringing both higher levels of the traded instruments on the real and
financial markets, and increasing more the price volatility of commodities.
Closely related to the effect of the interest rates over the volatility of the commodity prices, special
attention in our analysis was paid on the effect of the derivative market and the financialization
of the world economy. The trade on the derivative markets have developed significantly in the last
decade, and especially with the beginning of the world financial crisis since 2007, when the
volume of the outstanding gross market values of the main derivative contracts increased
42
enormously, signifying big financial risk for the market players, and the liquidity risk of the
world financial markets in general. In our analysis, we have noticed, that the dynamic of the
commodity prices and the trends of the outstanding commodity contracts on the organized
financial markets, showed similarity in their trends. We suggest that this similarity is coming
from the connection between the volume of the traded commodities, and the volume of the
outstanding derivative contracts, reflecting better the expectations of the financial players
about the prices on the physical markets. Besides that, the main commodities in each major
industry are priced through financial market indices, already proved to be subject many
times to manipulations through information agencies and banks.
Another dimension of the financialization of the world economy, was outlined not only with the
similarity between the trends of the Commodity indices and the trade on the official financial
markets, but also between the annual regional GDP growth, and the S&P equity indices,
preceding the GDP trends with one year. The fact that the financial trends were preceding
the trends of the real economy, are again related with the subjective future expectations of
the financial players, which are channelling huge amount of financial resources
predominantly in limited industries and regions. This fact is causing financial bubbles, and at
the same time decreasing the possibility for big profits, redistributing them among more people,
and/or causing heating of the certain perspective industries through overinvesting. The fact that the
investments on the derivative market in USA have reached 447 % of their GDP ( and between 100200% of GDP of many developed countries) , before the beginning of the financial crisis, is a good
example, on how the distortion of the financial flows in the one economy, between the driving
real market, and the investments on the financial market, could cause big financial risk and
fiscal problems worldwide. Significant element of those complex economic problems is also
the volatility of the commodity prices.
The process of Globalization in different aspects of transport and communication, economics,
finance, human development and science, developed progressively in the end of the 20th century,
and intensified in the last decade, affecting the roots of the all available classic theories and views
about the world. As main drivers related with the globalization, which affected the volatility of
the commodity prices, we assume the increase of the population and the global demand,
together with the industrialization and urbanization processes mainly in the developing
countries. In our analysis we have noticed big absolute increase of the global population,
urbanization and industrialization, which might be blamed for the increase of the commodity prices.
At the same time, the annual trends of those factors are detected to be predominantly decreasing,
both in developing and developed countries. Despite that the GDP of the developing countries is
increasing in times quicker than in the developed countries, there is a limit of the consumption and
demand, related with reaching of certain level of lifestyle, which decreases slightly the demand with
the economic development. Besides the fact that the world population is increasing more slowly,
there is a serious ageing process worldwide, which provokes question for many multinational
companies and governments, how to sustain their development.
Another dimension of the globalization that affects the commodity prices, is the obvious
global division of labor and specialization between developing, transition and developed
countries. There is a certain East- West direction of the global cost structure of the prices,
where the developing and transition economies are providing cheaper material and human
resources for production, while the developed countries are investing and outsourcing their
business there, implementing higher technologies and know- how, and later exporting the
final goods and selling them much expensive on West markets. The process of globalization
has profiled many of the developing countries as highly industrialized, focused on manufacturing
and extraction of natural resources, using the abundance of and human resources and their lower
43
prices/wages. The transition countries specialization is in the extraction of natural resources and
services related with the real economy. Developed countries are specialized in R&D, technologies,
as well as services, especially financial markets.
The motivation of the business companies, especially of the transnational corporations, is to
combine all those resources of developing, transition and developed countries, in order to
get the best possible combination quality- price. This is also the motivation behind the
increasing trends of international trade, foreign direct investments, mergers and acquisition trends
worldwide. Utilizing enormous profits from those global economic processes, the
transnational corporations formed many global oligopoly market structures. This allows
corporations to keep the prices higher, despite the decrease of the manufacturing costs,
using the global economies on scales and scope, and the lowest costs for each production
factor worldwide.
It is also interesting to notice, that after years of accumulating profits and increasing GDP levels,
the Asian developing countries, changed the trend of globalization in the recent years,
especially after the start of the world financial crisis. The old mainstream of investments and
business activities changed from West- East, to new direction East- West and East- East.
Motivated by the increasing global demand and markets in Asia, it seems like the Western
markets are losing their attractiveness for business, and the increasing regional prices in Asia
will further cause severe increases in prices in OECD countries, also due to their
dependency for cheaper resources and production from the developing countries. Eventual
improvement of the resources and prices in the developed countries could be reached,
through new breakthroughs in material science, new technologies, and change in the
consumption behavior.
In addition to the summary about the globalization and the financialization process in the world
economy, and the effect over the volatility of the commodity prices, we could picture the process of
shift from national to global economy and the predominant development of the finances. We could
say that the general process of globalization and financialization of the world economy
consist of four stages, which might be seen in the development of each country and
globally:
- Stage 1: On the first stage are the development of the national economy through national
resources, industrialization, manufacturing, human resources, technologies, development of
finances and banking.
- Stage 2: On the second stage, after extracting, or missing some of the mentioned factors or
resources, or looking for new markets, the national economies start using international
finances, trade, transfer fully or partially their technologies, productions, finances abroad through
outsourcing, JV,FDI, M&A, financial investments and etc. Banks and financial institutions are
operating with huge amounts of financial resources, and are mainly mediators of different
transactions and credits.
- Stage 3: On the third stage the internationalization and globalization, trying to predict the risk of
their financial operations, financial investors and analysts are creating and using more the
financial markets, which partially or fully start settling price indices for all types of
commodities traded on the physical markets.
- Stage 4: On the last fourth stage, the difference between pricing of commodities on the real
and financial markets is totally blurred, and the traders on the real markets are not anymore
the real driver behind the dynamic of the prices. The real price drivers are the financial
analysts and information agencies, and their market assumptions and calculations.
Now days the global economy is working in a free or less restricted and competitive global market,
where no matter of the stage of economic development of each country, the world prices of
44
all commodities are following the price trends shown by the financial markets in the most
developed countries ( Stage 4). The financial markets have almost fully substituted the price
function of the real markets and traders. This means, that the volatility of the commodity
prices is only partially dependent on the real markets, but more and more depend on the
volume of trade on the financial markets, which have increased enormously in the last
decade, together with the volatility of commodity prices.
Empirical Analysis -2
Analysis of the Globalization and Financialization of the Iron ore and Steel
industries, in the context of increased volatility of iron ore prices
The second analytical part concerning the price volatility, is dedicated to the iron ore
prices, which are related with the iron ore and steel industries. In order to represent
the process of globalization and financialization of the iron ore and steel industries, and the
effect of the new price system for iron ore trade since 2010, this analysis is separated into
four parts. Looking for global supply- demand imbalances, leading to the volatility of
the iron ore prices in the recent years, in the beginning of the analysis are outlined the
major world supply and demand trends from the iron ore and steel industries, considering
the production, imports, exports, apparent steel use, iron ore reserves worldwide, and the
price elasticity of the iron ore demand. As a second possible reason for the increased
volatility of iron ore prices, we consider the globalization and consolidation trend in the iron
ore and steel industries. We have outlined the consolidation process in both industries,
through joint ventures, mergers and acquisitions, which leads to formation of
globally more integrated, segmented and oligopoly market structure of the iron ore
and steel business. This consolidation process led by the biggest market players,
especially those placed at the end of the value- chain of the steel production- the leading
iron ore miners, facilitates the setting of higher margin profits, and increasing of iron ore
prices even more. In order to prove this statement, we have analyzed in details through
linear regressions, the profit margins and the revenues of selected 24 top, middlesized and small companies from the steel and iron ore industries for the period 20022011. In addition, bigger samples of 150 steel producers and 150 iron ore miners
were analyzed, through linear regressions of their profits margins and revenues for the
same period. The results are showing strong positive trend of increasing of the profits of the
companies from the iron ore industry, and deterioration of the profits of the steelmakers,
which could fuel further the consolidation process between both industries, and increasing
the prices to higher levels, speculating with the strong market positions.
In the third part of this analysis, we have explained the nature of the change in the
price system for Iron ore since 2008-2010, and have analyzed the differences
between the traditional annual price settling by the market players of the iron ore,
which was a global practice for decades, and the new price system which settles prices
quarterly and monthly, based on spot prices, quoted by information agencies and financial
markets. We claim, that the new price system for iron ore has strong effect on the
price volatility of iron ore in the recent years, which is proved with the analysis of the
revenues and profits, and in addition with statistical analysis of the volatility of the
iron ore price, in the last fourth part of our empirical analysis. First , we have
45
calculated the iron ore price volatility before and after the implementation of the new
price index IODEX62 in 2008, which proved the increased volatility of the iron ore
prices for the latest period. Afterwards, we have conducted multiple regression
analysis for the same pre and post- periods, for the major global prices of iron ore,
including main macro, logistic and trading factors. We have found some exceptional
changes in the influence, of many traditional supply- demand price factors - result from the
change of the classic pricing system for iron ore. The results are showing also
increased price volatility for the iron ore prices in the post- period, especially for the
Brazilian and Australian exporters. At the same time, the price volatility has
decreased for the Chinese and Indian markets, after the implementation of the spot
price index IODEX62.
4.The Global Supply and Demand, and Consolidation Process in the Iron ore and
Steel Industries. Analysis of the Profits and Revenues of the Iron Ore Miners and the
Steelmakers.
4.1. Supply – Demand analysis of the Iron ore
The importance of the of the steel industry for the world economy is determined by the fact,
that different steel products are forming between 15 % and 65 % of the costs of final
products from major markets like automotive industry, construction, machine building,
different appliances, packaging for the food and other industries ( LME73). On the other
side, the cost of the final steel products depend most on the price of the iron ore, because
on average the production of one tone steel, requires about 1.4 tones of iron ore. Other
major raw materials determining the steel price is the coking coal, which requires on
average 770 kg per 1 tone of steel. ( Worldsteel 74). Having in mind that, in our analysis we
are going to analyze the supply- demand balance of steel and iron ore, and will pay special
attention to the iron ore balance on the global and regional markets, as a major steel raw
material price- determinant . We will try to analyze if there is a reason to consider, that
there is a deficit in the supply of iron ore, which causes the volatility of the iron ore prices,
as well as will outline major iron ore and steel demand and supply regions and markets.
On figures 62 and 63 from the Annex, we could see the major trends in the supply and
demand of Iron ore by countries and world regions in the last 5 years. For the period
of 2005- 2010 the total world iron ore production have increased by 30- 32 % both by
major production countries and regions, reaching 1,7- 1,8 million tones annual world
production. Regionally Asia is leading in the iron ore production, which for the considered
five years period consist about 30 % of the world production. China and India are the main
iron ore producers in Asia, representing respectively 24 % and 12 % from the world iron ore
production, which increased as world market share accordingly by 2% and 1 % in 2011,
compared to 2005. The second most important region and country for the global iron ore
production is South America, and especially Brazil which is the main iron ore producer in
the region. In 2011, Brazil represents 22% of the global iron ore production, which is a
decrease of its global market share with 1 %, compared to 2005. The third most important
London Metal Exchange, “ The Steel Industry Globalization Trends, Abstract of presentation to LME Members”, May 23,
2003, p.19,20
74 Worldsteel, “ Fact sheets Raw Materials”, p.1 http://www.worldsteel.org/dms/internetDocumentList/fact-sheets/Factsheet_Raw-materials2011/document/Fact%20sheet_Raw%20materials2011.pdf
73
46
iron ore producing region is Oceania, with dominant market role of Australia. Regionally,
the market share of the iron ore coming from Oceania has increased by 5 % in 2010
compared to 2005, reaching 24 % from the global market. At the same time Australia has
slightly decreased its markets share by 1% for the same period, but still remains a leading
global supplier of iron ore. The fourth important iron ore supplier globally are the CIS
countries, especially Russia and Ukraine. CIS as a region has decreased its global market
share by 2 % for the period 2005- 2010, but the market shares of Russia and Ukraine are
almost unchanged for the same period, accounting respectively 7- 8 % and app.5 % from
the global iron ore market.
Further, on figures 64 and 65 from the Annex, we could follow the trends in the export of
iron ore globally, by regions and countries. The export from all major exporting
regions have increased by 49%, from 746 mln.tones in 2005, reaching 1113 mln.
tones in 2010. Main exporting countries are Australia, Brazil, India, South Africa and
Canada, representing 80 % from the global export of iron ore. The top three exporting
countries are Australia, Brazil and India, are representing app.73 % from the global export
of iron ore for the considered period 2005- 2010. It is interesting to mention that due to the
dynamic increase of the steel and iron ore demand from China, Australia became preferred
regional supplier of iron ore to developing Asia, and increased its market share on the iron
ore global market by 4 % during 2005 -2010. At the same time the both market shares of
Brazil and India dropped by 2 %, pressed by the Australian competition, as well as by
increasing national demand.
Overview of the global and regional imports of iron ore could be seen on figures 66
and 67 from the Annex. The total world imports of iron ore have risen by 42 % since
2005, reaching 1072 Mt in 2010. For the same period there was a significant change in
the regional markets, with a 10 % decrease of the iron ore imports from the European
Union ( 27), and at the same time 15 % increase of the import market share of Asia. The
demand from CIS countries and North America have sunk also by 1-2 % for the
considered 5- years period. Similar significant change of trend was detected also among
the leading countries importers of Iron ore – China, Japan, S. Korea, Germany, France
and Taiwan. In total, all mentioned countries increased their imports of iron ore by 12%
from the world iron ore imports. The increase is coming mainly from China, which increased
its imports by 21 %, reaching 642 mln.t of iron ore imports in 2010, representing 57 % from
the world iron ore imports. Significant decrease of the iron ore import market share was
detected for Japan : - 5% in 2010 compared to 2005. In downturn are the market trends
also for Korea, Germany, France and Tawian, which have also decreased their market
shares in imports of iron ore in 2010 by 1-2 %, since 2005.
We could summarize that in the period 2005- 2010, there was a significant increase
of world iron ore production and iron ore exports and imports, respectively by 30- 32
%, 49%, and 42 %. Besides that, significant change in the global balance of iron ore
supply and demand was detected. Leading role of China on the market came with its
increasing iron ore demand, production and imports. On the opposite, the demand,
and imports from EU and Japan, and other traditional markets decreased
significantly. The main exporting countries - Australia and Brazil sustained and
developed their global dominant iron ore supply role, despite the decreased demand
from EU and Japan, using the driving demand coming from China and India.
On figures 68, 69 and 70, we could also follow the regional and global supply- demand
dynamic of the steel production. The world steel production has increased by 22 %
for the period 2006- 2011, reaching 1527 mln.t. in 2011. Similar significant changes of
47
the trends on the global steel market are detected, as it was outlined for the iron ore
market. Asia has increased its steel production for the considered period 2006- 2011 by 11
%, with leading role of China .The steel production of China increased its share of the
world steel production from 34 % to 45 % , reaching 696 mln.t. in 2011. At the same time
the European countries experienced decrease in their steel production from 355 mln.t in
2006 to 329 mln.t. in 2011, representing 7 % decrease from the global steel market share
of EU and CIS together ( - 5 for EU 27, and – 2 for CIS ). Another significant decrease in
the steel production of about 2-3 % from the global market, was experienced in North
America, and especially in USA. In 2011 the countries that impacted mostly the global
steel market were: China with market share of 46 %, Other Asian countries ( 18 % from the
global market), EU ( 12%), North America ( 8%), and CIS ( 7.6 %).
In order to estimate the global demand and supply for iron ore, we are interested in
the Global apparent steel and iron ore consumption. The Apparent consumption or use
is calculated by the formula75:
Apparent use = Production + Imports- Exports
Usually the apparent use is defining the national domestic consumption, not taking into
account the changes in the stock levels as it does the real consumption. In our case we will
analyze the apparent use/consumption of steel and iron ore, because we do not have data
about the stock levels. At the same time, we have found ready data about the apparent
steel use in Worldsteel. For calculating the iron ore apparent use, we are using the data
about global production, imports and exports previously exposed ( fig.62, 65, 66) and the
above mentioned formula. The results are represented in tables and graph on figures 71,
72, 73, 74, 75 from the Annex. We could see that the World apparent steel use have
increased from 1042Mt in 2006 to 1300 Mt in 2010, and the iron ore apparent
use/consumption have risen annually from 1410Mt to 1779 Mt for the same period. It
is interesting to mention that there is a similarity in both trends, and for the considered
period, the iron ore consumption is between 35 % to 43% more than the steel
consumption, which is related mainly with the cost structure of the final steel production. On
average the production of one tone steel, requires about 1.4 tones of iron ore, but it could
vary depending on iron ore grade, and the production process and technologies used.
Regarding China, we could confirm again its driving role on the global iron ore and
steel market. The Steel consumption per capita in China has increased by 73 %
between 2005 and 2011, reaching in 459 kg annually per capita in 2011. The steel
consumption per capita in China for the same period was always higher than the average
world consumption of steel, increasing gradually this difference from 53% above the world
average steel consumption in 2005, to 126 % higher than the world average steel
consumption in 2011 ( only 215 kg steel per capita). The Iron ore apparent consumption
in China increased by 13 % between 2005 and 2010, reaching 53 % from the world
apparent iron ore consumption in 2010, or 934 Mln.t
When we want to estimate the possible supply of iron ore, we are also interested in
the world iron ore reserves. On fig. 76 we have exposed date from USGS76 about the
world iron ore reserves by countries in 2010, which we believe to be true, even though
75
76
http://www.steelonthenet.com/glossary.html
http://minerals.usgs.gov/minerals/pubs/commodity/iron_ore/feoremcs05.pdf
48
data from Australian Government Geosciences Agency77, is showing that the resources of
iron ore are much bigger worldwide, and especially in Australia, mining companies are
finding new iron ore mines almost every year.
On Fig.76 we could see two columns for Iron ore reserves – Crude Iron ore and Iron
Contained. The first one shows the tonnage with the impurities, not taking into account the
iron ore content. In the second column the data is recalculated according to the iron ore
content of the ore. According to USGS and Australian Government, Australia and Brazil
each, process in 2010 about 18 % of the world iron ore reserves, which is ranking them on
the top of the world iron ore reserves. China also is highly ranked for its iron ore reserves,
but they are with lower iron ore content. The world iron ore production consists of 60 %
high- grade hematite ores ( Mainly from Brazil and Australia), and the left 40 % are lowgrade magnetite ores. China has large resources of 23 Giga tones magnetite ores with app.
30 % iron ore content. USA posses about 27 billion tons of iron reserves according to
USGS. The majority of the iron ore resources in USA are also with low content of iron ore
and require pelletising prior to commercial use. Ukraine is also owning big iron ore
resources, with lower quality.
USGS is estimating the world iron ore resources to exceed 800 billion tones of crude
ore containing, and more than 230 billion tones of iron. According to the Australian
Government, the iron ore reserves will be available for the next 80 years. Though,
there is a problem with the fast increasing global demand and the increase of the
exploring expenditures. According to the Australian Bureau of Statistics, the
exploration expenditures for iron ore in 2010 totaled 553 mln. USD, which is 6 %
higher than the leveld from 2009. There are also many environmental problems with
the mines exploration, like ecological requirements preventing the fast exploration,
or seasonal floods, company strikes, preventing the regular shipments of iron ore.
As an alternative of the use of bigger quantities of high- grade iron ore, some steel
producers are practicing blending of grades, pelletising or use of scrap, even though due to
high prices or lower exploitation results, the use of high grade iron ore remains the most
preferred resource.
The leading iron ore producers in Australia and Brazil are constantly increasing the
exploration of new or existing mines, so in terms of quantities, there shouldn’t be a
reason for shortage of iron ore on the global market. On the other side, the increased
investment and exploration costs might imply some increase in the final price of the
iron ore.
After calculating the apparent iron ore consumption, and looking for explanation of the
volatility of iron ore prices, related with the supply and demand balance, we would like to
calculate also the Price elasticity of demand of iron ore. We will use the following
formulas ( Besanko, 2007) 78:
ή= ΔQ/Q0
ΔP/P0
77
78
;
ΔP= P1- P0, ΔQ = Q1 - Q0
http://www.australianminesatlas.gov.au/aimr/commodity/iron_ore.html
Beasnko,” Economics of Strategy”, John Wiley and Sons, 2007,p.24
49
Where, ή is the price elasticity of demand, P- prices for the periods 0 and 1,
and Q- quantities for periods 0 and 1
The calculations are given in figures 76e, 76f and 76g from the Annex, and the
corresponding graphs- under figures 76a, 76c, 76d. In addition on fig. 68a and 76b, we
have exposed the price dynamic of the major iron ore grades on the global market
for the period 2006- 2011.The data for Australian BHP FOB iron ore price, and Chinese
EXW iron ore prices are taken as benchmarks for calculation of the % Change in price,
and Price elasticity of demand in the World and China.
On fig.76b.we could analyze the price dynamic of the major iron ore prices for the
period before and after 2008, when started both the world financial crisis and the
quoting of the new benchmark iron ore price IODEX 62 was introduced by the
information agency PLATTS. The FOB iron ore prices from Australia and Brazil,
together with the EXW China iron ore prices have increased with similar trends
between 2005 and 2008 – app. 222-232 %. Than only for one year, the price trends of
the export prices start differing from the EXW China trends, which became similar to
the new introduced benchmark IODEX 62. After the financial crisis from 2008, in 2009
all iron ore prices dropped significantly. The export prices from BHP and Vale dropped
by 12-15 %, while the Chinese EXW prices dropped similarly to the new IODEX 62
benchmark – about 33- 38 %. The different trend pattern between the FOB export
prices from Australia/Brazil, and the Chinese based EXW and CFR prices continued
also till 2011. FOB Australia and FOB Brazil iron ore prices increased by 242- 263 %
between 2009- 2011, while both EXW China and IODEX 62 CFR China benchmark raised
by exactly 211 % for the same period. At the same time, in 2011 the average annual
benchmark price IODEX 62 CFR China for first time reached the price levels of the
export prices FOB Brazil and Australia – about 166- 170 USD/Dry Mt. This process
started from the usual annual price settling from April in 2011, when the IODEX 62
was widely accepted for commercial use for monthly and quarterly pricing. In general
for the period 2005 – 2011 the Brazilian and Australian export iron ore prices increased
from app.35 USD/ Drymt to app.170 USD/Drymt, which represents increase of about 485%.
The increase for the Chinese EXW price for the same period is 293 %, reaching average
annual price in 2011 of 129 USD/Dmt.
When analyzing the Price elasticity of iron ore demand (fig.76d, 76g), we could see that
the demand in China was not price elastic in 2006 ( -322.15%), and during 2008 –
2009 ( - 56 and - 32.96%). It means that in those periods, the Iron ore demand in China
was not very responsive to the change in price. In 2005- 2006 the iron ore demand in China
increased from 560 to 682 Mt, while the EXW iron ore price in China dropped on average
annual basis from 44.51 USD/Dmt to 41,50 USD/Dmt for the same period ( see figures 68a
and 75). In 2008 the Chinese iron ore demand dropped to 765 mln.t from its higher level of
783 mln.t in 2007, while at the same time the prices jumped from 69.82 USD/Dmt to 99.22
Dmt EXW China. In 2009 the demand in China increased to 861 mln.t, but the price
dropped to 61.44 USD/Dmt.
The iron ore demand in China was price elastic in 2007 and 2010, showing positive
values respectively of 21.70% and 12. 13% (fig. 76d, 76g). In 2007 the iron ore demand
in China increased to 783 mln.t, and the price reached 69.82 USD/Dmt. In 2010 the iron
ore demand in China was the record 934 mln.t, and the price jumped to 104.61 USD/Dmt
EXW China ( see figures 68a and 75).
50
The World iron ore demand elasticity during 2006- 2010 stayed positive for almost
the whole period, even though there were some downturn fluctuations around 2008,
similarly to the trends on the Chinese market described above. The world iron ore
demand stayed highly sensitive to the changes in prices, prior the crisis and
implementation of the IODEX62 price benchmark - in 2006 and 2007 the World iron
ore price elasticity was about 50 % ( see fig. 76d, 76g). The World iron ore demand
increased from 1410 mln.t in 2005, to 1701 mln.t. in 2007, while at the same time the
average Australian FOB prices raised from 34.83 Dmt to 49.57, for the same two- year
period ( see fig. 68a, 74) In 2008 the price elasticity of demand changed the trend to
inelastic ( 0.74%), and remained not very sensitive to changes in the price. The world
iron ore demand increased very slightly on annual basis by 8 mln.t , reaching 1709 mln.t in
2008, while the benchmark FOB iron ore prices in Australia raised for the same year from
49.57 USD/Dmt , to 81.02 USD/Dmt ( see fig. 68a, 74). In 2009, the world iron ore
demand became again highly sensitive to price changes ( 29,03%), when the demand
increased to 1633 mln.t and the prices dropped to 68.61 USD/Dmt. In 2010 the trends of
the World and Chinese iron ore price elasticity of demand, showed similar positive
values for a first time: 14.25% for the world demand, and 12.13% for the Chinese
demand. The world iron ore demand reached 1779 mln.t. in 2010, and the Australian FOB
benchmark price raised to 166.44 USD/Dmt on average annual basis.
It is quite difficult to summarize the reasons for all changes of the price elasticity of demand
on the Global and Chinese market for the period 2006- 2010. There are many factors that
are influencing the change in iron ore prices. Continuous floods, strikes, logistic and
transportation problems, difficulties in exploration of mines could cause short or
long- term disruptions of the regional and global iron ore supply. We have clarified
that the world reserves of iron ore are not a problem, but mostly the increased
exploitation costs and the fast increasing demand, which is difficult to be
compensated by the miners. Very important factor is also the financial stability of the
iron ore producers and customers, as well as the terms of contracting and pricing,
which have changed since 2008. From the supply- demand analysis exposed above,
we could suggest that the main reason for the increase of the global iron ore prices
in the period 2005 – 2011, is the doubled demand for iron ore coming predominantly
from Asia, and especially China. The shift in the traditional iron ore markets, and
especially the decreased consumption of steel and iron ore from the EU and North
America, affected the iron ore demand and supply only temporarily during the collapse of
the financial systems in USA from 2008, affecting further most of the developed countries in
EU, and other developing countries all over the world, and led to drop of the iron ore prices.
The huge increase of the iron ore demand coming from China, compensated more or less
the decreasing trends coming from Western countries, and kept the prices rising after 2009.
At the same time, from June 2008 the implementation of the iron ore benchmark spot price
IODEX 62 CFR China by the information agency PLATTS, was aiming to follow the market
trends on the Chinese market. With the time, it was accepted by the major iron ore
producers in Brazil and Australia for contract and price negotiations, together with the
reformed pricing changed from annual to quarterly basis. What we could detect from the
analysis of the price elasticity of demand, and the dynamic of the prices, is that the
FOB export prices of iron ore from Australia and Brazil showed similar trends, and
were very sensitive to the increase in the global demand. This price sensitivity of
demand was higher in the beginning of the analyzed period, and steadily decreased,
reaching the end of the period – year 2010. At the same time the Chinese EXW iron
51
ore price was showing higher price fluctuations, and was highly non- sensitive to the
Chinese iron ore demand in 2006. Reaching 2010, the trend changed to positive,
reaching price sensitivity of demand app.2 % lower, compared to the world price
elasticity of demand ( fig.76d). A significant role for this alignment was played by
the benchmark iron ore index IODEX 62 CFR China, which was introduced by the
financial market players and information agencies, to the iron and steel industry
during the financial crisis, both as possibility for new derivative trade, and as
possible use for real contracting. On fig.76 we could see that the first year when IODEX
62 CFR China was introduced, it was following straight the dynamic of the Chinese iron ore
prices EXW. In 2009 and 2010, the IODEX62 trend was adjusting to the trends of the
export prices FOB Australia and Brazil, while in 2011 CFR China – based IODEX62,
reached the levels of the FOB- based Australia and Brazil iron ore prices. At the same time
the Chinese EXW prices lost the trend similarity with IODEX62. It is obvious that we can
not compare FOB and CFR prices, without taking into account the transportation costs,
which are quite big and also fluctuating.
In short, we could outline as main price volatility drivers the increasing demand for
steel and iron ore from Asia and China, logistic problems and increased operating
costs of iron ore miners, and the implementation of the new price system on
quarterly basis using the benchmark iron ore spot price index IODEX 62 CFR China.
4.2.Globalization and consolidation of the Iron ore and Steel Industries
The process of Globalization in the Steel industry started in the late 60-ies and beginning of
70-ies of the 20th century, during the time of the first and second world Oil crises. The world
steel consumption by that time have almost tripled the steel consumption, compared to the
period before the World War II, reaching levels of about 700 mln.t of world annual steel
consumption, centered predominantly on national and continental markets. During the late
80ies and beginning of 90-ies of the last century, another significant global effect over the
world steel consumption was the Falling of the Berlin Wall, which opened big new markets
of Eastern Europe for the Steel and Iron ore industries, which intensified the international
trade to next level of about 800 mln.t of steel consumption. The international competition on
the steel market also caused decrease of market share of the top 10 steel producers, from
40 % in 1972 to 10- 15% in 1993. The last globalization and consolidation effect in the steel
industry, which started in the last 90ies and continues till present moment, is the influence
of the China as major world economic driver and power ( LME 79). For this period of about
20 years, the total world steel production have almost doubled , reaching levels of 1500
Mln.t in 2011 ( Fig.68 ). At the same time the concentration on the global steel market has
recovered through international joint ventures, mergers, acquisitions, and the top 10 steel
producers reached about 27% of the global steel trade. ( Fig.68 and 77).
The biggest takeover, which formed today’s global market structure of the steel industry,
came in June 2006 after Mittal Steel paid to Arcelor the amount of 33.1billion USD to
acquire the leading company in the steel industry by that time.80 Forming the leader steel
company , keeping around 30% of the global market share, was a result of preceding
consolidation process by both Arcelor and Mittal Steel. Mittal Steel had consolidated
79
London Metal Exchange, “ The Steel Industry Globalization Trends, Abstract of presentation to LME Members”, May
23, 2003, p.3,14
80
http://www.nytimes.com/2006/06/25/business/worldbusiness/25iht-steel.html?pagewanted=all
52
through mergers and acquisitions a lot of steel producing and mining companies from
Eastern Europe, CIS, Latin and North America, India, Africa. At the same time Arcelor has
concentrated its mergers and acquisitions more in the steel production and steel
distribution in Western European countries, and in some assets in Brazil, Canada and
Africa. In 2007 ArcelorMittal continued its expansive growth strategy with 35 new
investments through partnerships, mergers and acquisitions in mining and steel industry
worldwide.81 The world financial crisis from 2008 deteriorated the investment activity and
growth of the company, and its market share decreased by 12% for the last 5 years. ( see
fig.77 from the Annex).
The process of mergers and acquisition between the steel and iron ore industries became
necessity with the increasing volatility of the energy costs and raw materials like iron ore
and cocking coal, which squeezed their working capital( Nestour82). The mergers and
acquisitions between both industries was the only way for the steel producers, to keep
running and not transferring totally the increased raw material costs to the customers, in a
situation of unstable demand for steel. With the increasing prices of raw materials,
tightening of iron ore supply , and changing raw materials prices on semi- year and
quarterly basis, the steel makers were trying to renegotiate more often the increasing
prices, looking to secure supply of raw materials through joint ventures, mergers and
acquisition with miners. During 2010 worldwide there were 20 deals by steelmakers
targeting wither iron ore or cocking coal.
The steelmakers have to fight with the increased bargaining power of the three big iron ore
miners – Vale, Rio Tinto and BHP Billiton, which not only kept, but also increased their
oligopoly market power. For the period 2004- 2011 the leading three miners increased their
market share in total from 64 % to 76 %, increasing their global supply from 403mln.t to
683 mln.t iron ore ( see fig.78, 79). Attracted also by the increased prices in the steel
industry, they formed many strategic partnerships, mergers and acquisitions with steel
producers from China, Japan, Europe and other major steelmakers worldwide( see fig. 82).
Besides their strong oligopoly presence on the global iron ore market, in 2009 Rio Tinto
and BHP Billiton have signed a non-binding 50:50 joint venture agreement amounting 116
billion USD, in order to merge their iron ore operations in Western Australia83.The joint
venture was revised by international competition authorities and objected by Worldsteel the
same year, because it was not in interest of the business and public 84. Fortunately, for the
steel producers and the global society, in 2010 the joint venture between Rio Tinto and
BHP was abandoned after the market regulation of the European commission, claiming the
uncompetitive situation in the seaborne iron ore trade where the share of the top three
mining companies was about 70 %, while at the same time the biggest world steel
producing company holds less than 10 % of the world steel production 85.
After introducing the new iron ore price system for the steel producers, which squeezed
their finances in the last years of unstable steel demand due to the effects of the world
financial crisis, recently in August 2012 BHP Billiton placed hostile takeover offer to Rio
Tinto amounting about 150 billion USD86. Rio Tinto is yet rejecting the hostile offer, claiming
81
http://www.arcelormittal.com/corp/who-we-are/our-history
Nestour, Mangers, “ Global Steel – 2010 trends, 2011 outlook. India – next landmark on the global steel
landscape”, Ernst and Young, 2011, p.35-37.
82
83
Sourced from Orbis database, company news for Rio Tinto and BHP Billiton
Worldsteel, press release: http://www.worldsteel.org/media-centre/press-releases/2009/iron-ore-competition.html
85 Worldsteel, press release: http://www.worldsteel.org/media-centre/press-releases/2010/iron-ore-joint-venture.html
86 http://www.abc.net.au/news/2008-08-19/bhp-rio-takeover-bid-may-face-restrictions/481366
84
53
that the proposed deal price does not reflect company’s value and expansion projects87.
Hopefully the international competition regulators will restrict one of the biggest- ever
business takeovers, forming a mining giant, which will influence the global supplies and iron
ore pricing with its dominant monopoly market presence.
In order to illustrate better the market structure in the steel and iron ore industry, we have
exposed figures 77, 78, 79, 80 and 81 from the Annex. We could see from figures 68 and
77, that the world top 10 steel producers have increased their market share between 2006
and 2008 from 26,8 % to 28 %. During the financial crisis their market share dropped in
2009 to 23%, and recovered to 2006- levels in 2011, reaching 27 % from the world steel
production. The world leader in the steelmaking is ArcelorMittal with market share of 23%
or 97,2 mln.t of steel, even though its market share decreased by almost 12% during the
period 2006- 2011. At the same time other top10 world steel producers increased their
market shares with app. 1-2 % annually. Still, the global steel market could be considered
as competitive, as there is no company which holds the majority of the steel market.
Confirmation of the market competition in the steel industry is showed on fig.80, where the
industry concentration index calculated by UNCTAD between 2005 and 2010, was almost
constant with value of app. 0.15. The concentration index is based on the HerfindahlHirschmann index, and since it is closer to zero, shows homogeneous market between
exporters and importers. On fig.81 the Industry structural index for the same period has
increased from 0.14 to 0.20, which shows dynamic in the composition of the exporters and
importers, even though when closer to zero the index signifies of traditional market
structure.
The oligopoly market structure of the iron ore industry is represented on fig.78, 80, 81, 82.
We could see that the big three iron ore producers Vale, BHP, Rio Tinto are representing
the majority of the global seaborne trade with iron ore. Their market share have increased
from 64% in 2004 to 76.5 % in 2010, despite the world financial crisis and the turbulence in
the steel demand. They also represent about 25 % of the iron ore capacity of the top 10
world iron ore suppliers, while all other competitors from top 10 each keep app. 3-5 % of
this iron ore capacity. The industry concentration index for the period 2005 -2010 has risen
from 0.35 to 0.46, which signifies very big and increasing non- homogenous market of
importers and exporters. The industry Change structural index has increase between 2004
and 2009 from 0.17 to 0.26, but dropped in 2010 to 0.23. this reveals certain increased
dynamic in the compositions of exporters and importers till 2009, which decreases in the
next year. Still, the values are near to zero, which shows relatively traditional market
structure. This fluctuation in the structural change index for both industries in 2009- 2010,
might be also a result of the increasing numbers of mergers, acquisitions and other
partnerships between the iron ore and steel companies described in more details below.
We could see some of the major consolidation deals in the recent years in the iron ore and
steel industries on Fig.82. The list consist of different joint ventures, mergers and
acquisition between leading iron ore producers and steel makers, and its aim is to present
approximate picture about the consolidation and integration process between both
industries and leading market players, without ambition to be full and extensive in its
information about the process on the global steel and iron ore markets.
According to Price Waterhouse Coopers, the mergers and acquisition deals in the Metals
and Mining ( big part of which consists of the steel and iron ore industries), have been in
87
http://www.aljazeera.com/business/2008/02/2008525134610888353.html
54
peak during 2006- 2007, but dropped fluctuating downstream after the world financial crisis
from 200888. The mergers and acquisitions in the steel industry are represented in the table
below, showing small peak in the number of the mergers and acquisition deals in 2010 (
160 deals ) after the lower 2009 ( 150 deals), followed by another drop in 2011 with 145
deals. At the same time the value of the steel mergers and acquisition deals have
increased steadily from 7.5 to 11.3 bln. USD for the same period. It is interesting to mention
the global trend of increasing of the cross- border deals in the steel industry – they have
increased both by value and number, while the domestic deals have decreased their
number, but also increased the value of the deals.
Fig.G. Mergers and Acquisitions in the Steel Industry, 2009- 2011
2009
2010
2011
Domestic
Number
115
113
98
Value (US$bn)
6.1
8.2
7.4
Cross border
Number
Value (US$bn)
40
1.4
47
2.5
46
3.9
All deals
Number
Value (US$bn)
155
7.5
160
10.7
145
11.3
Source:Price Waterhouse Coopers
Most of the mergers and acquisitions, as well as joint ventures in the steel industry are
vertical integrations with raw material suppliers from the iron ore or coking coal industries.
Forced mostly by the volatility of the iron ore, the number of the steelmakers looking to
secure their resources supply and control their costs and price volatility, is increasing.
According to Ernst and Young89 in 2010, the volatility in raw material pricing was the main
driver for more than 20 deals of steel makers, targeting acquiring of mining operations like
iron ore and coking coal. They claim that ArcelorMittal is going to invest in iron ore projects,
targeting supply of 100 mln.t of iron ore till 2015, through acquisition of mines or joint
ventures. Searching to establish strategies to increase their bargaining power in negotiation
with raw material suppliers, the Chinese Government plans to consolidate the steel industry
in China. The proposed merger of Nippon steel and Sumitomo Metals in Japan is probably
going to create the second largest steelmaker in the world. The initiators are hoping to
decrease the number of market players, and increase their bargaining power in negotiating
iron ore prices.
The mergers and acquisitions in the iron ore industry are also among the top metals deals,
according to Price Waterhouse Coopers90. The iron ore M&A deals value as share from the
metal deals have increased from 4 % in 2007, to 57 % in 2010. In 2010, the cross- border
and cross- continental M&A metals deals have increased by 46 % on y-o-y basis, focusing
88
Jim Forbes, Metals Deals Forging ahead, 2012 Outlook and 2011 Review, p. 9
Nestour, Mangers, “ Global Steel – 2010 trends, 2011 outlook. India – next landmark on the global steel landscape”,
Ernst and Young, 2011, p.35-37.
90 Price Waterhouse Coopers, “Metals Deals Forging ahead 2010 Annual Review”, 2011
89
55
on optimizing the business production, distribution, raw material supply, and market
presence on the emerging markets. In the beginning of 2012, one of the biggest iron ore
supplier Glencore, agreed to buy its competitor Xstrata for 62 bln. USD, which is
considered to be the biggest mining takeover. According to study of KPMG done shortly
after the takeover, one of every three mining companies is planning to expand through
mergers and acquisitions in the next 1-2 years91. Confirmation for such intentions is the
hostile takeover made by mining leaders BHP to Rio Tinto in August 2012, which is not
accepted yet, and might be a subject of market restriction.
Regionally the mergers and acquisition deals are gravitating around Asia and the Pacific
area, since China, India and Korea are the perspective global steel markets, and Australia
is concentrating major iron ore resources in the world. Another region of interest for
mergers and acquisitions is Brazil and partially North America. Brazil is also a major iron
ore supplier trying to integrate and diversify its business, while in USA the miners are trying
to integrate vertically.( KPMG9293). EU stays uncertain market with the current financial
crisis, which further depending on the financial development of the steel makers, could
proceed to market consolidation.
Most of the M&A consultants suggest that in the near future, we will be witnessing some of
the biggest mega- deals of mergers and acquisitions, especially in the iron ore and steel
industries. Consultants from Price Waterhouse Cooper are expecting that those megadeals will be fueled by the strong commodity prices94. At the same time the global financial
crisis could stop many mergers and acquisition deals, making them too expensive with the
increasing of the commodity prices. Leading regions for mergers and acquisitions in the
steel and iron ore industry will continue to be Asia, and especially China and India.
4.3.Analysis of the profits and revenues of the companies from the iron ore and steel
industries
Besides the changes in the global market structure, the change in the company’s finances
is another effect of the consolidation process in the iron ore and steel industries worldwide.
On fig.83,84,85,86,. we have exposed information about the Profit Margin % and the
Operating revenue ( Turnover in th. USD) of selected companies from the iron ore and
steel business. The data is sourced from Orbis database, and the companies are filtered
according to the code of their business activity, additionally checked according to the rating
lists of the steel and iron ore companies available. The smallest companies which fall
outside of the rating list are checked for their business activity through their websites. We
have filtered top 100 companies from both iron ore and steel industries, using for the steel
business activity codes 2452 – Casting of Steel and , 2410 - Manufacture of basic iron and
steel and of ferro-alloys. For the top 100 companies from the iron ore business, we have
selected companies with codes 0710 – Mining of Iron ores. In addition, some companies
which are forming the main market structure in both industries, are classified in this list
even if they fall outside of these activity codes lists. The main idea of this analysis is, to
get an idea about the distribution of the profits and revenues among the biggest,
91
http://resourceinvestingnews.com/32454-mining-companies-poised-for-mergers-and-acquisitions-kpmg-study-showsglencore-xstrata-bhp-rio-tinto.html
92
Jim Forbes, Metals Deals Forging ahead, 2012 Outlook and 2011 Review.
Price Waterhouse Coopers, “Metals Deals Forging ahead 2010 Annual Review”, 2011
94 http://www.reuters.com/article/2011/03/03/us-pdac-pwc-idUSTRE7220XI20110303
93
56
middle- sized and the smallest companies, from the steel and the iron ore business,
capturing small samples from the whole market structure of both industries,
considering the different levels of their market concentration. We also would like to
understand, if there is a serious deterioration of the profits of the steel companies,
following the parallel process of market consolidation, and the implementation of the
new price system for iron ore, which represents major cost share for the steel
production.
We want to prove, that there is a redistribution of the profits and revenues from the
steel towards the iron ore companies, which creates financial conditions for future
consolidation process between both industries. Besides that, we want to prove that
the biggest winners from both the market consolidation process, and the new price
system for iron ore, are the oligopoly leaders of the iron ore industry. We want to
outline also, their increased profitability, which should not cause additional big
increases of investment and exploration costs for iron ore, which were blamed by
them to be the main reason for the increasing of the iron ore prices.
In the first analysis, we have used selected company’s data from Orbis database for
certain steel and iron ore companies. The results from the analysis are represented on
fig.83,84,85,86. We have selected the top 100 iron ore and steel companies, and
distributed them according to their revenues from the biggest to the smallest. Having in
mind the difference in the market concentration and revenue amounts between the iron ore
and steel industries, we have selected from the list of each industry, companies from the
top, middle and end of the lists. For the Iron ore industry we have selected 3 companies
from each of the ranges, and for the Steel industry- 5 companies from each range, so that
the different ranges in both industries could be more comparable according to their
revenues volumes. In advance was also checked the financial data availability of the
companies, in order to have better data for the analysis. More detailed analysis of the
profits and revenues of the companies from the iron ore and steel business have been
conducted, using Linear regression and SPSS for the selected sample. Linear regressions
of the profits and revenues of all 24 companies was conducted and the results have been
analyzed combined for the iron ore and steel industries on figure 86a.
In addition another statistical analysis with linear regressions using for all top 150 steel and
iron ore producers was conducted, using data and limited statistical options of the Orbis
database. The companies selected for the linear regression are 150 for both industries with
the same activity codes, as in the previous analysis, ordered again according to their
revenues. The difference is, that due to the limited time, we couldn’t check the availability of
financial data for each company, as in the previous analysis, and have more missing data
in this second analysis. Still, the results from both analysis are giving similar results, which
confirms the major trends for distribution of profits and revenues across both industries. We
have conducted linear regressions using the profit margins %, and the revenues in th.USD
for all selected companies, separately for each year from the period 2002-2011. The results
with outputs are represented on figures 87- 98 from the Annex95.
From the analysis on fig.83 we could see, that the average turnover of the steel producers
for the period 2002 – 2011 was 17 844 601 th.USD, which is bigger than the one of the
iron ore producers – 13 927475 th.USD. At the same time, for the same period, the
dynamic of the increase of the turnover between both groups is different. The average
turnover of the selected iron ore producers in 2002 was 4 250 491 th.USD, but have
95
The statistical outputs from fig.89 and 90, are given as a file, copied on a CD
57
increased by 707 % till 2011, reaching 30 044 001 th.USD. The dynamic of the increase of
the turnover of the steel producers was about half of the one of the iron ore producers.
Their average turnover in 2002 was 8 215 148 th.USD, while in 2011 have increased by
345 %, to 28 308 268 th.USD. The Annual average increase of the average turnover for the
selected group of companies was 402%. Six out of nine of the selected iron ore
producers ( 66%) , and five out of fifteen of the steel producers ( 33%) have
increased their turnovers above the average for the selected group. Two of the world
top three iron ore producers ( Rio Tinto and Vale ), and two of the world top five of
the steel producers ( POSCO and Baoshan Iron and Steel), are among the companies
with highest increase of the revenue. For the period 2002- 2011, Rio Tinto have
increased its revenue by 717 % , while Vale have increased its revenue by 1393%.
The increase of the revenues of the steel producers POSCO and Baoshan Iron and
Steel is lower, compared to those of the iron ore producers, it is respectively 495% (
2002- 2011), and 661% ( 2003- 2011).
The left 33% of the selected iron ore producers ( BHP Billiton, Shanghai Meishan Mining
and Resurgere Mines and Minerals),have increased their revenues below the average for
the selected group, respectively by 319 %, 223%, and 384 %. The other ten steel
producing companies ( 66 % from the sample of the steel producers), have also
increased their revenues below the average for the sample. Among those companies
are some of the top 10 world steel producers like ArcelorMIttal, Nippon Steel and
JFE, with increase of their revenues respectively 355%, 255%, and 190%.
The Analysis of the Margin profits distribution of our sample, consisting of 15 big,
middle -sized and small companies, from the steel and iron ore industry is shown of fig. 84.
The results are confirming that, that the average profit of the steel producers for the
period 2002 – 2011 is 8.48%, which is less than half of those of the iron ore
producers – 20.11%. Besides that, for the same period, the dynamic of the increase
of the margin profit% between both groups, is again in favor of the iron ore
producers. The average profit margin % of the selected iron ore producers in 2002 was
9.02%, and have increased by 0.27 % till 2011, reaching 9.29%. The dynamic of the
increase of the profit margin % of the steel producers during the period 2002- 2011, was
between 30 % and 100% lower, than those of the iron ore producers ( see fig. 84) Their
average profit margin % in 2002 was 0.41%, while in 2011 have increased by 3.07 %,
reaching 3.48%, which is only about one third of the profit of the iron ore miners.
The Annual average increase of the average profit margin % for the selected sample
group of companies was 5.53 %. It is interesting to outline that, many companies are
showing also negative increase of their profits. Among them, four are iron ore
mining companies ( 44% from all the iron ore companies in the sample), and six steel companies ( 40 % from all steel companies included in the sample). The iron
ore companies with negative profit margin increase are in general companies with smaller
revenues. The mines Resurgere Mines and Minerals India, Sinosteel Australia, Laiwu
Steel and Mining and Shanghai Meishan mining have decreased their profits respectively
by 32.38 %, 4.39%,14.46, and 0.15%. Among the selected steel companies with
negative increase of their margin profits are some top steel producers like POSCO,
Baoshan Iron and Steel, Magnitogorsk Iron and Steel, and Metinvest. Their profits
have decreased respectively by 3.56 %, 18.30%, 11.29%, and 7.07%.
Four out of nine of the selected iron ore producers ( 44%) , and four one out of
fifteen of the steel producers ( 27%) have increased their profit margins above the
average for the selected group. Among the companies with highest increase of
58
margin profits are four iron ore producers ( 44% from the sample of the iron ore
producers, including the big three leaders BHP, Vale and Rio Tinto), and four steel
companies with smaller revenues ( 27% from the group of the steel companies
selected). The big three iron ore leaders Vale, BHP Billiton and Rio Tinto have
increased their profits by 36.77%, 20.64%, and 6.28%. The increase of the profits of
the steel producers was comparatively lower to those of the iron ore producers .
Sumitomo Metals Industries, Ezz Steel, and Kobe Steel increased their profit
margins respectively 5.79%, 14.87%, and 7.40%.
Only one iron ore company (11 % from the selected mining companies), have
increased their margin profits below the average for the selected group. The profit
margin of Zhenjing Weigang Iron Mine between 2002 and 2009, have increased by 4.88%.
Other five of the steel producing companies ( 33 % from the selected steel
producers), have also increased their profit margins below the average for the
sample. Among those companies are some of the top 10 world steel producers like
ArcelorMittal, Nippon Steel and JFE. They have increased their profits margins
respectively by 6.41%, 6.33%, and 8.74%.
Additional information about the time-line dynamic of the revenues and margin
profits of the iron ore and steel producers is represented on fig. 85 and 86. We could
see that the average revenue for both industries was increasing in similar trends
between 2002 and 2008. The percentage increase of the revenues was 384% for the iron
ore industry (16,359,835 th. USD in 2008), and 310 % for the steel producers (25,482,224
th.USD in 2008). Later in 2008 with the start of the financial crisis, the revenues in
both industries dropped significantly about 80 %. On the next year with the official
implementation of IODEX 62 and the new quarterly –based price system for iron ore,
the revenues of the miners jumped by 232%, while those of the steelmakers- only by
109%. After the big wave of mergers and acquisition in 2010 between the iron ore
and steel industries, their revenues in 2011 have adjusted to similar levels of about
28 -30 000 000 th.USD.
The profit margins showed similar dynamic to those of the revenues, but preceding
the decreasing trend from the financial crisis with two years. The profit margins of
both iron ore and steel producers were increasing steadily till 2006. Steel producers
profits raised by 15.64% from 0.41% in 2002, reaching 26.05% in 2006. Similarly, the
profits of iron ore miners increased a bit faster by 18.7%, reaching in 2006 profit margin
level of 27.79%. Later, with the financial crisis, the profit margins in both industries
collapsed by app. 14% till 2009, reaching levels of 2.76% and 12,78% for the steel and
iron ore industries respectively. With the official implementation of the new iron ore
pricing system and the wave of many consolidation deals, the profits of the iron ore
miners in 2010 reached high average levels of 33%, while the steel producers
increased their profits only to 3.10%. Serious downward adjustments of the profits of
the iron ore miners followed in 2011, when they reached much lower level of 9%.
Still, this profit is about three times more than the profits of the steelmakers for the
same year of 3.48%.
We have also conducted statistical analysis in SPSS with the preselected sample of 15
steel and 9 iron ore producers. We wanted to understand if there is a trend of increase
of the profits of the companies, with the increase of their revenues, and what are the
trends among those two groups of companies. We conducted Linear regressions for all
the companies data in the sample, using as dependent variable their Profit Margins%, and
as independent variable- their Revenues, in th. USD. The data for most of the companies
59
was available for the period 2002- 2011. There are some companies which miss values for
some of the years. The combined results from all regressions are showed on fig.68a 96. We
have assumed in advance that we might have insignificant results from the analysis,
because of the preselected and small sample, as well as because of the small number of
yearly data, or missing values. Still, we wanted to see if the relationship between the
profits and revenues are positive or negative, and for which industry is the trend
more significant. On Fig. 68a , all companies are ordered according to their Pearson
correlation coefficients – from the largest, to the smallest. The first thing we could notice,
is that the companies with greatest positive correlation between their profits and
revenues, are the iron ore companies, and some steel companies with positive
profits above the average for the selected sample : 5.53% ( see fig.84, and notes
below fig.68a). On the bottom of the table with negative correlation between their
profits and revenues, we have predominantly steel companies with negative average
profits. The Pearson correlation for most of the regressions are not significant at
0.05 level, but still some of the top positive and the top negative correlations are
significant.
The miner Olenogorskii Gornoobogatitelnyi Kombinat (OGK) is showing the largest value of
the Pearson correlation coefficient of 0.863, with significance 0.001, showing very strong
relationship between the profits and revenues, which falls under the significant level of
0.05. The next two iron ore companies with positive correlation coefficients, and significant
levels, are two of the biggest world iron ore suppliers - Vale and BHP Billiton. Their
correlation coefficients are 0.722 ( Vale), and 0.695 ( BHP Billiton), with significance values
respectively – 0.009 and 0.019, and R-square values are 0.722 and 0.695. The last, fourth
iron ore company with significant positive correlation coefficient is Zhenjing Weigang Mine
Co. Its Pearson correlation value is 0.672, at significant level 0.034, and R-squared 0.451.
Summarizing the results for the iron ore companies, we could say that 44.5% from all
preselected miners, including two of the top leaders, are showing average very
strong positive relationship between their profits and revenues ( average Pearson
correlation of app.74%), and on average 55% (R- sqares) of the variance in their
increasing profits, could be explained by percentage increase in their revenues.
The iron ore company with the lowest , negative and insignificant Pearson correlation in
the table, is Resurgere Mines and Minerals India. Its correlation coefficient value is
- 0.799, and the significance level: 0.052. The coefficient of determination R-squared is
0.638. This could mean that in the worst case, there is an insignificant probability,
that the profits of the iron ore companies would change negatively by 63.8%, with
percentage increase of their revenues.
Analyzing the steel producers, we could see that the company with the best possible
positive, but insignificant correlation coefficient is EZZ Steel Company. Its Pearson
correlation value is 0.550, with significance 0.063, shows mid- strength between the
dependent and the independent variables, which falls out of the confidence interval 0.05.
The coefficient of determination R squared is 0.302. We could say that the best chance
for a steel company to increase its profit with 30.2%, with every percentage increase
of its revenue, is insignificant.
At the same time, the only significant Pearson correlation results for steel companies
in our sample, are negative. At the bottom of the table with the regression results, we
could see that Novolipetski MK and Baoshan Iron and Steel are presenting Pearson
96
Note: The original outputs from the SPSS Linear regressions are copied on a CD.
60
correlation values of - 0.862 ( NLMK), and – 0.919 ( Baoshan), at significant levels
respectively 0.001 and 0.000. The coefficient of determination of NLMK is 0.743, and for
Baoshan is 0.844. We, could summarize that 13% of the steel companies in our
sample, including one of the world top steel producers ( Baoshan Iron and Steel), are
showing significant negative relationship ( app. 89%) between their profits and
revenues. On average 79.4% (R- sqares) of the variance in the decrease of their
profits, could be explained by percentage increase in their revenues.
From the analysis above, we could conclude that 44% from the selected iron ore
companies are showing strong significant positive relationship between their profits
and revenues, while 13 % of the steel producing companies are showing strong and
significant negative relationship between their profits and revenues. In general, we
could consider, that with the increasing of their revenues, the iron ore companies
are increasing their profits much more than the steel companies, and there is a trend
among the steelmakers to decrease their profits, no matter from the increase of their
revenues.
In addition to the previous analysis of profit margins and revenues of selected top, middlesized and smaller companies from the top 100 iron ore and the steel industries, giving the
majority of the market structure, we have used the software option for Linear regression in
Orbis database to confirm our results with bigger sample. The sample size consisted of
financial data for 150 companies from both industries, and our aim was to get
approximately the full size of our initial list of top 100 companies from the previous analysis,
considering the probability to get many missing values. The Linear regression analysis in
Orbis is not giving all the details for analysis like other professional statistical software
programs, but still could help us to confirm or reject the results from the first analysis with
the smaller sample. The reason we didn’t run this analysis in SPSS, was that it requires a
lot of time to source and clean the data from Orbis, which was not within our time- limits.
The results from the Linear regression analysis are given in the Annex, from figure 87 to
figure 98. On figure 87, we could see the results for the correlation coefficient, median,
standard deviation, average and the sample size, from the linear regression run for the
steel producers, where our dependent variable was the profit margin %, and the predictor
was the revenue in th.USD.. First we could see that our sample size for all the years, for
which we run the linear regression ( 2002- 2011), have minimum about 30% missing
values, and for 2011 the missing values are reaching about 50% from the sample size. This
could mean, that our results might miss some reliability, especially for year 2011, but still
we have available data for about 70 % of the samples for all the years, which is a good
basis for analysis. The results for the median, average and the standard deviation for both
variables, are given also graphically on fig. 92 and 94. We could see that the standard
deviation, median and average of the revenues of the steel producers are following the
same trend, but the amplitude between them increases with the time, which might suggest
increasing dispersion of the revenues. Serious are the difference in the fluctuations in the
profits of the steel producers, exposed on fig.94. While the median and the average of the
profits are sharply decreasing between 2010- 2011, the standard deviation is keeping and
even increasing its trend, which lowers the possibility for prediction of a model, including
the profit margin. The correlation coefficient between the Profit margin% and the Revenue
of the steel producers is fluctuating between negative and positive during 2002- 2011 ( see
fig.87, 95), but is predominantly negative, with average value of the correlation for the
analyzed period of - 0.034. This means, that the profit margin of the steel producers is
not strongly correlated with their revenues. The profit margin would decrease only
61
by 3.4 %, with the increase of the revenue. Looking at the residuals on fig.89, we could
confirm that only few companies with the biggest revenues are following the linear
regression and calculated correlation between their profit margins. The companies
with smaller revenues, are maybe following another correlation, which might be analyzed
with different sample of companies and professional software. In addition, the distribution
of the profit margins of the steel producers between 2003 and 2011 shown on fig. 97,
are confirming lack of normal distribution of the profits. With the time, we could see
that the revenues of most of the steel companies are increasing, but especially those from
the top 25 %. The upper limit of their profits increases from 35.5% in 2003, to 100% for
some companies in 2011. The lowest 25 % from the steel producers are decreasing their
negative profits from -26% in 2003, to -12 % in 2011. At the same time 50 % of the steel
companies in the group are decreasing their average profit range from 2.53 – 12.48%
in 2003, to -0.35 / 5.57% in 2011. In general, we could say that the consolidation in the
steel industry, the size of the sample, the missing values, as well as the effect of the
financial crisis and other industry changes the new iron ore price system, are among the
main reasons, which are causing inconclusive results from the linear regression. The most
important result from this analysis, is the negative sign of the correlation between
the Profit margin and the Revenues of the steel companies, which confirms the
results from the previous analysis with the smaller preselected sample of
companies.
The results from the linear regression between the Profit margin and the Revenues of
the top 150 iron ore mining companies is represented on fig. 88, 90, 91, 93, 95, 96 and
98. Our sample size consist of 150 iron ore companies for all the years, for which we run
the linear regression ( 2002- 2011). We have app. 30% missing values between 20032009, around 50 % missing values for 2002- 2003, and about 68% missing values for 20102011. This could be a reason, for our results not to be very reliable, especially for years
2002-2003, and 2010- 2011. Still, we might consider the results for 2004-2009, as more
reliable, since they have only about 30% missing values, as we considered in the analysis
of the steel companies.
The results for the median, average and the standard deviation of the profits and revenues
of the iron ore miners are represented graphically on fig. 91 and 93. The standard
deviation, median and average of the revenues of the iron ore producers are
following similar patterns till 2007, but the amplitude between them increases a lot
afterwards, and the dispersion raises by more than 600% between 2002 and 2011.
This could suggest big increase of the variance of the revenues of the iron ore
producers, and could be a reason for inconclusive results from the analysis.
Serious are also the fluctuations of the profits of the iron ore producers, exposed on
fig.93 The median and the average of the profits are sharply dropping in 2009 , and
raising more than double in 2010- 2011. At the same time, the pattern of the standard
deviation is comparatively more stable, following normal distribution trend between 2004
and 2011, and facilitates the prediction of the model.
The correlation coefficient between the Profit margin% and the Revenue of the iron ore
producers, is fluctuating with decreasing trend, but stays predominantly positive
during 2002- 2011, showing negative value only during the financial crisis from 2008
( see fig.88, 95). The average correlation coefficient for the iron ore producers fro
this period is 0.0881, which suggests slight positive relationship between the profits
and revenues of the miners. The result could mean that profit would increase by
8.8% with percentage increase of the revenue.
62
Looking at the residuals on fig.90, we could confirm that only few companies with the
biggest revenues are following the linear regression and calculated correlation
between their profit margins. The other companies with smaller revenues, are
clustered in a more concentrated group, than those of the steel companie ( fig.89),
which reflects the difference in the concentration between both industries. The
results might suggest that it is more appropriate to use smaller and random sample of
companies, instead of full list of top 100 or 150 companies. That’s why the results from the
previous analysis with the smaller preselected sample could be useful.
In addition, we could see the distribution of the profit margins of the iron ore producers
between 2003 and 2011 on fig. 96, which are confirming lack of normal distribution of
the profits. With the time, we could see that the revenues of most of the iron ore
companies are increasing, but especially those from the top 25 %. The upper limit of their
profits increases from 44.35% in 2003, to 100% for some companies in 2011. On the
opposite, the lowest 25 % from the iron ore producers are increasing their negative profits
from -5.60 % in 2003, to -39 % in 2011. At the same time 50 % of the iron ore
companies in the group are increasing their average profit range from 3.03 – 14.13%
in 2003, to 21.48 – 52.70 % in 2011.
If we summarize the results from this analysis of based on bigger sample, with the
results from the previous analysis with the smaller sample, we could say that results
are confirming the major trends and their directions for both industries. Outlined is
comparatively strong positive relationship between the margin profit and the
revenue of the iron ore producers, including two of the biggest world suppliers- Vale
and BHP Billinton, which showed strong positive trend in this relationship. The
results from the smaller sample are showing stronger positive relationship, compared to the
second analysis, but it is understandable, having in mind the big concentration on the iron
ore market and the difference in the sizes of the samples. The trend of increasing the the
positive relationship between the company’s profits and revenues, is more common
for the iron ore industry, than for the steel industry. In general, the iron ore
companies are having higher levels of profits than the steel companies, reaching
200- 300 % and more percentage difference. The majority of the steel producing
companies are showing slightly negative relationship between their profit margins
and revenues, which suggest slow deterioration of their business. The trend is found
to be very strong and significant for one of the top three world steel producersBaoshan Iron and Steel.
The outlined process of deterioration of the profits and revenues of the steel
producers, and the increasing profits of the iron ore miners, is additional financial
reason for increasing the volume of the consolidation process between both
industries, through mergers, acquisitions and joint ventures. This would increase
even more the market concentration, and together with the new pricing system for
iron ore, the bargaining power of the oligopoly players from the iron ore industry
soon could gain enormous global strength. Such situation could lead eventually, to
additional increase of iron ore and steel prices, which would affect the volatility of
prices of all other related industries using steel products.
63
5. History of the change in the iron ore pricing system, and the implementation of the
iron ore price indices for spot trading
The old price system for iron ore was running over more than 40 years until 2010. The
prices for delivery of iron ore from the miners to the steelmakers, were determined
annually with frame- type contracts, arranged usually around March- April. The
contract iron ore prices were determined according to different factors:
- Specific iron ore content (grade) of the material from certain ore deposit
- Processed level of the iron ore - size of the particles ( lumps, pellets, fines)
- Quantity negotiated for delivery
- Moisture content
- Contaminants in the ore, like Alumina and Silica
- Other metallurgical properties
- Geographical location
- Terms of trade according to Incoterms, conditions of payment and etc.
The prices for iron ore are usually specified in Dry metric tons, or dry long tones in USD,
after subtracting the moisture content per ton with formula. Iron ore lumps were historically
traded at higher prices than the sinter feed, since they are more efficient as direct feed to
blast furnaces in the steelmaking. Iron ore concentrates are typically traded at levels near
to the sinter feed, while the pellets are traded at highest price, reflecting their higher
efficiency in the steelmaking process.97 The difference in the efficiency of the different
types of iron ore, is reflected in their “Value-in– use” (VIU) which shows additional
value for the steelmakers, usually above the market price of the raw material. The
difference in the VIU of different grades iron ore, their sizes and other specifications, are
determining certain premiums or discounts in the iron ore prices.
The increased volatility on the global market, was a reason for many of the leading iron
ore and steel companies, to change their financial and risk management strategy, by
starting derivative trade with market risk factors, that affected their resultsexchange rates, commodity prices, interest rates like LIBOR. Such new market
strategy, targeted to measure and manage the market risk, was also adopted by the global
leader in the iron ore industry Vale, since December 200098. Followed by the iron ore
import from China, which have increased 4.5 times from 2002 to 2008, there was a
revolutionary price hike of all mineral resources, called “The Paradigm Shift”. The
enormous soaring of the iron ore and steel prices reached all- time high levels in June
200899. Later, in September 2008 Leman Brothers bankruptcy caused on the global market
“The Leman Shock”, which collapsed the prices of all metals and mineral resources after
the failures on the derivative market. The followed world financial crisis in 2008- 2009, was
a reason for many steelmakers worldwide to stop or decrease their production volumes. In
Europe and China, some of them, have stopped sending vessels for delivery of contractual
iron ore, because the spot prices for iron ore fell down below the contractual prices
97
Annual report Vale, 2001, p .55, 78
http://nyse.10kwizard.com/cgi/image?&ipage=1588314&doc=41&fdl=1&odef=8&dn=2&quest=1&rid=23
99
TEX annual report, Iron ore, 2009, p 89- 90
64
(PLATTS100). In June 2009, BHP Billiton and Rio Tinto (two of the Big 3 market
leaders on the iron ore market), forced by the reduced annual sales ( -24% for Rio
Tinto, and -51 % for BHP in 2008- 2009101) , caused by the collapsed market, and the
financial crisis, have signed a non- binding agreement for creating of joint venture
company, in order to reduce their costs and optimize the growth of both companies.
The joint venture was planned to be established by the second half of 2010, and the
decision was reconsidered by the market regulatory institutions for almost a year. During
that time, the spot prices for iron ore droved by the demand from China, rose beyond
the contract prices, and the steelmakers returned back on the market, asking for iron
ore on contractual prices. At that moment, the miners pushed to price contracts,
based on information for spot iron ore prices, coming from information bulletins like
PLATTS. In 2010 the joint venture between Rio Tinto and BHP was abandoned, after the
market regulation decision of the European commission, claiming the forming of highly
concentrated and uncompetitive situation in the seaborne iron ore trade, between the iron
ore producers and the steelmakers.
The failing of the joint venture between the market leaders, was in parallel process
with the first structural changes in the iron ore pricing introduced in early 2010. Steel
makers agreed to the demands of the leading iron ore miners, to exchange the annual price
negotiations with semi-annual and quarterly contracts, based on the average spot
quotations for the previous periods ( Ernst and Young102). In 2011 some of the steelmakers
and iron ore miners, have proceeded even to quarterly pricing, based on the spot quotes
from the current quarter’s three-month average price indices, and others - using the
monthly average of the spot price indices (Vale103).
The new price method, and the tight iron ore supply, under conditions of fast
increasing demand from China, gave additional bargaining power of the iron ore
miners. In June 2010, they have increased the iron ore prices for iron ore 62% FOB
Australia to 120- 140 USD/Dmt , which represented increase of 88-92% on yearly basis.
The increased volatility of the iron ore and other raw materials, have caused reform
also in the pricing of the steel. The steel makers included and index- based raw material
surcharge in their price formula, and most of them reduced the terms of their frame
contracts, to semi- annual and quarterly –based.
The major iron ore spot price index IODEX62 used for negotiations on the physical market,
is quoted by the leading information agency in the raw materials and mining business PLATTS. The agency is quoting variety of price indices, related with the raw materials and
mining, which are traded for years on the financial market and used as benchmarks for
physical trade worldwide. The quoting of IODEX62 was preceded by the collapse of the
world derivative market, and decreasing of all prices of raw materials and metals in 20082009. Looking for new options to help improving of the investment portfolios of its
customers from the financial market, PLATTS have introduced officially the quoting of its
new iron ore spot price index IODEX62 in June 2008. In parallel with the invention of
IODEX62, many other spot and term – based iron ore indices started quoting and
developing derivative trade worldwide – TSI ( The Steel index), MBIO ( Metal Bulletin),
Keith Tan,” Evolution of Iron Ore Pricing: A Review of Methodology, Prices”, Platts Steel & Raw Materials Forum
Singapore, 2011
101
TEX annual report, Iron ore, 2009, p.102
102 Nestour, Mangers, “ Global Steel – 2010 trends, 2011 outlook. India – next landmark on the global steel landscape”,
Ernst and Young, 2011, p.35-37.
103 Annual Report Vale, 2011, p.19
100
65
SGX ( Asiaclear), SIOTA ( Globalore), and others. Most of the index quotes for iron ore, are
following the standard specification and terms of the quoted by PLATTS, TSI and Metal
Bulletin. Besides that, many other new price indices for OTC derivative trade were
invented, related with other raw materials for the steel production, and the steel products
themselves – coking coal, coke, steel billets, hot rolled coils, reinforcing steel and etc. This
way the financial markets with the help of the information agencies, after the collapse of the
derivative market in 2008, have created new platform for derivative trade, based on the iron
ore and steel industries, and impacted the volatility of the iron ore and steel prices through
intensified market and information activity.
The standard specification of the spot iron ore price index IODEX62 is as follows104105106:
- Iron content 62%, Premium per 1% Fe content differential
- Contaminants in the ore : Moisture: 8.00%, Silicon Dioxide: 4.50%, Aluminum
Dioxide: 2.00%, Phosphorus: 0.075%, Sulphur: 0.02%.
- Impurities normalization: Cargoes of iron ore fines with greater levels of impurity
- than these standards, is normalized to the 62% standard, using prevailing market
values for each impurity under value-in-use economics.
- No specific origin or iron ore depot
- Size of fines: Granular size of up to 10 mm for up to 90% of the cargo.
- Minimum quantity of cargo: 35 000 Dmt
- Delivery : CFR Qingdao, North China
- Quoting: daily, in Dry metric tones/USD
- Price derivation: Journalistic basis, accessing information about market deals, bid,
offers both on the physical and financial markets, logistic issues, and other
competitors and market information.
- Payment: Letter of Credit at sight
As, we could understand, by comparing the exposed conditions of trade from the era
of the annual pricing, and of the spot- index pricing, there are a lot of differences.
The major and most important difference is, that the new index pricing is based on
unified product specification that doesn’t really exist. IODEX62 and any other index
prices, are standardized contracts for trade on specific terms of technical
specification, payment, freight, size of the cargo, and no certain origin. Besides, the
assessment process is based on assessments both from the real and financial markets,
as well as information gathered by journalists, which might be manipulated no matter of
their professionalism. We should outline again, that the derivative trade is not related with
real delivery of any material, and uses market information, only to fix the bid and call offers,
and deal settlements, which are also requiring minimum margin spreads per tone, and
taxes for each deal paid to the trade platform. It is in the interest of financial market players,
to increase the bid prices with any information sourced about the market. The inclusion of
the market information from the derivative trade, is not appropriate practice for quoting
prices for real deliveries, because could manipulate the market price. Other practical
problems with the use of IODEX62, are the so called “normalizations” of the cargo, or
the re- calculations of the differentials in the Value- in –Use for certain grades, which
differ to larger extent from the specification of IODEX62. There are new proposals for
premium differentials in the contents of the Alumina in Silica, and other impurities, which
104
105
Freight Investor Services, “Iron Ore Swaps Trading Overview”, 2009
PLATTS, “Methodology and specification guide for Iron ore”, March 2012
106
Keith Tan,” Evolution of Iron Ore Pricing: A Review of Methodology, Prices”, Platts Steel & Raw Materials Forum
Singapore, 2011
66
would facilitate finding the right correlation with the specifications of different cargos of iron
ore. Regarding the size of the cargo, ideas for new premiums or price indices are
proposed, which should involve on the financial market also the iron ore lumps and
pellets. We would also outline, that the information about the freights, is partially also
sourced by estimates from the derivative market for freights, which might include some
price manipulation element. In addition, there are practical problems to recalculate
precisely the freight differences for certain tonnage of cargo, to certain port, when
using the standards of IODEX62, based on CFR China for cargo of 35000 Dmt. Those
differentials are sometimes neglected by the business, and are also causing higher price
volatility of iron ore prices. Last, but not least, there is no certain information about how to
compare the taxes for different terms of payment, which are also included in the quoted
iron ore prices. Or at least, there is need of information about the bank costs of Letters of
Credit at sight in China- fixed in IODEX62 terms, which might be compared with the ones,
for trade in other parts of the world.
We could understand how the imposed use of the spot price index IODEX62, has caused
many problems, mainly for the steelmakers. The decreasing of the periods of
negotiation of iron ore prices from annual to quarterly and even monthly, based on a
disputable iron ore price index like IODEX62, is only increasing the market uncertainties,
and the bargaining power of the iron ore miners. In such market situation, there is no
other way, but to increase the volatility of the iron ore prices, which are depending
even more on the sport prices and the derivative trade, than on the decisions of the
representatives of the steelmakers and iron ore miners.
Due to the increased bargaining power on the iron ore producers, the steelmakers have
adopted different strategies to increase their bargaining power with both their
suppliers of raw materials, and their customers (Ernst and Young107). In Germany
ThyssenKrupp have established joined raw materials procurement agency for the
steelmakers. In China the Government has initiated consolidation policy towards the
national steel industry, using the help of CISA ( The Chinese Steel and Iron
Association). The idea is, to transfer the iron ore price negotiations to smaller number of
individuals and companies, in order to increase the bargaining power of the steel
companies. Besides that, China is increasing its own iron ore production, as well as iron
ore investments and partnerships overseas. In Japan is expected consolidation of two
of the biggest steel producers – Nippon Steel and Sumitomo, which would ease the
bargaining power of the Japanese steelmakers. The integration between the
steelmakers and the iron ore producers through mergers, acquisitions, and other
types of investments, is also very popular strategy in the last decade. This way the
steelmakers are providing raw materials at lower cost, and the iron ore producers, are
receiving higher price added value, and secure profits from the increasing steel prices.
In the new era after the first publishing of IODEX62, and the financial crisis from 2008, the
financial markets are developing in parallel with the iron ore and the steel business. The
industry information leaders like Platts, TSI, Steel Business Briefing, and many
others pushed strong efforts to make popular the new iron ore, coking coal and steel
based derivatives to the wide public in the steel and iron ore industries, organizing
many seminars, conferences, and educations on how to trade with the new derivatives. In
addition in 2011 the leader among the industry information agencies for the steel
107
Nestour, Mangers, “ Global Steel – 2010 trends, 2011 outlook. India – next landmark on the global steel landscape”,
Ernst and Young, 2011, p.35-37.
67
business – Steel Business Briefing, and the information leader on the market of
mining, metals and minerals- PLATTS, have merged together, forming a global
information leader for the market of metals, material and resources, monopolizing
the market information and price quotation, fueling both the real and the financial
markets.
Shortly after the implementation of the IODEX62, have been formed also a special
association for iron ore and steel derivatives ( IOSDA), where the main members are
companies and representatives of the financial market, major information agencies
from the industry, as well as some of the top iron ore and steel producers in the
world. According to the chairman of IOSDA , the quarterly pricing of iron ore is too
inflexible to reflect the real prices of the physical spot delivery, and urges the steel and iron
ore producers to use iron ore and freight short- term derivatives, and even post- benchmark
market to hedge their price risk. He also outlined, that the hedging of the price risk requires
“ much greater use of cleared iron ore swaps”, meaning that the market could exist only if
there are more participants, who could absorb the price risk, which some other traders
would like to hedge. The following statement is also exposing his idea about the main
function of the iron ore swap trading, which is advertized in order to be used on the
financial market: “ The important point to remember about using cleared iron ore
swap, is that you might call the market wrong, but you will always get paid, as
clearing covers the risk of counterparty default.”108. This statement reveals the
irresponsible behavior towards the market price manipulation on the financial market, which
is further partially transferred in the quotes of the iron ore price indices, quoted by the
industry information agencies. It looks like, the idea about the iron ore swap trading is
considered as profitable also by group of leading iron ore and steel producers (
Vale, BHP, Rio Tinto, Baosteel, Hunan Valin, Glencore) , who in May, 2012 have
acquired stake of 2.5000 th. USD from one of the iron ore trading platforms –
Globalore ( Orbis database). The final result from the marketing campaign of the iron ore
price indices since 2008, is the increased volume of trading of iron ore derivatives –
options, swaps and futures. According to information from TSI109,the cumulative trade with
iron ore derivatives on some of the major trading platforms from the financial market, has
increased from zero in 2009, to app.130 million tones monthly in July 2012. ( fig.99). At the
same time, the final result from the introduced new pricing system for iron ore, using the
spot index price IODEX62, is the increased volatility of the iron ore prices, which followed
the volatile trend of IODEX62 ( fig.100).
6.Statistical Analysis for Determining the volatility of iron ore prices, before and after
implementation of the price index IODEX62 to the physical market
6.1.Recalculation and aggregation of the iron ore prices, and calculation of the
volatility of the iron ore prices for both periods of the analysis
We want to see if there is a certain effect over the iron ore price volatility, determined by the
implementation of the price index IODEX62 into the real market. For this reason we will
compare the standard deviations, and means of different iron ore prices, and will use the
monthly price data to calculate the price volatility according to the formula for constant
volatility –moving windows, because it represents best the real historical volatility of prices.
108
109
“Index pricing ‘the next step’ for iron ore market”, Press release - IOSDA, 2010
TSI Iron ore monthly review, July 2012
68
We will do this for two periods- before invention of IODEX62 in June 2008, and afterwards
until Dec 2011. We do not consider the year of the implementation of IODEX62, as officially
used in the iron and steel business in 2010 for two reasons. First, because the invention of
IODEX62 on the financial market have influenced the global iron ore producers before
2010. In addition, because the invention of IODEX62 from the information agencies and the
financial markets, came in the beginning of the financial crisis in 2008. This was the time,
when the collapse of the derivative markets worldwide affected enormously the real
business, and at the same time was a reason to create alternative secure derivative
markets, based on a classic industries like the iron ore mining and steel production. The
second reason to consider June 2008 as a mid- point between pre- and post periods, is
that for the both periods observed- January 2005 - May 2008, and June 2008- December
2011,we have approximately the same number of months. 41 are the months for the first
pre- change period, and 43 - for the second post- change period, which is a good basis to
compare two periods and to get significant results.
To conduct the analysis we have sourced price and freight data from PLATTS-Steel
Business Briefing, which are information leaders in the steel and iron ore industries. We
have used following price data for the major iron ore market prices :
- For Australian FOB prices: 1. Hamersley (Pilbara blend) Lump 63.5% Fe - Japan /
Australia export FOB W.Australian port wet $ cent/t; 2.BHPB Mt.Newman high-grade 63%
Fe fines- Japan / Australia export FOB W.Australian port wet $ cent/t
-For Brazilian FOB prices: 1. CVRD/Vale standard sinter feed 65% Fe - Europe / Brazil
export FOB Tubarao $ cent/t; 2. CVRD/Vale blast furnace pellet 65.7% Fe - Europe / Brazil
export FOB Tubarão $ cent/t; 3. CVRD/Vale Carajas fines (CJF) 66% Fe - Japan / Brazil
export FOB Ponta da Madeira $ cent/t
-For iron ore prices in Asia:1. Iron ore concentrate 66% Fe wet / China domestic Ex- N.E.
China Works (incl. 17% vat) $/t; 2. Indian Iron Ore 63% Fe fines DRY / China import CFR
N.China port $/t;3. IODEX 62 CFR China Dmt
- Freight rates:1. W. Australia - China Capesize Iron Ore - $/t; 2. Brazil - China Capesize
Iron Ore - $/t
First we have recalculated the iron ore prices in USD/Dmt, and have excluded the VAT
from the Chinese price based on EXW. Next we have formed aggregated FOB prices for
Brazil and Australia, from the average of the listed price quoted for each country. Than we
have added the respective freight rates from Australia and Brazil to China, in order to get
the import CFR prices in China, and to be able to measure them on the same market basis,
since China is the main global user of iron ore, producing more than 50% of the world steel
market. This way, in our volatility prices analysis, we are comparing the base import prices
of iron ore on CFR basis China, coming from Brazil, Australia and India, together with the
domestic Chinese price, and the new price index IODEX62, which also based CFR China.
We have entered the data into SPSS file and conducted descriptive statistics in order to
check the data distribution. The results are shown on fig. 101 and 102 from the Annex. We
could see that the data has no missing values, there are 41 entries for the first period, and
43 entries for the second one. Almost all the prices are normally distributed before and after
the change in 2008, with small exception of the Indian CFR China prices for the second
period. In both periods the lowest is the Chinese EXW price ( means 57.24 and 97.43),
while with the highest prices in both periods, are the imports coming from India and Brazil means 102.51 and 100.10 for period 1, and 135.32 and 155.84 for period 2. The standard
deviation which represents also the price volatility, for the first period is lowest for the
69
Australian iron ore – 21.95, and highest, for the Indian – 47.59. For the second period the
standard deviation is lowest for the Chinese material – 30.15, and highest for the Brazilian49.88. On the second step we have calculated with Excel, the volatility of prices for the pre
and post periods, on monthly basis for all iron ore prices according to the formula below. In
order to find the volatility of prices for the first and second periods of observation, we have
multiplied the average monthly volatility found by the formula, with the numbers of the
months in each period.
Formula for constant volatility/moving windows110
N
σ² = 1 Σ Ri² , where Ri = Si - Si-1
N ͥ =1
Si-1
where:
σ² is the volatility
N are the number of the periods
Ri – is the variance of the price in period i
Si is the price in period i
Si-1 is the price in period i - 1
The results about the standard deviations, means, and volatility of prices for both periods
are presented in the table below.
Fig.H. Price volatility, standard deviation and mean of the iron ore prices before and after
the change of the price system.
IODEX 62 PRICE
AUSTRALIAN
BAZILIAN IO
INDIA IO
CHINA
INDEX (BASED
IO PRICE
PRICE CFR
PRICE CFR
DOMESTIC
CFR CHINA)
CFR CHINA
CHINA
CHINA
IO PRICE
Std. Deviation
-
21.95
30.00
47.59
27.60
31.79
Mean
-
70.54
100.11
102.51
57.25
82.60
Volatility period 1
-
63.00%
31.00%
53.00%
178.00%
81.25%
Std. Deviation
42.90
43.33
49.88
42.98
30.15
41.58
Mean
129.90
134.65
155.85
135.32
97.44
130.81
Volatility period 2
68.00%
98.00%
83.00%
61.00%
51.00%
73.25%
Std. Deviation: Period 2- Period 1
21.38
19.88
-4.61
2.55
9.80
Mean period 2 - Period 1
64.11
55.74
32.81
40.19
48.21
AVERAGE
Period1 : Jan 2005- May 2008
Period 2: June 2008 – Dec 2011
Difference: Period 2- Period 1
110
Wilmott Paul, @ Introduces Quantative Finance”, John Wiley and Son, 2007, p. 205
70
Volatility: Period 2- Period 1
n.a.
+35.00%
+52.00%
+8.00%
-127.00%
-8.00%
As we could see from the results in the table, that the average volatility of iron ore prices for
Period 1 ( Jan 2005- May 2008) is 81.25%, while for the second period (June 2008- Dec
2011) it has decreased to 73.25%, which represents change of 8% . It is very surprising,
having in mind that the prices of iron ore have increased enormously after 2008. But when
we take a closer look at the change of price volatilities of the suppliers from different
regions, we will see the difference in the dynamic among the different iron ore suppliers.
We see that prices for iron ore of Australian suppliers to China, have increased their
volatility by 35% from period 1 to period 2. At the same time the Brazilian suppliers have
increased their volatility by the maximum limit for the period: 52% .Much smaller is the
increase in the volatility of the iron ore prices of the Indian suppliers, showing increase of
only 8%. On the contrary, the Chinese domestic market for iron ore have decreased
substantially their enormous volatility from period 1 of 178 %, to 51% in the second period,
which represents a decrease of 127 %. We should also mention that the new price index
IODEX62 represented in the second period of our observation, has an average volatility of
68%, which is the closest to the average volatility for the second period of 73.25%.
As a main reason for such turbulence shift in the volatilities of different suppliers in both
periods, we could mention two main reasons:
1.The increase of the demand for iron ore from China, expressed by increased imports of
iron ore mainly from Australia and Brazil.
2.The inclusion of the IODEX62 index as base for calculation of the contractual prices.
IODEX62 is a price index, based for delivery in China and has a unified quality properties,
and this is causing some practical problems for calculation of the price for real trade. First,
the index is not considering precisely the value in use of the different grades of iron ore
supplied, which might cause big differentials in the price premiums, or the price discounts
of the iron ore traded. Second, the fact that the index is based for delivery in China, makes
the Chinese steel producers beneficiaries from the new index system, because they would
make less mistakes when calculating the price without considering fluctuating freight rates.
And at last, but not least, the fact that the price index is published daily by the main
information agencies in the iron ore and steel business, changes the expectations of the
market players on the market, and makes them anticipate certain dynamics on the market.
At the same time the use of those bulletins became a daily necessity for the companies,
and they trust sometimes more to them, than to their own trading partners, and prefer to
consider the price index as fair market price. In fact, the same the index is used for financial
trade of options, futures and swaps, which are in majority not related with real supply of
iron ore. The fact that those information agencies are serving with market information and
price index, both the financial and the real market, as well as estimating the index based on
more noisy information, makes the use of index unreliable estimate of the real price of the
iron ore, and causing big volatility.
6.2.Statistical analysis of the volatility of the Australian and Brazilian iron ore prices
CFR China, before and after the initiation of IODEX62 in 2008
With the presented in this chapter analysis, we would like to understand, if the increased
volatility of iron ore prices, is showing strong positive relationship with some classic
71
demand and supply drivers (production, export, import, stock inventories, industrial
development), and other marketing and finance- based drivers - freight rates, steel
prices, exchange rates, and competitor’s prices from Brazil, China and India. For
some of the mentioned price volatility drivers, we suggest that they are positively related
with the price volatility, and should keep their positive relationship for both periods- before
and after the implementation of iron ore price index IODEX62. In case, their relationship
decreases or changes between both periods from positive to negative, or in the
opposite case- increases or changes from negative to positive, we would suggest
that the implementation of the iron ore price index IODEX62 has changed the classic
relationships between the price drivers from the real economy, causing additional
volatility of the iron ore prices. Our assumption for this effect, is based on a fact exposed
by many economists, that the intensity and the increasing volume of the derivative trade, is
leading to increase of the price indices. Unfortunately, we couldn’t find time series data
about the volume of trade of the IODEX62 index on the derivative market, and include it in
our statistical analysis. Still, we have bulletin information from TSI, that the derivative trade
with iron ore swap and option price indices, on most of the global financial markets, have
increased from null in 2009, to app.130 million tones monthly in 2012111. This proves the
increasing intensity of iron ore derivative trade and could be a serious reason for the
increased volatility of the iron ore prices, in addition to the move from annual, to quarterlybased price negotiation between the steelmakers and the iron ore miners.
Our approach for analysis is to conduct stepwise multiple regression analysis, for the
periods before, and after the implementation of IODEX62 as benchmark for iron ore
prices in 2008, and see if there is a change in the results about the main drivers of
the price volatility. In general, if we want to understand what is the difference in the
volatility drivers for the different regional markets, we would do the analysis with all regional
iron ore prices used in the previous part. Since, we were limited in our time, the analysis
was performed for the export regions showing the highest iron ore price volatility change,
before and after the implementation of IODEX62- Brazil and Australia. Another reason to
prefer those exporting countries, is that they are the major iron ore suppliers of China, and
the global market. This is also a reason to consider, that the results would be robust, and
valid for the majority of the global iron ore market.
In the multiple regression analysis we will use as dependent variables the aggregated
Australian and Brazilian iron ore prices CFR China, used in the previous analysis about the
price volatility. As independent variables we will use the Chinese iron ore production,
exports, imports, port inventories, the freight rates Brazil- China and Australia- China,
indices for steel prices and global industrial production, real effective exchange rate
USD/Chinese Yuan, and the aggregated iron ore prices based in China, import from India,
as well as the domestic Chinese price for iron ore ( see the analysis for iron ore price
volatility). We will conduct four multiple regressions – two separate regressions for
Australian and Brazilian export prices based for delivery in China, before 2008.
Another two multiple regressions for the same prices will be conducted for the
period after 2008. When we switch the regressions from one Australian to Brazilian iron
ore prices as dependent variables, we will use the other one as independent variable
together with the other 12 independent variables, considering the price, as competitive
market factor like the iron ore prices from India and China.
111
TSI Monthly Iron ore review, July 2012
72
All the data is on monthly basis, and collected from reliable sources – Worldsteel,
UNCTAD, World Bank, PLATTS Steel Business Briefing, other specialized bulletins related
with the iron ore and steel business. We are using one dataset split into two SPSS files
The first file is containing data for the period January 2005-May 2008 (41 months, no
missing values), and the other file is with data from June 2008 – December 2010 ( 43
months). In the second file we have 12 missing values for one of the variables, which is
decreasing the sample size to 31, but still the variables have normal distribution and are
considered to be good for the analysis. The names of the files with the datasets are as
follows: AGGREAED IO PRICE BEFORE THE NEW SYSTEM.sav – for period 1, and
AGGR IO RICE AD IODEX AFTER THE CHANGE 2 SHORT.sav – period 2.
The limitation of the study, or some biases of our results might be influenced by the short
observable period after the implementation of IODEX62 on the financial markets, and the
change of the price system for iron ore – a combined process which started in June 2008.
Therefore we have limited time series of data – 41 months before and 43 months after the
change. Besides that, we have 6 missing values in the variable of the Global Production
index, and 12 in the Real effective exchange rate, which might influence the reliability of the
results. Other data that might be influence the volatility of the iron ore prices was not found
on monthly bases, in order to be included in our analysis. As such could be considered the
Chinese interest rate, or more detailed data on the steel business, as a factor determining
the demand for iron ore. We also had time limitation, in order to try different combinations
of variables and statistical analysis in our study.
In the first multiple regression we did, we used the dataset for the period prior the change
of the price system, and as dependent variable was chosen the price for iron ore from
Australia, CFR China. We had 12 different variables as independent – 3 prices of other
market players ( Brazil, China and India), 2 for freight rates ( Brazil- China and AustraliaChina), 4 variables related with the fundamentals of the demand and supply – production of
steel and iron ore in China, import and port inventories of iron ore in China. Other
2 variables related directly with the prices are also included – the real exchange rate in
China, and Global price for steel products. In addition an index for the Global industrial
development is considered, as detector for increase of the global demand. In the second
multiple regressions we used again the dataset for the period prior the change of the price
system. The dependent variable was the price for iron ore from Brazil, delivered to China.
We used the same 12 independent variables as in the previous analysis, only switching the
place of the Australian price for iron ore from dependent to independent. The third and the
fourth multiple regressions were done with the same dependent and independent variables
as in the first two analyses, but applied to the dataset for the period after the change of the
price system. The outputs for all the four multiple regressions are given as attachments in
fig.104, 104, 205 and 106 from the Annex.Since, it is very hard to analyze them together
due to the volume of information given on many pages in the SPSS output, we have formed
tables with the general results in a summary tables below. There are eight tables - four for
the two periods before and after the change, with multiple regressions on dependent
variables Australian and Brazilian prices. There are two types of tables - four of each type (
for each of the multiple regression). The extracted data content for the first four tables is
given in the notes under the first table. The data extracted for the second group of four
tables, is explained under the notes of the first table, form the second group of tables.
73
Fig.I. MULTIPLE REGRESSION RESULTS FOR THE PERIOD BEFORE THE IMPLEMENTATION OF IODEX 62112:
JAN 2005 - MAY 2008
DV : IO PRICE AUSTRALIA CFR CHINA BEFORE
THE IMPLEMENTATION OF IODEX 62
1
Independent Variables :
IO PRICE AUSTRALIA CFR CHINA BEFORE THE
CHANGE
IO PRICE BRAZIL CFR CHINA BEFORE THE
CHANGE
IO PRICE INDIA CFR CHINA BEFORE THE
2
Standard
deviation
21.952
30.001
3
Pearson
Correlati
on
1
0.953
4
Unstandardi
(A,B,C,D),
zed
Included
Coefficients
variables
Beta
7
8
Sig.
t
.
0.000
0.000
27.599
0.850
0.000
Brazil - China Capesize Iron Ore - $/t
25.883
-0.280
0.038
W. Australia - China Capesize Iron Ore - $/t
9.637
-0.316
0.022
Crude Steel production, China, mln.t
4.670
0.650
0.000
Production of Iron Ore, China, mln.t
10.474
0.614
0.000
Import of Iron Ore in China, mln.t
10.062
0.752
0.000
SBB China steel price tracker -$/t
46.637
0.139
0.193
China, Real effective Exchange rate
7.857
0.685
0.000
GLOBAL INDUSTRIAL PRODUCTION INDEX
4.780
-0.395
0.005
PORT INVENTORIES IO CHINA, MLN.T
12.991
0.717
0.000
CHANGE
4 models
tailed)
0.808
CHINA DOMESTIC IO PRICE BEFORE THE
6
Sig. (1-
47.591
CHANGE
5
min. 0.723-
A,B,C,D
max.0.818
D
-0.176
min.1.067-
B,C,D
max.1.380
min.1.4247
0.000
max.26.368
0.021
0.000
-2.408
min.4.818 max. 7.239
Fig.G. DV: IO PRICE BRAZIL CFR CHINA BEFORE
THE IMPLEMENTATION OF IODEX 62
Independent Variables :
IO PRICE AUSTRALIA CFR CHINA BEFORE
THE CHANGE
IO PRICE BRAZIL CFR CHINA BEFORE THE
CHANGE
Standard
Pearson
deviation
Correlation
Sig.
(1tailed)
21.952
0.953
0
30.001
1
.
4 models
Unstandardiz
(A,B,C,D),
ed
Included
Coefficients
variables
Beta
A,B,C,D
min. 1.073max.1302
Sig.
0.000
t
min.18.247max.26.368
112
The data is sourced from the SPSS outputs as follows :Column 2: Extracted from the descriptive statistics are, the
standard deviations of the independent variables; Columns 3 and 4: Extracted are the Pearson correlations and the
significance values between the dependent variables and independent variables from the table with the correlations.;
Column 4: Data is taken from the tables Summary of the models, and Coefficients, where are outlined the dep.var., which
fit best the model. Column 5: Data is taking the minimum and maximum for unstadardized Beta for the variable, included
in column 4, from table Coefficients.; Columns 7 and 8: Extracted data for significance and t- value of the selected
variable from table Coeffieicnts.
74
IO PRICE INDIA CFR CHINA BEFORE THE
47.591
0.89
0
27.599
0.884
0
Brazil - China Capesize Iron Ore - $/t
25.883
-0.452
0.001
W. Australia - China Capesize Iron Ore - $/t
9.637
-0.495
0.001
Crude Steel production, China, mln.t
4.670
0.578
0
Production of Iron Ore, China, mln.t
10.474
0.512
0
Import of Iron Ore in China, mln.t
10.062
0.771
0
SBB China steel price tracker -$/t
46.637
-0.009
0.478
China, Real effective Exchange rate
7.857
0.711
0
D
GLOBAL INDUSTRIAL PRODUCTION INDEX
4.780
-0.6
0
B,C,D
PORT INVENTORIES IO CHINA, MLN.T
12.991
0.713
0
C,D
CHANGE
CHINA DOMESTIC IO PRICE BEFORE THE
CHANGE
-0.674
0.07
min .-2.018 max. -1.666
0.000
-2.873
min. -9.591
-max.-8.255
min.0.196 -
0.01-
min.2.085 -
max. 0.596
0.44
max. 3.668
Fig.K. MULTIPLE REGRESSION RESULTS FOR THE PERIOD AFTER THE IMPLEMENTATION OF IODEX 62: JUNE 2008 - DEC 2010
DV: IO PRICE AUSTRALIA CFR CHINA AFTER THE IMPLEMENTATION OF IODEX 62
5 models
Independent Variables
Standard
Pearson
Sig. (1-
(A,B,C,D,E),
deviation
Correlation
tailed)
Included
variables
AUSTRALIAN IO PRICE CFR
30.758
1.000
.
38.422
0.929
0.000
40.680
0.626
0.000
25.642
0.730
0.000
20.916
0.138
0.229
B,C,D,E
6.789
0.045
0.404
D,E
5.676
-0.006
0.487
15.118
0.411
0.011
Import of Iron Ore in China, mln.t
9.179
-0.293
0.055
SBB China steel price tracker -$/t
35.447
0.573
0.000
CHINA AFTER THE CHANGE
BAZILIAN IO PRICE CFR CHINA
AFTER THE CHANGE
INDIA IO PRICE CFR CHINA
AFTER TEH CHANGE
CHINA DOMESTIC IO PRICE
AFTER THE CHANGE
Brazil - China Capesize Iron Ore
- $/t
W. Australia - China Capesize
Iron Ore - $/t
Crude Steel production, China,
mln.t
Production of Iron Ore, China,
mln.t
A,B,C,D,E
C,D,E
Unstandardized
Coefficients
Sig.
t
Beta
min. 0.744max.0.881
min. 0.534max.0.869
0.000
0.000
min.13.539max.37.826
min. -10.996 max.- 7.573
min. 1.034-
0.001 -
min. -3.107 -
max.1.172
0.005
max.- 3.733
min. – 0.358 -
0.000 -
min. – 4.008 -
max.- 0.310
0.004
max.- 3.139
75
China, Real effective Exchange
rate
GLOBAL INDUSTRIAL
PRODUCTION INDEX
Port inventories of IO-China, Mt
3.987
0.164
0.189
3.373
0.597
0.000
5.237
0.096
0.304
D
0.708
0.030
2.304
Fig.L. DV: IO PRICE BRAZIL CFR CHINA AFTER THE IMPLEMENTATION OF IODEX 62
4 models
Independent Variables
Standard
Pearson
Sig. (1-
(A,B,C,D),
deviation
Correlation
tailed)
Included
variables
AUSTRALIAN IO PRICE CFR
CHINA AFTER THE CHANGE
BAZILIAN IO PRICE CFR CHINA
30.758
0.929
0.000
A,B,C,D
1.000
.
40.680
0.767
0.000
25.642
0.837
0.000
20.916
0.458
0.005
B,C,D
6.789
0.328
0.036
D
5.676
0.102
0.293
15.118
0.451
0.005
Import of Iron Ore in China, mln.t
9.179
-0.226
0.111
SBB China steel price tracker -$/t
35.447
0.767
0.000
3.987
0.127
0.248
3.373
-0.102
0.293
5.237
0.695
0.000
INDIA IO PRICE CFR CHINA
Coefficients
Sig.
t
Beta
min.1.029
0.000
- max. 1.161
38.422
AFTER THE CHANGE
Unstandardized
min.3.2061
max.13.539
AFTER TEH CHANGE
CHINA DOMESTIC IO PRICE
AFTER THE CHANGE
Brazil - China Capesize Iron Ore
- $/t
W. Australia - China Capesize
Iron Ore - $/t
Crude Steel production, China,
mln.t
Production of Iron Ore, China,
mln.t
China, Real effective Exchange
rate
GLOBAL INDUSTRIAL
PRODUCTION INDEX
PORT INVENTORIES IO CHINA,
MLN.T
C,D
min. 0.617 max. 0.957
0.000
min.8.643max.13147
-1.088
0.004
-3.116
min. 0.254 -
0.000 -
min.3.562-
max. 0.261
0.001
max.4.202
76
Fig.M. IO PRICE AUSTRALIA CFR CHINA BEFORE THE CHANGE113
MODEL A
2
3
4
Adjusted
ANOVA-
R Square
F
0.905
MODEL B
MODEL C
MODEL D
382.28
5
6
7
ANOVA-
Durbin-
Colinearity-
Normal
Sig.
Watson
Tolerance
a
1.000
b
0.640
.000
0.954
415.498
.000
0.959
310.527
.000c
0.963
264.55
.000d
8
9
distribution
Residuals
Heteroscedasticity
YES
OK
PROBLEM
min.0.205 -
1.777
max. 0.599
min.0.036 max. 0.393
Fig. N. IO PRICE BRAZIL CFR CHINA BEFORE THE CHANGE
MODEL A
MODEL B
MODEL C
MODEL D
Adjusted
ANOVA-
ANOVA-
Durbin-
Colinearity-
Normal
R Square
F
Sig.
Watson
Tolerance
distribution
0.905
382.28
.000a
1.000
b
0.844
0.965
554.307
.000
0.968
403.548
.000c
0.973
364.055
.000d
min.0.433-
1.143
Residuals
Heteroscedasticity
OK
PROBLEM
YES
max.0.840
min.0.181max.0.596
Fig.O. IO PRICE AUSTRALIA CFR CHINA AFTER THE CHANGE
Adjusted
R Square
ANOVA-F
ANOVA-
Durbin-
Colinearity-
Normal
Sig.
Watson
Tolerance
distribution
Residuals
Heteroscedasticity
YES
OK
PROBLEM
MODEL A
0.859
183.309
.000a
1.000
MODEL B
0.965
420.521
.000b
0.790
0.974
372.246
.000c
0.980
371.098
.000d
0.123-0.706
0.983
347.149
.000e
0.106-0.874
MODEL C
MODEL D
MODEL E
1.036
0.761-0.948
113
The data is sourced from the SPSS outputs as follows: Columns 2 and 5 data is extracted from the Model Summary
table; Data in Columns 3 and 4 – from ANOVA table; Data in Column 6: From the Coefficients table; In columns 7, 8 and
9: from the Charts
77
Fig.P. IO PRICE BRAZIL CFR CHINA AFTER THE CHANGE
Adjusted
R Square
ANOVA-F
ANOVA-
Durbin-
Colinearity-
Normal
Sig.
Watson
Tolerance
distribution
MODEL A
0.859
183.309
.000a
1.000
MODEL B
0.972
525.345
.000b
0.981
0.980
500.656
.000c
0.985
499.065
.000d
MODEL C
MODEL D
0.613
0.814 - 0.979
YES
Residuals
Heteroscedasticity
OK
PROBLEM
0.128-0.829
General results for multiple regression analysis with dependent variable- Australian
iron ore price CFR China
Multiple regression analysis was conducted with the dependent variable Australian iron ore
price CFR China twice – with sample data for 12 dependent variables, before and after
2008. The big quantity of the variables, have caused higher level of multicolinearity and
heteroscedasticity especially in the model for the first period, but in general most of the
residuals are fitted well on the probability plot and are normally distributed for both periods.
For the period after 2008, we have slightly worse fitting to the model, but, the residuals are
less clustered, which is caused partially by the 12 missing values we have in the second
period. For the first period we have 11 significant correlations between the dependent
variables and the Australian iron ore prices, and in the second period- only 5. In both
periods, the variables with the highest positive relationship with the dependent variable, are
the competitor’s prices from Brazil, China and India. Their significance in both periods is
0.000, but has decreased in the second period ( for more details- see below the paragraph
with explanation of the price variables results). Second most important variable for both
periods is the Global Industrial index, reflecting the global demand trend. Its correlation
values have changed from negative in the first period, to positive in the second, but kept
their high significant levels around 0.000 – 0.005. Many classic supply- demand price
drivers variables from the first period, have changed their strength and direction from the
first, to the second period. In the first period positive relation with the Australian iron ore
prices showed the Production, Imports and Port inventories of Iron ore in China, the Crude
steel production in China, the exchange rate Yuan/USD, and the freight rates from Brazil
and Australia to China. In the second period besides the competitors prices, and the Global
industrial index, positive relationship with the Australian iron ore prices showed the Steel
price tracker, which was negatively related in the first period. In the period after the initiation
of IODEX 62 and the new price system for iron ore, most of the listed supply-demand
fundamental variables, which showed positive relationship in the first period, have changed
the strength and direction of relationship with the Australian Iron ore prices in the second
one.
78
General results for multiple regression analysis with dependent variable- Brazilian
iron ore price CFR China
Similarly to the multiple regression analysis with the Australian iron ore prices, we have
conducted twice multiple regression analysis with dependent variable the Brazilian iron ore
prices CFR China, with sample data for 12 dependent variables, before and after 2008. As
in the previous models, we have detected higher level of multicolinearity and
heteroscedasticity in the first period, but most of the residuals were fitted well on the
probability plot and were normally distributed for both periods. For the period after 2008,
the model showed less clustered residuals, and worse fitting with the probability line, due
probably mainly to the 12 missing data in the sample for the second period. For the first
period we have 11 significant correlations between the dependent variables and the
Brazilian iron ore prices, and in the second period- only 5. The only one independent
variable, which wass not positively related with the Brazilian iron ore prices in the first
period, wass the Steel price tracker- China. Similarly to the case with the Australian prices,
Brazilian iron ore prices showed biggest positive correlation with the prices of other
competitors from India, China and Australia , for both periods. In the second period, the
only two other significant variables related with the Brazilian iron ore prices, were the
Global industrial production index, and the Steel price tracker- China, which have changed
the direction and strength of its correlation with the dependent variable. The other supplydemand related price drivers like Production, Imports and Port inventories of Iron ore in
China, the Crude steel production in China, the exchange rate Yuan/USD, and the freight
rates from Brazil and Australia to China, became insignificant towards the Brazilian iron ore
prices. Many of them also changed the strength and the direction of their relationship with
the dependent variable, after the initiation of IODEX62 and the implementation of the new
iron ore price system in second period.
Estimation of the models
All models suggested by the stepwise multiple regression analysis ( see A,B,C,D models
from tables Model Summary in the SPSS outputs, or the last 4 summarized tables above),
both before and after the change, are highly significant. The outlined by the models
variables are explaining more than 90% of the variation of the iron ore prices. For the first
period, the variables showing greatest relationship with the iron ore price volatility are the
competitor’s export prices from Brazil, India and Australia, the Global Industrial production,
the real effective exchange rate in China, and the Chinese port inventories of iron ore
For the second period after 2008, variables showing largest relationship with iron ore price
volatility, are the Australian and Brazilian prices, the freight rates from Brazil and Australia
to China, and the production and import of iron ore in China ( see columns 4 to 7 from the
first four summarized tables above). We could summarize that the most important
influence over the iron ore price volatility, is exercising the market competition
between the exporters from Australia and Brazil, because it is influencing the iron
ore prices by comparatively higher extend, in both periods before and after 2008.
Some classic factors related with the demand and supply are changing their
importance between both periods: before 2008 the Global industrial production and
the Chinese port inventories are more related with the price volatility of iron ore,
compared to 2008, when the iron ore production in China and Chinese imports are
showing greater importance. After 2008, the freight rates in general are also
79
increasing their influence over the volatility of iron ore prices, while in the previous
period their influence was comparatively not so significant and negative in its
character. The real effective exchange rate in China, has also decreased its highly
significant and strong positive influence from the first period, becoming insignificant
in the second one. The variables combinations in the models are sharing big variance,
represented by the F statistics. There is a small problem with the multicolinearity detected
from the Durbin Watson coefficient, the Colinearity tolerance and the Hetroscedasticity plot.
On the other side all models and their residuals are following the normal distribution, and
are fitted comparatively well along the regression line, which confirms that our model is
robust.
Detailed analysis of the correlations of all independent variables, with the Brazilian
and Australian iron ore prices for both periods – before and after 2008.
Considering the models formed with the multiple regressions, we could detect some
independent variables, which showed difference in the dynamic over time. The
direction or the strength of the relationship of some of them with the dependent
variables, changed before and after 2008. For example the Global Industrial production
index have changed it’s relationship with the iron ore price volatility, from slightly to strongly
negative: Pearson corr. – 0.395 ( sig. 0.005, Brazil), and – 0. 6 ( sig. 0.000, Australia) in
the first period, to strongly positive for the Australian iron ore prices ( 0.597, sig.0.000), and
insignificant for the Brazilian iron ore prices ( -0.102, sig.0.293) in the second period. This
could mean that in the first period, the increasing Global industrial production led to
decreasing the volatility of the iron ore prices in Australia and Brazil, while after
2008, the increasing industrial production changed its influence over the price
volatility to positive for the Australian iron ore prices, and insignificant for the
Brazilian. We could consider the negative and the insignificant effects of the industrial
output over the volatility of the iron ore prices as anomaly, caused possibly by oversupply
of iron ore before 2008, and increasing shortage from the Asutralian market after 2008,
which have reflected partially the Brazilian market. It could be also caused by the missing
values in the sample for the second period, or the implementation of the new price system
for iron ore after 2008.
The port inventories of iron ore in China in the first period, showed significant correlation
with the price volatility – about 71% for both regressions. In the second period, the
independent variable for the regression of the Australian iron ore prices becomes
insignificant, and for the Brazilian prices, slightly decreases to 69%, but the strong positive
trend of the relationship is sustained in general in both periods. This could mean, that the
Port inventories could explain about 71 % of the variation of the of the Australian
and Brazilian iron ore prices before 2008, and about 69% of the volatility in the
Brazilian prices after 2008. The volatility of the iron ore prices in Australia after 2008,
could not be confirmed to be dependent on the port inventories of iron ore in China.
The diminishing effect of the Chinese port inventories over the prices of iron ore, exported
from Australia to China, might have been affected by the closer distance and lower freight
rates between both countries, compared to the Brazilian export. Another possibility is the
change of the fundamental supply- demand drivers after the implementation of the new iron
ore pricing system after 2008.
The iron ore production in China in the first period showed about 51% and 61% significant
positive correlation ( sig. 0.000) respectively, with the volatility of the iron ore prices in
Brazil and Australia. In the second period, after the implementation of IODEX62, the
relationship stayed positive but decreased to 45% for Brazil ( sig.0.005), and to 41% for
80
Australia ( sig.0.011). The results showed, that the iron ore prices levels for Brazilian
exporters, decreased their dependence from the Iron ore production in China by 6%,
after the implementation of IODEX62 and the new price system for iron ore. For the
same period, the volatility of the Australian iron ore prices decreased its dependency
from the levels of iron ore production in China by app. 20%. This analysis is showing
that the classic supply- demand fundamental driver has decreased its power,
especially on the iron ore market in Australia. The effect might be partially due to
slightly decreased iron ore production by 6Mt in China between 2008 and 2011 ( fig.62.),
but its suggested effect is minor, compared to the volumes of the Chinese economy and
iron ore consumption.
In the period prior the implementation of IODEX62 and the new price system, the levels of
Import of iron ore in China have showed strong positive and significant relationship with
both Australian and Brazilian iron ore prices delivered in China, respective corr.coef. :
0.752 ( sig.0.000), and 0.711 ( sig.0.000). In the second period the relationship between the
imports and the price volatility becomes slightly negative and insignificant: Australia with
corr.coef. – 0.293 ( sig.0.055), and Brazil with corr.cef. – 0.226 ( sig.0.111). According to
the results, the volatility of the Brazilian and Australian iron ore prices before 2008,
could be explained by app. 71-75% of the increasing Imports of iron ore in China.
After the invention of IODEX 62 and its implementation with the new pricing system
for iron ore after 2008, the volatility of the iron ore prices is not any more positively
affected by the levels of the imports in China, and is showing more probable
negative relationship towards the increase of the iron ore prices. This changing
trend in the influence of such important supply- demand driver as the iron ore
imports, towards the volatility of the iron ore prices is difficult to be accepted as
normal. Besides, on fig. 66, we could see that the import of iron ore in China have
increased by 162% between 2005 and 2008, and by 146% between 2008 and 2011. The
difference in the imports increase trends between both periods is only 16%, and the total
increase of iron ore imports between 2005 ( 275Mt) and 2011( 642Mt) is in total 233%. The
means and the standard deviations of the iron ore imports in China both periods are
exposed on the SPSS outputs in the attachment. For period 1, the mean is 10.06, and
standard deviation 37.38. For period 2: the mean is 9,18, and stand. dev. is 48.36.
Checking the multiple regression results about correlations of the Iron ore imports in China,
we could also see, that in the period before 2008, the variable is highly correlated with
many of the other 12 variables, while in the second period, it is highly correlated only with
the Steel crude production ( 0.686, sig.0.000),and Iron ore production ( 0. 452, sig.0.005).
We could suggest that the levels of imports as fundamental supply- demand driver
has kept its strong relationship with other strong supply- demand drivers, like the
steel and iron ore production, but at the same time other factors have caused
erasing of its fundamental market influence, increasing its standard deviation, and
changing its significance over the iron ore price volatility.
Considering the freight rates from Australia and Brazil to China, for the periods before and
after 2008, we could say that they experience big changes towards their relationship and
strength with the iron ore price volatility. We would outline, that the results for the freight
rates Brazil- China and Australia- China, in both regressions with dependent variable
Brazilian iron ore prices, and in both periods estimated, showed close significance levels –
respectively 0.001/0.005, and 0.001/ 0.036. At the same, time, the direction of their
relationship, measured by Pearson correlation have changed, keeping its strength of about
30-50%. For freights Australia- China, Pearson correlation changed from – 0.495 in period
81
1, to + 0.328 in period 2, and respectively for from – 0.452, to + 458, for the freights BrazilChina. This could mean that, in the period prior to implementation of IODEX 62 in
2008, app. 50% of the increase of the freight Australia- China, and 45 % of the
increase of the freight Brazil- China, would effect in decrease of the volatility of
Brazilian iron ore prices. On the opposite, in the period after 2008, percentage
increase of the volatility of the Brazilian iron ore prices, was caused by increasing of
the freight Australia- China by app. 33%, and 46% increase of the freight BrazilChina.
The results for the volatility of the Australian iron ore prices, in respect of the freight rates
Brazil- China and Australia- China in period 1, showed similar negative relationship as the
Brazilian iron ore prices. For the second period the trend also changed to positive, but
stayed insignificant, for distance from the Brazilian iron ore prices. The Pearson correlation
coefficient before 2008, between the Australian CFR prices China, and the freight BrazilChina was – 0.28 ( sig.0.038), but after 2008 changed to 0.138 ( sig.0.229). Similar is the
situation with the freight Australia- China, which showed low negative relationship with the
Australian export prices to China: - 0.316 ( sig.0.022) before 2008, and changed to positive,
but insignificant after 2008: 0.045 ( sig.0.404). We could summarize, that before the
implementation of IODEX62, the increase of the freight Brazil- China by app.28%, and
the freight Australia- China by app.32%, was causing decrease of the volatility of the
export iron ore prices from Australia to China. After the financial crisis and the
change of the price system in 2008, the Australian iron ore prices CFR China have
lost their relationship with the level of the freights Brazil- China and Australia- China.
When we analyze the influence of the market price competition, over the volatility of
the iron ore prices of the Australian and Brazilian exporters, we are interested in the
price correlation , and significance values of the Australian, Brazilian, Indian iron ore
exporters in China, and the domestic Chinese iron ore price. The correlation between the
Australian and Brazilian iron ore prices have decreased from 0.953 ( sig.000) before 2008,
to 0.929 ( sig.0.000) after 2008. We could say, that the volatility of the iron ore prices
between the leading Australian and Brazilian global market players, has decreased
its interdependence by 2.4%, from the period before the invention of IODEX62 and
the implementation of the new price system for iron ore. Still, they were experiencing
very strong positive relationship, explaining about 95% of their price variances in the
first period, and app.93% in the period 2008 -2011. The Indian iron ore prices CFR
China have decreased more their positive relationship with the volatility of the iron ore
prices, of the Australian and Brazilian exporters during 2005- 2011. The Pearson
correlation between the Indian and Australian iron ore prices have decreased from 0.808 (
sig.0.000), to 0.626 ( sig.0.000) for the periods before and after 2008. The relationship
between the Indian and the Brazilian iron ore prices based in China, have changed from
0.890 ( sig.0.000), to 0.767 ( sig.0.000) for the same periods. In a summary, the increase
of Indian iron ore prices CFR China, was explaining app.81% of the variance in the
Australian, and 89% from the Brazilian iron ore prices based in China, during 20052008. Its positive trend effect over the Australian and Brazilian export prices
decreased during 2008- 2011, respectively by app. 18% and 12%. The Chinese
domestic iron ore prices, have also decreased their very strong positive relationship with
the Australian and Brazilian export prices based in China, during 2005- 2011. In the period
prior to the invention of IODEX 62 and the new price system, the correlation between the
Domestic iron ore prices in China and the import iron ore prices from Australia, was 0.850 (
sig.0.000), while after 2008, it has dropped to 0.730 ( sig.0.000). The same relationship,
82
but with the Brazilian iron ore import prices have decreased from 0.884 ( sig.0.000) in the
first period, to 0.837 ( sig.0.000) in the second one. This means, that the change in the
domestic Chinese iron ore prices was explaining 85% from the variance in the
Australian import iron ore prices in China during 2005- 2008, but after 2008 , its
positive influence has decreased by 12%, reaching 73% in 2011. At the same time,
the influence of the Chinese domestic iron ore prices over the Brazilian iron ore
import prices, have dropped from app 88% in period 1, to app. 84% in period 2,
representing change of about – 4%.
It is interesting to mention, that in general, the relationship between most of the iron
ore prices under this study, are decreasing and sometimes changing from positive
to negative, in relation with fundamental supply- demand factors like Crude steel
production, Production of Iron ore, Imports and Port inventories from the first to the
second period. At the same time, the iron ore prices tend to change from negative, to
positive their relationships with the freight rates ( see the SPSS outputs , tables
correlations). Another phenomena, which we would like to outline, is the trend of
decreasing the positive correlations between the prices of the global Australian and
Brazilian leaders, and even more decreasing correlation between their prices and the
Indian and Chinese iron ore prices, mentioned in the analysis above. In this relation,
we would like to remind also, that during the previous analysis of volatility of iron ore prices,
we have found out, that during 2008 -2011, the volatility of the Indian CFR price
showed closest average volatility to the volatility of IODEX62 ( 61% versus 68%,
accordingly). At the same time, the domestic iron ore producers in China became the
net winners from the implementation of IODEX62 ( based on CFR China), and
decreased their price volatility by 127% from period 1, to period 2 ( 178% versus
51 %). Besides that, the supply- demand and the consolidation analysis from previous
chapters, confirmed the increasing market concentration in the iron ore industry,
related with many mergers, acquisitions and joint ventures. We would suggest , that in a
situation of increasing market concentration, the decreasing correlation between the
prices of the iron ore producers, are two contrary processes that cannot coexist.
One reason for this result could be the missing values in our dataset for the second
period of analysis. And the other reason, could be the implementation of the iron ore
price index IODEX 62, which is acting like major market competitor on the global iron
ore market, changing the relationships between the main market players, and the
fundamentals of the supply and demand, as it was confirmed in our analysis.
The influence of the real effective exchange rate between the Chinese Yuan and USD, has
changed its influence over the export iron ore prices from Australia and Brazil to China, for
the period before, and after 2008. The Pearson correlation coefficient between the
exchange rate Yuan/USD, and the Australian iron ore prices has decreased from 0.685
( sig.000) before 2008, to 0.264 ( sig. 0.189) , and became insignificant at 0.05 level. In the
same both periods, the correlation of the Yuan/USD exchange rate with the Brazilian iron
ore prices, decreased also from 0.711 ( sig.0.000), becoming insignificant in the second
period with value 0.127 ( sig.0.248). We could summarize, that during 2005 -2008, the
increase of the Real effective exchange rate Yuan/USD, was affecting about 69% of
the variance in the Australian iron ore prices, and 71% from the variance of the
Brazilian export prices. The changed situation with the new iron ore price system
after 2008, have deteriorated this classic and pure financial relationship between the
83
exchange rates and export prices, causing decreasing of the correlation between
them, which became also insignificant.
The Steel price tracker - Chiina is a price index, formed by Steel Business Briefing, based
on systematic tracking of variety of steel prices in China. We consider it to be useful and
correct for our analysis, and to define the price relationship of the cost formation between
the iron ore miners and the steelmakers. In our analysis during the first period, the steel
price tracker showed insignificant relationship and slight positive relationship with the
Australian iron ore prices, with Pearson correlation coef. 0.139 ( sig.0.139). In the second
period the correlation increased to 0.573 and became significant at level 0.05, with
sig 0.000. This could mean, that in the period prior to the change of the pricing
system, the variance of iron ore prices didn’t show significant relationship in the
variance of the steel price level. After 2008, this relationship became very strong and
significant: 57% of the increased variance in the steel prices, could explain also the
increase of the volatility of the iron ore prices. The relationship between the steel prices
and the level of the Brazilian iron ore were similar: insignificant and slightly negative
correlation of - 0.009 (sig. 0.478) in the first period, and 0.767 ( sig.0.000) in the second
one. After 2008, the increase in the Brazilian iron ore prices could be explained by
app.77% of the variance of the steel prices, while this relationship was insignificant
prior to the change of the iron ore price system. Here we would like to mention, that this
relationship between the iron ore and steel prices, is depending to large extent on the cost
structure and the technologies used for production of one unit of steel. Usually the
production of one tone steel, requires about 1.4 tones of iron ore, which is confirmed
also by the data on fig. 73 and 74 ( see chapter Supply – Demand analysis of the Iron
ore). This means, that the analyzed drastic change in the relationship between the
steel and iron ore prices after 2008, is not due to the change in the supply- demand
relationship of the quantities. We know, that the iron ore prices were negotiated in the
past on annual basis, but the developing of the new pricing system since 2008, and its
official implementation from 2010, using the price- quoting on semi- year and
quarterly basis, using the financial spot price index IODEX62, caused many changes.
This could be a very reasonable condition, to increase the iron ore prices more often, which
causes changes in the cost structure of the steel producers, deteriorating their profits and
working capital ( already proved in the chapter Profit- Revenue Analysis of the iron ore
miners and the steelmakers). This way, the volatility of the iron ore prices have been
transferred to the steelmakers, who also started quoting of their prices on more
regular basis, adding price- formulas to adjust their prices, to the change of the
prices of the raw materials. That’s why we are sure that in our analysis, the change
of the relationship between the Steel price tracker- China, and the Australian and
Brazilian iron ore prices CFR China after 2008, is not caused by missing values in
the sample for the second period, but mostly because of structural changes in the
iron ore and the steel industry.
The Crude steel production in China is very important classic supply- demand driver for
the iron ore prices. As we have already explained in the previous paragraph ( see Steel
price tracker), there is a direct cost relationship between the steel and the iron ore, since
the last one is the major raw material for the steel production in certain proportions. If we
follow the classic demand- supply theories, certain quantity of steel demand, should cause
certain quantity of iron ore demand, and would influence the final iron ore prices. The
strength of the classic supply- demand theories is proved in our analysis, by the
84
relationship between the Crude steel production in China, and the export prices for iron ore
from Brazil and Australia to China, represented only in the first period. Pearson correlation
between the Crude Steel production and the Australian iron ore prices before 2008, was
0.650 ( sig.000), and with the Brazilian iron ore prices : 0.578 ( sig.0.000). In a summary,
before the new price system for iron ore, 65% of the variance in the Australian iron
or prices, and 58% of the variance of the Brazilian iron ore prices, could be explained
by percentage change in the Crude steel production in China. After the change of the
price system for iron ore, this classic supply- demand relationship has lost its
significance and strength. Pearson correlation between Australian and Brazilian iron ore
prices, and the Crude steel production in China became respectively - 0.006 ( sig.0.487),
and 0.102 ( sig.0.293).
Summary
The results from the analysis are showing significant change in the classic supply- demand
drivers for the iron ore prices before, and after the invention of the price index IODEX62,
and the new iron ore pricing system, both initiated after 2008. The main trend extracted
from the our study is, that on the biggest Chinese market for iron ore, the prices of the
leading exporters from Australia and Brazil, have decreased and in some cases abandoned
their classic relationship with the iron ore price drivers like the Production, Imports and Port
inventories of Iron ore in China, the Crude steel production in China, the exchange rate
Yuan/USD, and the freight rates from Brazil and Australia to China. Based on the
statistical analysis, as main drivers affecting the level of the import prices of iron ore
in China before and after 2008, are outlined the Global industrial production, and the
Market price competition between exporters from Australia, Brazil, India, and the
domestic Chinese iron ore producers.
We have assumed the effect of the missing values in our analysis for the period after 2008,
but still, the estimates are showing that our model is robust. We are considering, and have
explained in details in this chapter, how the structural changes in the iron ore and steel
industries after 2008, have caused strong effect over the volatility of the iron ore prices.
Based on the Supply- Demand analysis of the iron ore, the Analysis of the Profits and
Revenues of the Iron ore miners and the Steelmakers, and the Statistical Analysis of the
volatility of the iron ore prices, as main reasons for the increased volatility of the iron
ore prices we would assume the following:
-
-
-
The fast increased global demand and industrial production, coming mainly from
Asia and China, which is difficult to be absorbed on time by the iron ore suppliers, due
to financial, logistic and force- majeure problems.
Increased global market concentration, result of the consolidation process in the
iron ore and the steel industry. The final effect is the formation of oligopoly market
structures by the iron ore miners, deteriorating the profits of the steelmakers through
speculative high iron ore prices.
The invention of the iron ore benchmark spot price index IODEX 62 ( and other
alternatives), by the information agencies and the financial market in 2008, and
its implementing both for derivative trade on the financial markets, and as pricedeterminate for negotiations between the iron ore miners and the steelmakers. The
estimation of the index is based on daily sourced and manipulated data, sourced by
different representatives of the real and financial market.
85
-
-
-
-
The official change of the price system for iron ore price settling, introduced by
the leaders on the iron ore market – Vale, BHP Billiton and Rio Tinto in 2010.
Previously, the iron ore prices were negotiated and settled around March- April each
year. From 2010, the price- settling moved to semi- year, and later to quarter, and
in some cases on monthly basis. The price formula was changed, implementing
the spot price benchmark IODEX62, as official formula for price calculation of the
iron ore. The increased frequency of negotiations, and the differentiations between the
technical specification and the specified terms of trade of the iron ore benchmark,
caused many differentiations in the re-calculation of the official prices. In addition, the
intensified derivative trade with iron ore on the global financial market, have
caused additional speculation trend in the quotes of IODEX62, which is further
transferred to the real market.
Our suggestions to handle the problem with the volatility of the iron ore prices
are including:
Revision of the formation system for the quotes of IODEX62, or any other iron ore
or steel- based derivatives.
Limitation of the volumes of trade with derivatives, according to the proportional
volume of the trade on the physical market. Initiating of requirement for control of
the financial deals of the traders on the financial market, in order to prevent
speculation in big sizes among different derivatives like iron ore, steel, freight rates,
exchange rates, interest rates and etc., concerning directly or indirectly the price
formation in the iron ore and the steel industry
Revision of the new price system for iron ore by the miners and the steelmakers,
and recommendation for transit to maximum of semi- annual price- settlement.
Reconsideration of the use of the spot price benchmark IODEX62 for physical
trade.
Prevention of further consolidation and concentration among the Big 3 in the iron
ore industry, which would create definite monopolist on the global iron ore
market, and would increase the trend of increasing the iron ore prices, and
deterioration of the profits and working capital in the steel business. This process
would also fuel next consolidations between the iron ore and steel industry, and will
decrease the market competition in both industries.
All above mentioned conclusions about the sources of the volatility of the iron ore
prices, based on different analyses in the presented Master thesis, and the suggested
possible decisions, could be very useful for different regulatory authorities, concerned
with the prevention of the market concentration and monopolies, frauds on the financial
markets, or any representatives of the iron ore and steel industry
86
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