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Oil Price Volatility Factors
An Applied Research Project Presented in Partial Fulfillment
of the Requirement for the Degree
Master of Business Administration
by
Piyal Das
Applied Project Supervisor: Dr. Rodney Beard
Abstract
The need for Oil has shaped economies, governments and lives of people on global
scale in twenty-first century. The necessity caved to the price of getting that Oil. Oil
price and its volatility have affected the modern society more than any other commodity.
The author identified key factors that historically have repeatedly influenced the supply
and demand equilibrium and thus price for Oil. BRICS countries have taken the lead in
driving the demand for Oil however; there is growing trend that emerging economies
outside OECD and BRICS will mold future demand. OPEC will continue as the major
supplier like past few decades nevertheless, the intra-cartel competition and noncooperation has negatively influenced supply for Oil. The possibility of formation of
outside OPEC cartelization cannot rule out in future but that could lead to inter-cartel
race and supply volatility. Existence of multiple benchmark reference crude prices
paved way for opportunistic endeavors from commodity traders, adding further
complexity to the price volatility. The trend of regional or global recession followed by
every Oil price spike in the last few decades, directs towards the influence of world
affairs on crude Oil. Oil price is a complex phenomenon of multi-level mesh of supply
and demand, that a single aspect of those factors can influence volatility.
1
Table of Contents
1 Introduction .................................................................................................................. 6
2 Background ................................................................................................................ 10
2.1 Non-OECD ........................................................................................................... 10
2.2 Demand and Population Growth .......................................................................... 13
2.3 Demand and Income Growth ............................................................................... 14
2.4 Demand and GDP Growth ................................................................................... 15
2.5 OPEC ................................................................................................................... 17
2.6 Middle East Politics .............................................................................................. 19
2.7 Crude Oil Types ................................................................................................... 22
2.7.1 Macroeconomic Impact .................................................................................. 24
2.7.2 Market Fundamentals .................................................................................... 25
2.7.3 Market Conditions .......................................................................................... 26
2.7.4 Currency Impact ............................................................................................ 27
2.8 Inflation ................................................................................................................ 28
2.9 Recession ............................................................................................................ 29
2.10 War .................................................................................................................... 30
3 Methods ..................................................................................................................... 31
4 Analysis ...................................................................................................................... 34
4.1 Analysis: Non-OECD influence on Oil Price ......................................................... 34
4.2 Analysis: OPEC influence on Oil Price ................................................................. 36
4.3 Analysis: Benchmark reference price differential influence .................................. 40
4.4 Analysis: Global crisis influence on Oil Price ....................................................... 43
5 Conclusion ................................................................................................................. 47
2
References .................................................................................................................... 48
Appendix - Workflows.................................................................................................... 52
3
List of Figures
Figure 1 OECD & Non-OECD Consumption and WTI ................................................... 11
Figure 2 OECD & BRICS+1 population growth rate ...................................................... 12
Figure 3 OECD & BRICS+1 GDP growth rate ............................................................... 12
Figure 4 OECD & BRICS+1 GNI per capital (US$) ....................................................... 12
Figure 5 Private investments in transport sector ........................................................... 13
Figure 6 OECD and Rest of World GDP and PPP ........................................................ 15
Figure 7 WTI Spot Price & OPEC Production ............................................................... 18
Figure 8 OPEC production shares of member states .................................................... 21
Figure 9 Swings in Production Share & WTI ................................................................. 21
Figure 10 Select Crude Oil Price Points ........................................................................ 23
Figure 11 Spot Price (FOB) WTI and Brent ................................................................... 24
Figure 12 WTI-Brent Spread and US$ vs Major Trading Country Exchange ................ 28
Figure 13 WTI-Impact of Major global events............................................................... 29
Figure 14 Heat map: OECD and Non-OECD production change and Price fluctuation 35
Figure 15 ROC Analysis: Non-OECD Influence ............................................................ 36
Figure 16 Calibration Plot: Non-OECD Influence .......................................................... 36
Figure 17 Heat map: Iran & Saudi Production and Price influence ............................... 38
Figure 18 Parallel Coordinates: Iran & Saudi Production, Price influence and OPEC
output impact ................................................................................................................. 38
Figure 19 ROC Analysis: Saudi Influence ..................................................................... 39
Figure 20 Calibration Plot: Saudi Influence ................................................................... 39
Figure 21 Heat map: Brent and WTI-Brent price differential.......................................... 41
Figure 22 Heat map: Euro/USD and WTI-Brent differential ........................................... 42
Figure 23 Heat map: Cushing inventory against WTI and Brent price differential ......... 42
Figure 24 ROC Analysis: WTI-Brent price differential ................................................... 43
Figure 25 Calibration Plot: WTI-Brent price differential ................................................. 43
Figure 26 Heat Map: WTI and Price fluctuation from Global events .............................. 44
Figure 27 ROC Analysis: Global crisis events ............................................................... 45
Figure 28 Calibration Plot: Global crisis events ............................................................. 46
4
List of Tables
Table 1 Non-OECD Demand Categorization................................................................. 34
Table 2 Non-OECD Price Categorization ...................................................................... 34
Table 3 OPEC Production Categorization ..................................................................... 36
Table 4 OPEC Price Categorization .............................................................................. 37
Table 5 Price Differential Categorization ....................................................................... 40
Table 6 Brent Price Change Categorization .................................................................. 40
5
1 Introduction
Oil is an essential commodity of twenty-first century. The global economic engines are
willingly or otherwise heavily dependent on oil and its various byproducts. Access to
abundant and cheap oil plays a major role in world political landscape. Equally
noteworthy is the cost of Oil for production, export-import and consumption.
Developed countries drove the demand for energy primarily crude oil for a major part of
twentieth century. Developed economies, which forms Organization of Economic Cooperation and Development or OECD, until recently based upon their consumption
influenced the price for crude oil. The last couple of decade witnessed an astonishing
economic growth from countries outside OCED. The hunger to fuel the domestic
requirement of these emerging economies due to their growing population, industrial
and commercial growth have led to higher consumption of crude oil now than ever in the
past. The key component of emerging or developing economies are Non-OECD
countries, in particular Brazil, Russia, India, China and South Africa or BRICS, together
makes a market of over two-billion people and trillions of dollars of combined economy.
Their rate of progression in purchasing power, preceded by increasing income per
capita is difficult to match for the rest of the world.
The Organization of the Petroleum Exporting Countries or OPEC is the most influential
association of oil and gas exporting countries. With an estimated proven reserve of over
1,100 billion barrels (OPEC, 2015) OPEC member states holds in excess of eightypercent of worlds proven oil reserves. Saudi Arabia is a major partner in OPEC,
producing almost thirty- percent of the cartel’s daily production of thirty-one million
barrels per day. The Middle Eastern regional politics due to structural disparity on
governance, ideology as well religious belief affects OPEC’s unified production strategy
as a cartel. The rationale of protectionist exploitative tactic in OPEC is reflection of
member state’s differing economic and social interests.
Crude oil varies by substance and location. There are various types of crude – light,
sweet, sour and heavy, available around the world. The complexities generated through
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these variations have led oil traders to adopt reference products that offer close
relevance for their market. The existence of multiple reference benchmark products and
goal for maximizing profit depending on the production volume, currency exchange rate
and inventory have led to price differential in trading of oil.
Global events have played their share to fluctuate the price of oil. War, conflict,
instability, recession and political unrest have all contributed in the precautionary
demand for oil and its price. The development in global oil market has influenced
significantly in real income shifts between oil exporting and importing countries.
However, the impact of oil prices on individual countries depends on a wide array of
factors including the quantity of oil exported or imported, their cyclical positions, and
their effect from monetary or fiscal policy of the trading nation.
Dargay and Gately, (1995) reviewed the paths of world energy and oil demand over
time and relative to income growth. They outlined the demand in less industrialized
countries (LDC) is more responsive to income growth than industrialized countries
(OECD) and heterogeneous relationship between income growth and demand from
income growth in LDC. Galli, (1998) analyzed the non-monotonic relationship between
energy intensity and income in Asian emerging countries. Gately and Huntington,
(2002) studied the asymmetric effects on demand of changes in oil prices, the irregular
effects on demand of change in income and the rate of demand adjustment to changes
in price of oil and income for 96 of world’s largest countries by per-capita.
They
concluded OECD demand responds more to increases in oil prices than to decreases,
demand’s response to income decreases is unequal in Non-OECD countries and the
rate of demand adjustment is sooner to changes in income than price.
Difiglio, (2014) Rodríguez and Sánchez, (2005) examined the historical trend of oil price
shock followed by period of weak economic growth or recession and recession
preceeded by oil price shock. Difiglio reviewed the price-inelastic demand and supply of
oil that cause oil price shocks and relocation of capital and labor after oil price shocks
that freeze economic growth. Rodríguez and Sánchez performed empirical assessment
on the effect of oil price shocks on the economic activity of OECD countries. They
concluded evidence of non-linear impact of oil prices on GDP growth in both oil
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importing and exporting countries. Kilian and Hicks, (2013) established the fact that
growth of emerging Asia outperformed the forecast for the period of 2003-2008 causing
surge in the real price of oil.
Eckbo, (1976) concluded that OPEC is a segregation of three-part cartel structure
based on the production capability and need for cash. His division of the cartel
framework was hard-core members, price-pushers and expansionist-fringe. He
concluded that low discount rate and large resource base would interest a producer on
lower price trajectory for continuous robust future demand. Hnyilicza and Pindyck,
(1976) examined pricing policies of OPEC member states from the perspective of
spender and saver countries with varied needs for cash. They suggested that in the
two-part cartel framework at fixed output share the price approximates the optimal price
path however, if the output share are subject to control the optimal price path depends
on the bargaining power of individual blocks. Moran, (1981) modelled OPEC’s behavior
based on the maximizing economic benefit and concluded political decision-rules more
likely dominates the pricing policy of influential OPEC members over economic benefits.
He highlighted the implications of Saudi pricing policy on the future course of OPEC
prices.
Fattouh, (2011) analyzed the features of crude oil pricing system to study the link
between different financial layers and between the financial layers and main benchmark
reference crudes. Buyukasahin et al., (2013) examined fundamental and financial
differences between the two-reference benchmark: WTI and Brent. Their work showed
on the physical side storage capacity could affect the price non-linearly whereas on the
financial side they reviewed the dimension of commodity index trading (CIT) in the
energy market. Kao and Wan, (2012) discussed the declining trend of WTI in reflecting
market tendencies and Brent crudes gradual progression in substituting WTI for
processing information. Lizardo and Mollick, (2010) studied oil price and exchange
rates. They found oil prices significantly influence movements in the value of U.S dollar
against major currencies. Brunnermeier and Pedersen, (2009) provided an empirical
model that links market liquidity and funding liquidity. Their model indicated that
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government commitment to improve funding in potential future crisis could improve
market liquidity.
Hamilton, (2009) explored the similarities and differences between the price shock of
2007/08 and earlier shocks. Kilian, (2008) disintegrated the price shock into crude oil
supply shocks, shocks due to the global demand for commodities and demand shocks
specific to the crude oil market. Reinhart and Rogoff, (2008) Rubin and Buchanan,
(2008) have identified that almost all U.S. recessions were preceded by oil price shock.
In this paper, I have attempted to bring together major causes influencing the price of
crude oil and hence its volatility. I have supported the hypothesis of qualitative theories
from literature reviews with quantitative regression analysis and various mapping
techniques.
The paper divided into five sections. Section 2, discuss the background to the influence
on the oil price from OCED and emerging economies, OPEC, reference benchmark
crude oil spreads and global crisis of 1970-2012 period. Section 3, provides the
methods utilized to analyze the publicly available data retrieved from various
governmental agency and industry publication. Section 4, analyzes the hypotheses
based on visualization techniques as well as classification and regression algorithm
based widgets. Section 5, looks in the analysis and offers some conclusions.
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2 Background
2.1 Non-OECD
The formation of Organization of Economic Co-operation and Development or OECD
dated back to1960 with eighteen European countries along with United States and
Canada. The dedicated objective at the time of formation of the organization was to
make coherent efforts to the economic development of its member states. Today, the
organization grew to thirty-four Member countries around the world from North and
South America to Europe and Asia-Pacific. OECD’s focus has expanded to include
cooperation with civil society of non-Member states and key partners like BRICS
through business, industry and trade unions (OECD, 2015).
Hamilton, (2014) has mentioned oil demand for most of the twentieth century driven by
developed economies. Until 2005, the annual combined demand of these countries
grew at 440,000 barrels per day. Since, OECD comprises of Member states deemed
developed country, global oil consumption was dependent on the growth of OECD
economies. Since 2005, consumption of oil in OECD has fallen on average 700,000
barrels per day, averaging net intake of 8 million barrels per day by 2012. In this study,
Indonesia has also been included in the club of BRICS as BRICS+1. The growing
economies of BRICS+1 will drive their respective governments to continue to influence
the geopolitics for satisfying their energy security. The strategic petroleum reserves
build or in the process of making outside OECD are higher than ever. These emerging
economies have already started to shape the world economy and the supply demand
equilibrium of global crude oil exploration, production, trading, transportation and
consumption. On the other hand, demand for oil from emerging economies like BrazilRussia-India-China-South Africa and Indonesia (BRICS+1), which considered as part of
non-OECD economy grew at an astonishing rate (refer Figure 1). China on its own
accounted for fifty-seven percent increase in global oil consumption in the last decade.
One of the factors associated with continuing decline in demand for oil from developed
economies is slower growth in population (refer Figure 2). Although there is evidence of
spike in OECD population growth rate between 2007- 2011 but it was the result of
increase in net migration of population often in response to a business cycle or
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geopolitical event. According to a census, the period saw around thirty-five percent
increments in migration to OECD country in particular Germany within Europe and U.S
(OECD, 2014). Other factor contributed to lower consumption of oil in OECD is slower
GDP growth (refer Figure 3). BRICS+1 economies has maintained on average GDP at
seven-percent annual growth rate since 2000 as compared to average two-percent
growth in OECD. Another economic parameter, Gross national income (GNI) of
BRICS+1 economies saw shocking increment on average of thirty-five thousand dollars
per capita within a decade (refer Figure 4).
Huntington and Gately, (2002) has highlighted the differences across countries in the
relationship between energy growth and income growth. In OECD, most of the countries
had slower or sometime negative growth in demand of oil as compared to their income
growth. However, non-OECD countries exhibited much greater heterogeneity in the
growth in demand of oil and income level, sometime growth in demand of energy
exceeding or without the income growth. All the indicators are pointed towards nonOECD economies including BRICS+1 as the driver for the future demand for oil, in this
chapter we will review the relation between the demand of oil and growth in population,
income and GDP.
Figure 1 OECD & Non-OECD Consumption and WTI
1
1
Data Source: BP Statistical Review of World Energy, June 2013
11
Figure 2 OECD & BRICS+1 population growth rate
Figure 3 OECD & BRICS+1 GDP growth rate
3
Figure 4 OECD & BRICS+1 GNI per capital (US$)
2
3
2
4
Data Source: OECD Library
Data Source: World Development Indicators, The World Bank
12
2.2 Demand and Population Growth
Even though, the Figure 2 depicts the declining trend in the annual population growth
rate at an average one-percent annually. These two populous economies share
between them around 2.7 billion people or thirty-five percent of world population. The
rapid growth in population exerts pressure on the country’s infrastructure, transport and
commercial sectors.
Figure 5 Private investments in transport sector
5
According to an independent analyst, the total number of vehicle in operation
worldwide-surpassed one-billion units in 2010, with China and India recorded highest
growth in vehicle population since 2000 (Sousanis J, 2011). The increase in the global
motor vehicle population led to the surge in demand for oil. Although, oil will remain the
dominant fuel in transport it’s share will fall below ninety-percent by 2030 (BP, 2013).
The decline in market share of oil as the primary fuel for transportation also reflected in
the international energy outlook for the period 2000-2015. U.S. Energy Information
Administration (EIA) forecasted total energy demand for transportation at 37.5
quadrillion Btu in 2020 however, the estimate declined to 26.4 quadrillion Btu by 2040.
Energy consumption could fall most rapidly through 2030, primarily due to improvement
in light-duty vehicle (LDV) fuel economy with the implementation of fuel and greenhouse
gas emissions (GHG) standards in non-OECD countries. By 2020, alternative fuels like
electric or compressed natural gas (CNG) could replace nearly four-percent LDV fuel
4
5
Data Source: World Development Indicators, The World Bank
Data Source: World Development Indicators, The World Bank
13
consumption. According to a study conducted by Grand View Research, growth of
natural gas vehicles (NGVs) coupled with fuel efficiency of CNG and government
sponsored financial incentives are anticipated to contribute in the growth of CNG in
developing economies by 2020 (NASDAQ, 2015). Economic growth in the developing
nations along with low projected or in some instances, subsidized jet fuel prices could
yield nearly four-percent annual increase in air travel, resulting increase in jet fuel
consumption by 2.9 percent a year. (AEO, 1999) (AEO, 2015)
2.3 Demand and Income Growth
Dargay and Gately through their work have identified a number of factors that determine
the relationship between energy demand and income growth for an individual country
like the stage of economic development, the state of technology, energy endowments
and energy pricing policy. According to them, the economic development theory
consists of phases in the development process that generates implications in relation to
energy and income growth. Economic development generally accompanied by an
increasing energy income ratio maximizes at a certain point in time, followed by
gradually decline after a period of stabilization as the income continues to grow. As
developing and under developing economies continue to grow, the shift to more
industrial economy requires larger input of energy. Suri and Chapman have mentioned
that the structural composition of GDP first moves in favor of the energy intensive
industrial sector while the share of agriculture declines.
14
Figure 6 OECD and Rest of World GDP and PPP
6
This results in rapid increase in the demand for oil than growth in income. However at
higher stages of development as the GDP growth reaches a saturation point, the share
of energy intensive industry begins to fall while that of the non-pollution-intensive
service sector rises. The shift to newer or alternate forms of energy while the income
continues to grow, resulting in the decline of energy to income ratio. This phenomenon
supports the consumption of oil driven by demand and GNI per capita after 2000 in
OECD and BRICS+1 economy (refer Figure 6). The purchasing power parity (PPP)
used worldwide to compare the income levels in different countries emphasizes that the
GDP, PPP of the world economy excluding OECD is growing at a phenomenal pace.
The key contributors in the rise of global PPP to over fifty trillion dollar within a decade
are primarily non-OECD and low income country (LIC) economies.
2.4 Demand and GDP Growth
The industrial production growth used as an alternative representation for global real
economic activity saw unexpected increase in the demand for oil after 2002, largely due
to the growth from countries outside the OECD. Kilian and Hicks, (2013) in their findings
were consistent with the general worldwide perception of commodity boom driven by the
economic transformation of countries in Asia such as China and India from 2003
onwards. The assumption of demand for oil impacted by developments outside OECD
established, by the observation made on above average accelerated growth of world
6
Data Source: World Development Indicators, The World Bank
15
economy from 2003-2008 accompanied with growth shocks in China, Russia and
Japan. After 2008, the economic growth collapsed globally dragging with it the demand
and price for oil. The key factor for the demand of oil outside OECD to continue is the
sustainability of the economic growth of BRICS in particular China. Gau and N’Diaye,
(2009) has found that China’s growth relies on external demand and investment in
manufacturing. Exports contribute nearly thirty-percent of value added output of the
country making China’s market share of the global export to over nine-percent in 2008.
During the global financial crisis, China’s GDP growth declined significantly from the
average ten-percent (Büyükşahin & Robe , 2011) due to overdependence on exports
and lower demand from advanced economies. International Monetary Fund (IMF)
forecasted that the recovery of demand from China’s main trading partners might be far
slower than that assumed making the path for the country’s GDP to return to its usual
growth rate daunting. The organization assumes that by implementing policies to
increase domestic consumption through reform in the healthcare, education and
pension systems China could support growth sustainably in future. The fuel for
sustainable long-run GDP growth is energy security of uninterrupted supply of
petroleum imports, transportation and market access. This formed the foundation for
Strategic Petroleum Reserve (SPR). Difiglio, (2014) has explained according to IEA
treaty member states are required to hold petroleum or petroleum products to replace
90 days’ worth of their import however, the reported reserve figures from member states
are questionable and information of non-member country’s stockpile is sparse. These
government stocks in short-term do not influence the elasticity of oil supply as their
release are dependent on the government actions however, the volume of reserve and
rate of release of the emergency reserves has the potential to offset world-wide crude
oil supply demand equilibrium. Forbes magazine reported SPR exists as a tool for
market manipulation. Nevertheless, SPR grew into much bigger role in today’s world for
governments, as contingency to protect economies from oil price shock, national
security and emergency preparedness for military logistical support as well to promote
sentiment of stability among fellow citizens.
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2.5 OPEC
Five founding members – Iraq, Iran, Saudi Arabia, Kuwait and Venezuela, created
OPEC in 1960, the oil cartel as commonly known in Baghdad. Over the years, OPEC
grew to twelve-member oil exporting nations. Qatar, Libya, Nigeria, Angola, UAE,
Algeria and Ecuador joined the founding cartel members to coordinate and unify
petroleum policies in order to secure fair and stable prices for petroleum producers,
efficient and economic supply of petroleum to consuming nations and fair return on
capital to investments in oil and gas industry (OPEC, 2015). Ian Skeet, (1998) in his
book has described OPEC as an organization that has been held responsible for
destruction of world economy and international financial system as well as been
congratulated on releasing the third World from the grip of economic colonization. The
largest of the OPEC member and probably the most influential is Saudi Arabia. Saudi’s
exercise major role in OPEC’s price and production decisions. The characteristic to
model OPEC’s behavior as the best predictor of the cartel's price and production
decisions provided by economic self-interest that is consistent with the Kingdom’s
policy. Although, political decisions produce short-term deviations from the economic
route and exogenous events like wars or revolutions could remove capacity from
production causing sudden spike in the price of petroleum. However, the common belief
is the most likely price for OPEC oil will be the best price for OPEC oil, that is, the price
that maximizes the economic benefits received by the cartel. A timid price policy
deprives member states of revenue. An adjusted revenue stream reflects the impact of
price on the structure of supply and demand whereas a discounted revenue stream
reflects the income lost. However, aggressive price policy acts counterproductive by
inducing protection and damaging growth of consuming economies. The successful
cartelization of a nonrenewable resource comes from the manipulation of the rate of
exploitation, and the consequent shape of the price trajectory, over the life of the
resource (Lizardo R.A. & Mollick A.V., 2010). The rationale behind monopolistic
approach for self-interest suffers in OPEC as individual governments of the cartel have
differing economic interests depending upon their domestic social pressures including
religious divisions, revenue needs, alternative sources of export earnings and fiscal
income, hard currency financial assets, and geological reserves. Hnyilicza and Pindyck,
17
(1976) have divided OPEC into two groups: saver countries comprising Saudi Arabia,
Libya, Iraq, UAE, Bahrain, Kuwait, and Qatar and spender countries including Iran,
Venezuela, Indonesia, Algeria, Nigeria, and Ecuador based on the cartel’s membership
in 1976. The groups differ according to two variables: high or low immediate cash needs
and large or small proven reserves. Their analysis for an optimal solution lead to the
conclusion that since saver-country oil losing its value less rapidly, the production can
be reduced or dropped significantly while the spender-country oil is produced based on
two important facts. First, within the optimization framework the actual price-path for
OPEC depends heavily upon the relative balance in cartel policy formation among the
individual OPEC governments and second, that the stakes for these individual states in
approximating their optimal price and production policy are extremely large. Eckbo,
(1976) has divided the cartel into three categories to determine its behavior based on
the cartel’s membership in 1976. First category members or hard-core, could expand
could expand output substantially at a lower price like Saudi Arabia, Kuwait, UAE,
Qatar, and Libya. The second category or price-pushers, does produce close to
potential and have a strong need for income like Iran, Venezuela, Algeria, and Gabon.
The third category member states or expansionist-fringe, have smaller reserves than
the core, have strong need for income, but produces at a slower rate of depletion than
the price-pushers like Indonesia, Nigeria, Iraq and Ecuador.
Figure 7 WTI Spot Price & OPEC Production
7
7
Data Source: BP Statistical Review of World Energy, June 2013
18
Eckbo’s analysis concluded that given a low discount rate and large resource base, a
country like Saudi Arabia should be motivated to choose a lower price trajectory
because it is less attracted to quick profits than the price-pushers and more concerned
about the robust state of future demand. Willett, (1979) and Singer, (1978) has stressed
on two vital characteristic of higher oil price. First, Saudis will be required to bear
unequal production cutback within the cartel, and second large stake of the Saudis in
the success of the cartel will make it risk-averse against the threat of possible collapse
that higher oil prices would produce. It is evident from the above arguments that Saudi
preference on lower price is economically best-optimized solution for the future of the
Kingdom and their intention to flood the market with excess oil to reduce the demand
and hence the crude oil price. However, it also emphasis the penalty the hawkish
members of cartel like Iran and Venezuela have to pay if Saudi preferences
supersedes. Consequently, the disagreement among the cartel’s divergent economic
interests is intense and that there is no intuitively logical or rational formula based on
economic self-interest for adjusting the conflicting interests of the cartel members
(Lizardo R.A. & Mollick A.V., 2010). Thus, precedence of intra-cartel bargaining for a
preferred price path has been the norm lately and geo-politics has greater influence in
the price negotiation.
2.6 Middle East Politics
Saudi Arabia’s political influence and impact as a fallout of international policies has
greater impact on the oil price more than any other OPEC state. The structural division
between Saudi Arabia and Iran is well known. The differences between these OPEC
members apart from Eckbo’s categorization are their ideology. The political and
governance in Saudi Arabia and Iran differs as the philosophy of the Islamic Republic
rejects the monarchial regimes in Saudi Arabia and other Arab states. The legitimacy of
clerical authority and quasi-democratic institution in Iran seen by many as direct threat
to dynastic privilege and custodianship of Islamic holy sites of al-Saud family in Saudi
Arabia. However, post-Saddam middle-east saw the tension between these regional
powers escalated to new highs with Tehran’s view of Riyadh as America’s proxy and a
barrier against Iran’s rightful primacy in the region while Riyadh’s worry about Tehran’s
asymmetric power, regional ambitions, growing influence in Iraq and alleged pursuit of
19
nuclear weapon. Besides, the sectarian differences of Sunni-Shi’a divide and continuing
marginalization of Shi’a minorities in gulf cooperation council (GCC) region factors into
the calculus of the leadership of the two states and are either encouraged or
downplayed as a tool in larger geopolitical maneuver. U.S. and Saudi interests aligned
against Iran in more than one-way primarily Tehran’s alleged continuation of proxy
against Tel Aviv through Hezbollah in Lebanon viewed as threat for the U.S. ally in the
region. However, recent unilateral de-escalation of U.S. rhetoric and lifting of sanctions
on Iran combined with broader Gulf engagement with Tehran viewed as a game
changer for Saudi dominancy with other Arab states. The recent lifting of Iranian trade
embargo by U.S. led allied could see rise in production level of the Persian state
exerting further pressure on Saudi Arabia’s price policy and politics behind oil. Closed
society and privacy around Saud dynasty did not prevent people for casting doubts on
the royal family’s succession challenge. Divisions within Saudi royal family obsess the
western diplomats, journalists and researchers, as well Saudi exiled dissidents. The
lack of institutionalized succession procedures considered as the most glaring threat to
the elite unity. The principle of primogeniture does not exist in Arab-Islamic tradition
rather value of ‘the eldest and most able’ takes the center stage in Arab tribal culture.
This formed the basis of various rumors that have indicated power struggle following
King Fahd’s illness between apparent heir Abdallah and other Sudayri brothers,
similarly following King Salman’s appointment of Prince bin-Nayef as crown prince
shaking the line of succession to the throne. Saudi royal family exercises influence on
the oil policies of the country and OPEC. Since, succession is a major hurdle for the
stability of any family dynasties and strength in administrative policy and governance, a
stable royal family is in the best interest for global oil production.
20
Figure 8 OPEC production shares of member states
Figure 9 Swings in Production Share & WTI
8
9
Eckbo’s characterization of OPEC is evident from the production of cartel’s member
states since 1976. Saudi’s tussle for market share and the dominancy in OPEC and
Middle East region as well Iran’s drive to lift the spot crude price index being a ‘pricepusher’ is apparent in Figure 9. In particular, the months following Iranian hostage crisis
and U.S. sanction on Iranian oil imports 1979-1981, saw steep decline in production
from the Persian state (Hostage Crisis, 2013). Although the crisis was marked with,
WTI spot price increment by nearly hundred twenty-four percent from $14.6 to $ 38 per
8
9
Data Source: BP Statistical Review of World Energy June 2013
Data Source: BP Statistical Review of World Energy June 2013
21
barrel, but it was also the period that brought Saudis closer to west through their efforts
to cool the spot price futures by pumping record oil in the market and claiming the
primacy in Arab world. The result of the record production from Saudi Arabia followed
by Kuwait opportunistic production increment also marginalized WTI price volatility,
even with drop in Iraqi and Iranian production during the eight years of Iran-Iraq conflict
(Imposed War, 2011). Middle East region is prevalent with various forms of autocratic
rules. However, the authoritarian regimes have made OPEC a dominant force in global
economy over the years by assuring stability and consistency to the oil production from
the region. The uprising in Arab world also known by ‘Arab Spring’ since 2010 has seen
the downfall of many authoritarian regimes in the region but that has not led to any
region-wide democratic reforms. As an aftermath of Arab Spring, particularly in Libya,
Syria and Iraq the production dropped to phenomenal level threatening the very
establishment of OPEC. The lack of governance, security and control in these affected
areas under numerous pseudo-governments and militias are threatening to spill into
neighboring countries. Emergence of Islamic fundamentalism is on the rise. The region
that believed to have given birth to this extreme form of Islam is in itself jolting with the
threat. Arab Spring brought the resentment of people on their regimes out on the street.
Patronage spends post Arab Spring is on the rise in existing Middle Eastern regime
controlled states as a sought to smooth dissent. The region that is ever increasing is
dependency on oil revenues to fight proxy wars, counter internal dissent, tackle
fundamentalism and to maintain primacy with sister states, the effect of regional politics
plays sizable role in geopolitical arena.
2.7 Crude Oil Types
There are many types of crude oil produced in the world characterized by their density
and Sulphur content. Density ranges from light to heavy while Sulphur content
characterized as sweet or sour (refer Figure 10). Light and sweet crude oils priced
higher than heavy and sour crude oils because they gets processed with far less
sophisticated and energy-intensive procedures. Gasoline and diesel fuel, which sells at
a premium from the crude price can usually be, produced economically using light,
sweet crude oil (Fattouh, 2010). The complexities of oil due to the substance and
location led oil traders to adopt reference products whose prices reflect relevant
22
characteristics for their particular markets. While the reference products make efficient
price discovery for similar substance of crude oil, the price of non-reference products
also improves as they too priced regularly off a reference. Today, the dominant
reference products used in oil trading for pricing mechanism and hedging are West
Texas Intermediate sweet crude (WTI) the primary benchmark in the Americas and the
European benchmark, Brent crude. Even though, wide variety of crude oils produced in
the U.S., WTI assumes special importance in the global oil and financial markets as it
underlies one of the largest traded commodity futures, the light sweet crude futures
contract. Brent is a crude grade primarily produced from North Sea. Although, North
Sea consists of a wide variety of grades but over the years low physical production
caused distortion, manipulation and squeezes leading Brent price to disconnect from
the rest of grades. Hence, the Brent system comingled with Ninian-Forties-OsebergEkofisk grades by 2007 to form the current benchmark BFOE or as commonly referred
Brent3. Brent market was not predesigned and grew in complexities according to the
needs of the market participants. Today nearly, seventy- percent of the international oil
trade directly or indirectly based on the price generated in the Brent complex.
Figure 10 Select Crude Oil Price Points
10
10
Data Source: U.S. Energy Information Administration
23
As Kao and Wan, (2012) have mentioned, over the years technological advancement
and demand has favored WTI. This could be the fact that the largest economy, U.S.
was the single biggest source of demand for oil in the past. However, with the rise of
Asian economies the demand for oil is no longer restricted to North America. This along
with the similarity in the physical property of the two reference products has led to the
small differential in the trading of WTI and Brent with WTI usually priced slightly higher.
However, that trend has changed post 2008 financial crisis. The rationale behind price
differentials between WTI and Brent can be categorised into macroeconomic impact,
market fundamentals and market conditions.
2.7.1 Macroeconomic Impact
There has been infrastructure bottleneck in shipping oil within North America, as the
pipeline capacity did not adapt to the growth of crude oil production in the continent. The
feasibility of new pipeline investment not only requires long-term commitment on supply
and volume but also shippers are increasingly hesitant in committing large volume into
Figure 11 Spot Price (FOB) WTI and Brent
11
a specific market for long term (Curtis et al., 2014). This along with regulatory
constraints from federal and state authorities delayed sanctioning of new pipeline
projects leading to discounted price of Canadian, Bakken and other North American
crude at delivery point in Cushing, OK. The resurgence of shipment of oil by rail in
recent times has allowed companies to move crude oil to favorable coastal markets and
receive Brent pricing instead of discounted Cushing price without regulatory hassle.
11
Data Source: US Energy Information Administration
24
However, according to EPRINC cost to move crude within continental U.S. by rail can
range from 10 to 15 dollar per barrel, which outdoes its economic benefits over building
pipelines. These infrastructure bottlenecks caused hindrance in the movement of crude
from delivery point to Gulf Coast along with building glut of crude storage at Cushing.
Alternatively, to the oversupply, the storage capacity at Cushing is available to both
sweet and sour WTI, constraining available storage capacity for either of the crude
types. The low spare capacity at Cushing affects negatively to the delivery of expiring
WTI contracts. These circumstances changed the cost-of-carry and prompted
adjustment in price dynamics for WTI post 2008-09 financial crisis but not for Brent. In
between 2011-2015, weightage of Brent oil in S&P GSCI commodity index increased
from 15.9 to 24.7 percent (S&P Dow Jones Indices, 2014). The Brent’s increase came
at the cost of WTI. Besides S&P index, Brent’s introduction to Dow Jones DJ-UBS saw
billions of dollars as investment funds reallocated from WTI. Gromb and Vayanos,
(2010) have also highlighted index effect, addition or deletion from prominent market
indices like S&P’s 500 index raises the price of the stock as we have experienced with
Brent. The WTI-Brent spread before and after the alteration in weightage of indices,
complemented the theory behind changes in commodity paper-market positions and
prices (Buyukasahin et al., 2013).
2.7.2 Market Fundamentals
Comparing to other commodities, the price of crude oil is not exceptionally volatile.
However, like most other commodity, supply and demand acts as the market
fundamentals in crude price. We have seen in the previous section, the storage
constraints, transportation bottleneck to Gulf Coast, new North American supply source
like Canadian and Bakken oil amid glut of crude at delivery point in Cushing without
significant hike in demand, resulted in WTI-Brent spread moving apart. Prior to 2007,
the logistical bottleneck to move oil to Cushing resulted WTI futures to move very high
as compared to other benchmarks. The pressure on WTI price also comes from excess
OPEC supply outside Saudi Arabia. Saudi produces both Arab light and heavy crude,
much different from sweet crude oil of WTI and Brent, but Saudi refineries cannot easily
switch production type to influence the price index of either of the reference crudes.
Besides, there have been more questions raised on the Saudi excess capacity reported
25
in recent times, so OPEC production outside the kingdom influences WTI. The effect of
Arab Spring since 2011, casted political risks on Middle Eastern crude oil supply. The
risks aggravated following Libyan crisis when the civil- unrest in that country cut-off a
large source of sweet crude oil from the market. Nuclear disaster following Tsunami
increased Japan’s demand for fossil fuel otherwise fulfilled by nuclear energy. European
refineries built decades ago were primarily concentrated on increasing gasoline
production in the continent, however these high-octane fuels popular for efficiency
during industrial revolution were gradually replaced by diesel over last few decade for
lower emission. As such, gasoline-refining capacity in Europe dropped on average twomillion barrels per day (P.K. Verleger, 2011). Market fundamentals, shrinking refining
capacity along with gradual decrease in Brent’s production post 2012 have exerted
upward pressure on seaborne crudes like Brent, and the WTI-Brent spread that started
separating in 2010 moved further apart.
2.7.3 Market Conditions
Theoretically, the greater the liquidity in derivative market the weaker it gets in the spot
market7. According to Brunnermeier and Pedersen, (2009) funding that drives market
liquidity depends on margin. Fragility and liquidity arise when the margin requirements
are destabilized or if the trader’s existing positions are in accordance with customer’s
demand. Gromb and Vayanos, (2010) have stated that there are two kinds of traders:
outside investors and arbitrageurs. While outside trader’s demand of asset is inelastic
and equal, arbitrageurs are competitive and risk averse. The possibility of financial
market stress, often limits the ability and willingness of both kinds of traders to involve in
cross-market arbitrage. Commodities are gradually becoming integrated part of any
investment portfolio and the amount of money invested globally in commodity indices
has grown over ten folds between 2003 and 2008 (Brunnermeier, M. K. & Pedersen, L.
H., 2009). Commodity index traders (CITs) are the people driving the investment in
commodities. U.S. Commodity Futures Trading Commission (CFTC) collects daily
information on the positions of every large trader at the close of each of these markets
as well as information on each trader’s purpose for trading and main line of business7.
As index trades represent futures, there is a growing interest to determine the impact of
CIT’s activity on commodity price levels in WTI or Brent futures and WTI-Brent future
26
price spread. The reliability of the pricing mechanism and the effectiveness of hedging
strategies relying on benchmark products, however, depend on the predictable
differences between the price of reference products and the prices in markets of nonreference products (Buyukasahin et al., 2013).
2.7.4 Currency Impact
The interaction between financial market and crude oil has been growing since last
decade and the link between oil and currency market is well established (refer Figure
12). According to Zhang et al., (2008) as US dollar is the major invoicing currency in
crude oil market, strong green buck has adverse effect on oil-importing countries.
Subsequently, the volatility of US dollar casts unpredictability on the behaviour of oilexporting countries. Reboredo, (2012) has identified that most of the studies direct
towards negative relationship between crude oil price and US dollar rate. From 2002 to
2007, WTI-Brent spread moved from twenty-dollars to over ninety-dollars per barrel and
in the same period, the US dollar has fallen by twenty-eight percent against the
currencies of major trading partners. Lizardo and Mollick, (2010) has identified that the
US dollar has lost sixty-five percent against Euro in the same period. Brent in spite of
being a European benchmark reference traded in US dollar. The depreciating dollar
makes oil cheaper for oil-importing economies and thus affects the demand for the
black gold, which ultimately pushes the price. Besides, weaker US dollar attracts foreign
investors to reduce non-US dollar denominated assets. Some oil exporting economies
also like to peg their currency with US dollar in order to stabilize their export in US
currency and import in non-US currency.
27
Figure 12 WTI-Brent Spread and US$ vs Major Trading Country Exchange
12
2.8 Inflation
Historically, the correlation between oil price swings and inflation has wide influence
across countries. During the era of hundred plus dollar barrel of oil there was stagnation
in the economic growth of oil importing countries. Likewise, at lower oil prices similar to
the trend reflected since 2014 the impact varies across countries. The effect of lower
price of oil replicated in the growth of oil exporting economics both within and outside
OPEC, impact on currency exchange rate, the monetary policy of oil importing nonOECD and emerging economies because of economic slowdown in OECD and equity
market meltdown of many emerging economies. The price of oil is concomitant to
capital in or out flows, currency reserve buildup or loss, sharp depreciations or spike in
sovereign debt in oil exporting or importing nations.
12
Data Source: The World Bank
28
Figure 13 WTI-Impact of Major global events
13
2.9 Recession
Many studies have indicated that high oil price gives rise to recession (refer Figure 13).
Tverberg, (2012) in his paper acknowledged that in the United States, four out of five
recessions receded by oil shocks between 1970-2007. Hamilton, (2009) based on a
review of the historical record, specifies that in the United States, eleven out of twelve
recessions since World War-II preceded by oil price shocks. Lower demand during
recession leads the way or price of oil to decrease. However, demand starts to increase
in the parts of the world that are not subject to recession. Inadequate oil supply during
growing demand tends to raise prices, if prices rise sufficiently, recession sets in and
prices fall again. This pattern gives rise to oil price oscillation. The oil price shocks tend
to have moved billions of dollars in income from OECD economies with typically very
low savings rates to higher savings rate provided economies. The redistribution of
income from oil-consuming countries to oil-producing countries is far from demand
neutral of world economy. Reinhart and Rogoff, (2008) has studied that historically from
the time Napoleonic War global economic factors like commodity prices play a major
role in sovereign debt crisis. They used a range of real global commodity price indices
from 1800 to 2006, the peaks and troughs in the commodity price cycles represented
leading indicators of capital flow cycle. Tverberg in his paper has referred the work of
Brown et al. for an analysis of extensive global data to emphasis energy’s role in
imposing fundamental constraints on economic growth and development. The spike in
13
Data Source: U.S. Energy Information Administration
29
the price of oil allows the domestic debt build-up of oil importing economies. Global debt
crises have often radiated through commodity prices, capital flows, interest rates, and
shocks to investor confidence. The US, Asian and lately European financial crisis have
all casted uncertainties on the global economic recovery and long-run demand affecting
the price of oil repeatedly.
2.10 War
Kilian, (2008) in his paper highlighted the role of exogenous events such as war or
revolution on the real price of oil because of their effect on precautionary demand for oil.
The oil-market specific demand shocks are reflection of perception on disruption of the
supply of oil. The Iranian revolution and Khomeini’s arrival in 1979, Iranian hostage
crisis and Soviet invasion of Afghanistan in 1980, Iran-Iraq war in 1986/88, invasion of
Kuwait in 1990/91 and 9/11 twin tower attack all affected the price of oil. The impact on
oil price was result of short-run supply shocks and on long-run precautionary demand.
Precautionary demand could trigger the perception that war or instability would result in
the supply disruption due to destruction of oil fields, infrastructures and eventual supply
routes to meet the demand of economic activity of the rest of the world or would lower
the future dependent on fossil fuel as observed post 9/11. Historically, when supply of
oil affected to need of demand rich economies due to conflict or war, interests of market
share and short-run profitability of OPEC and non-OPEC states have met the supplydemand gap. Iran-Iraq war in 1986/88 saw record increase in Saudi and Kuwaiti
production, similarly invasion of Kuwait saw increase in output from Saudi Arabia, Iran
and Venezuela.
30
3 Methods
Data is a reinterpretable representation of information in a formalized manner suitable
for communication, interpretation or processing (University of Minnesota, 2015). Data
can include observational data, experimental data, simulation results, documented
analysis and physical articles or relics. Data mining is the process of analyzing the data
from various viewpoints and generalizing it into useful information (Palace, 1996).
In this paper, for the period of 1970 to 2014 I have retrieved crude oil production data of
various geographical locations from BP statistical review of world energy 2013, various
financial data from The World Bank, WTI-Brent spot price and other information from
U.S. Energy Information Administration. I have used Orange data mining toolbox v2.7.
Orange is a machine learning and data mining software for data analysis through
Python scripting and visual programming. Orange is free software released under
general public license (GPL) by University of Ljubljana. The code hosted on Bit bucket
repository (https:// bitbucket.org/biolab/orange). The software can use Windows, Mac
OS X and Linux operating systems and can install from the Python Package Index
repository. (Janez Demsar et al., 2013) Orange consists of a canvas interface onto
which the user places widgets and creates a data analysis workflow (refer Appendix Workflows). Widgets offer basic functionalities such as reading the data, showing a data
table, selecting features, training predictors, comparing learning algorithms, visualizing
data elements, etc. The user can interactively explore visualizations or feed the selected
subset into other widgets.
I have analyzed the hypotheses based on heat map technique to provide 2-dimensional
visualization for continuous attributes and discrete attribute as well logistic regression
and naïve Bayesian learners to determine the receiver operating characteristic (ROC)
curve and calibration plot.
In statistics, classification is the problem of identifying category an input observation
belongs from the pre-defined set of categories. Alpaydin, (2009) has defined the
terminology of machine learning classification as an instance of supervised learning, i.e.
learning where a training set of correctly identified observations is available. The
31
corresponding unsupervised procedure known as clustering involves grouping data into
categories based on some measure of inherent similarity or distance.
Logistic regression is a statistical method for analyzing a dataset in which there are
multiple independent variables to determine an outcome. The result measured with
option of only two possible outcomes. The goal of logistic regression is to find the best
option to describe the relationship between the dependent variable and outcome
variable and a set of independent variables. This Orange widget provides a graphical
interface to the logistic regression classifier. This widget provides a learner and
classifier on the output. Learner is a learning algorithm with settings as specified by the
user. It provides input into widgets for testing learners, for instance Test Learners.
Classifier is a logistic regression classifier, built from the training examples on the input.
Naive Bayes methods are set of supervised learning algorithms based on applying
Bayes’ theorem with the “naive” assumption of independence between every pair of
features. The different naive Bayes classifiers differ mainly by the assumptions they
make regarding the distribution between every featured pairs. According to Poole and
Mackworth, (2010) Bayesian learning used to compute the posterior probability
distribution of the target features of a new example conditioned on its input features and
the entire training example. This Orange widget like logistic regression provides a
graphical interface to the Naive Bayesian classifier. Classifier is a Naive Bayesian
Classifier, built from the training examples on the input.
The receiver operating (ROC) curve is the graphical representation of performance of a
binary classifier system. The curve plots the true positive rate against the false positive
rate between sensitivity and specificity. Sensitivity and specificity are one approach to
quantify the diagnostic ability of the test. Altman and Bland, (1994) defined sensitivity as
the proportion of true positives that correctly identified through the test and the
specificity is the proportion of true negatives. A high sensitivity test is reliable when
higher is the number of true positives among all the samples. The Orange widget of
ROC curves shows the tested models and the corresponding convex hull. The features
of costs of false positives and false negatives can also determine the optimal classifier
and threshold. The widget can represent performance line, which changes as the user
32
changes the parameters. The points where the line touches any of the curves
considered as the optimal point for any of the given classifiers.
A calibration curve is a general method of determining the concentration of a substance
in an unknown data set by comparing the unknowns to a set of known samples. The
curve plot demonstrates the accuracy of the calibration of the classifiers. In analytical
techniques, the curve provides dependable methods to calculate uncertainty in a data
sample as well information on empirical relationship. The Orange widget of calibration
plot chooses the target class as positive class by default. In case there are more than
two classes, the widget considers all other classes as a single, negative class. If the test
results contain more than one classifier, the user can select the curve needed for
consideration.
33
4 Analysis
4.1 Analysis: Non-OECD influence on Oil Price
The future demand and price fluctuation for crude oil will be coming from regions
outside the OECD. The yearly change in recorded consumption for both categories
referred in the analysis as OECDCh and NOECDCh. Assumptions made that the
consumption is equivalent to the demand and the demand categorized as above,
average and below.
Table 1 Non-OECD Demand Categorization
Category Range
Below
Average
Above
Lower limit (K bbl.)
-300
-600 to -301
Less /equal -601
Upper limit (K bbl.)
300
301 to 600
Greater/equal 601
Similarly, WTI spot price (FOB) at Cushing, OK referred for the purpose to determine
the price fluctuation on the yearly basis referred in the analysis as PCAT. The price
fluctuation categorized as high, medium and low.
Table 2 Non-OECD Price Categorization
Category Range
Low
Medium
High
Lower limit (US$/bbl.)
-5
-10 to -5.1
Less /equal -10.1
Upper limit (US$/bbl.)
5
5.1 to 10
Greater/equal 10.1
Heat map visualization used for analyzing change in OECD and Non-OECD
consumption and WTI price change, that impacts the Non-OECD demand. The plots
(refer Figure 14) represent distinguishing characteristic, OECD consumption variation
influenced WTI spot price however; the impact is more noticeable as negative demand
i.e. when the consumption from OECD reduced the WTI price dropped though the data
events in recent times are minimal. Whereas, the Non-OECD consumption influence on
WTI is due to increase in demand. It is evident since only from year 2000 onwards the
influence of BRICS demand for oil has grown and the data samples could be related to
the fact, crude pricing in future will be in correlation to the demand from outside OECD.
34
Figure 14 Heat map: OECD and Non-OECD production change and Price fluctuation
The ROC analysis curves (refer Figure 15) depicts that the data points that categorized
demands as ‘above’ and ‘below’ have larger area under the curve and thus accurate as
compared to data points that categorized demands as ‘average’ making a 45-degree
diagonal. Calibration plot curve (refer Figure 16) is the method that shows the accuracy
of the calibration of the classifier. These plots further verify the hypothesis as the
diagonal ‘above’ curve resembles a perfectly calibrated classifier.
The review of the GDP growth outside the OECD, along with the demand for access to
uninterrupted crude oil supply from the region is going to continue its influence on the
world oil. The analyses have verified the trend hypothesis that the requirements and
consumption of BRICS will influence highly the volatility of the crude oil price in future.
35
Figure 15 ROC Analysis: Non-OECD Influence
Figure 16 Calibration Plot: Non-OECD Influence
4.2 Analysis: OPEC influence on Oil Price
Historically the data sample from 1976 – 2012, identifies the policies of Iran, Iraq, Saudi
Arabia and Kuwait within OPEC has been the major causes of influence on the cartel’s
overall production and global oil price. The annual change in recorded production
percentage for the above stated member countries and OPEC calculated, referred in
the analysis (in that order) as IrCng, IqCng, SACng, KwCng and OPECng respectively.
The change in production categorized as, steep, moderate and normal.
Table 3 OPEC Production Categorization
Category Range
Normal
Moderate
Steep
Lower limit (%)
-3.0
-7.0 to -4.0
Less /equal -8.0
Upper limit (%)
3.0
4.0 to 7.0
Greater/equal 8.0
36
Similarly, WTI spot price (FOB) at Cushing, OK for the purpose to determine the price
fluctuation on the yearly basis in the analysis denoted as PrCng. The price fluctuation
categorized as high, medium and low.
Table 4 OPEC Price Categorization
Category Range
Low
Medium
High
Lower limit (US$/bbl.)
-3
-4.1 to -3.1
Less /equal -4.1
Upper limit (US$/bbl.)
3
3.1 to 4.1
Greater/equal 4.1
Among the four member states selected, Iran and Saudi Arabia’s stride for market share
has the biggest influence on crude supply and market price. The heat map technique
used to provide percentage change in Saudi and Iran production and change in price of
WTI (refer Figure 17). The plot represents minor change in production from either one
or both these states has affected the WTI price for a short run. Major change from Iran’s
production has minor impact on WTI, indicating it would be Saudi excess production
and urge for market share that would oversupply the demand for oil as it occurred
during Iraq-Iran conflict. Multi-dimensional data visualization technique (refer Figure 18)
known as Parallel Coordinates, include attributes IrCng, SACng, OPECng and PrCng.
From 1977-2012 overall, 36 visualized attributes used to connect to each vertical line
between the maximum and minimum points at the appropriate dimensional value. The
correlation between neighboring attributes plotted with the intent of identifying
visualization with the highest sum of the absolute value of correlations between
neighboring attributes. The correlation between change in Saudi and Iran production
and impact on OPEC’s output is primarily moderate to normal indicating that the trend is
usually one of these OPEC member state will seal the decline in production by
increasing their market share. In the past 36 years, only occasionally OPEC’s total
share saw a steep change due to either of Saudi or Iran’s production. However, the
production fluctuation from either or both of these states resulted in high volatility of
crude price since 1977. While the crude price tendency been heavily sensitive to any
change in Saudi’s production profile, Iran’s ability to influence the price volatility is
limited for normal to moderate change. The ROC analysis curves (refer Figure 19)
depicts that the data points that categorized price volatility as ‘high’ has largest area
37
under the curve among the rest and thus technically more accurate as compared to
data points that categorized price volatility as ‘medium’ and ‘low’ making a 45-degree
diagonal.
A calibration plot curve (refer Figure 20) verified the hypothesis as the
diagonal ‘high’ curve resembles a perfectly calibrated classifier.
Figure 17 Heat map: Iran & Saudi Production and Price influence
Figure 18 Parallel Coordinates: Iran & Saudi Production, Price influence and OPEC output impact
38
Figure 19 ROC Analysis: Saudi Influence
Figure 20 Calibration Plot: Saudi Influence
Saudi Arabia has been successful in orchestrating crude price crash by over supplying
the market. The data mining manifests the interest of Saudi Arabia in lower oil price that
would permanently shut its competitors including OPEC member states from
envisioning production increase. This policy has secured the kingdom is playing
dominant role as an influential power in world economy. Iran on the other hand has
been partly effective to ante the intention of Saudi’s by establishing itself as a
dependable long-term global supplier for oil. Being the largest among the OPEC
producer, Saudi’s policy on oil production has deep impact on the price volatility, which
is evident from the plunge of oil price in 2014, but the long-term sustainability of Saudi
strategy and their economic impact in unknown.
39
4.3 Analysis: Benchmark reference price differential influence
The various macroeconomic as well as market fundamentals and conditions
unfavorable to WTI, has benefited Brent to differentiate itself as higher priced crude oil.
Primarily being a North Sea crude type, Brent production data assumed to the
combined production of United Kingdom and Norway. The annual recorded production
from United Kingdom and Norway from 1987-2012, referred in the analysis as BPROD.
The annual price differential of the benchmark reference crudes (WTI-Brent) referred in
the analysis as PrDiff. The historical month-end spare inventory reported from 20042015, referred in the analysis as CSTOK, retrieved from EIA (Cushing, OK ending
stocks of crude oi), Aug 2015. The price differential (PrDiff) of the benchmark reference
crudes categorized as high, medium and low.
Table 5 Price Differential Categorization
Category Range
Low
Medium
High
Lower limit (US$/bbl.)
Upper limit (US$/bbl.)
-3.0
-7.0 to -3.1
Less /equal -7.1
3.0
3.1 to 7.0
Greater/equal 7.1
The percentage change in spot price for Brent for consecutive years, referred in the
analysis as BCng. BCng categorized as steep, moderate and normal.
Table 6 Brent Price Change Categorization
Category Range
Normal
Moderate
Steep
Lower limit (%)
Upper limit (%)
-7.0
-25.0 to -8.0
Less /equal -26.0
7.0
8.0 to 25.0
Greater/equal 26.0
The heat map of change in price differential (PrDiff) of Brent and WTI with BPROD and
percentage change of Brent price (BCng) plots (refer Figure 21) resembles positive
trend for Brent pricing. As the Brent production increases, the price differential between
the reference benchmark crudes is ‘steep’ i.e. Brent crudes increase market share
comes at the cost of lower WTI spot price. Further, heat map (refer Figure 22) used to
analyze change in price differential (PrDiff) of Brent and WTI with US dollar exchange
40
against Euro and price differential category of benchmark references. The plot
represents distinguishing characteristic, the higher price difference between the WTI
and Brent is visible when the US dollar trades at higher discount to Euro. Similarly, the
technique used to determine the trend of Brent and WTI spot price as the spare
inventory level varies at Cushing, OK (refer Figure 23). The plots represent no
distinctive characteristic. As the inventory builds up the impact on Brent price is high i.e.
due to the assumption that the spare capacity contract on a long term is possible. The
inventory benefits WTI, however since Cushing is primarily used for sweet and sour light
crude storage buildup could trigger less capacity for either one of both types of crudes,
which would be unfavorable in long-term contract commitments. Alternately, maximum
storage also damages the future pricing of the benchmark reference crudes, as that
could be an indicator for declining trend in the demand for oil.
Figure 21 Heat map: Brent and WTI-Brent price differential
41
Figure 22 Heat map: Euro/USD and WTI-Brent differential
Figure 23 Heat map: Cushing inventory against WTI and Brent price differential
The ROC analysis curves (refer Figure 24) depicts that the data points that categorized
price differences as ‘high’ and ‘low’ have larger area under the curve and thus accurate
as compared to data points that categorized as ‘medium’ comparatively. Calibration plot
(refer Figure 25) further verify the hypothesis as the diagonal curve for class ‘high’ and
‘low’ resembles a comparatively perfectly calibrated classifier.
42
Figure 24 ROC Analysis: WTI-Brent price differential
Figure 25 Calibration Plot: WTI-Brent price differential
The review of the Brent market’s continuous adaptability to complexities and ease in
shipment has made the referred benchmark the choice for majority of the oil traders.
The adoption of Brent over WTI by the emerging economies will continue to pull the
benchmark reference over its competitor. The analysis shows that the macro
environmental factors and market conditions provide better valuation to Brent price over
WTI. However, the 2014 oil price crash indicates gradual closing of the price difference
between the benchmark references.
4.4 Analysis: Global crisis influence on Oil Price
Global crisis has always shaped the price trajectory of crude oil, whether it was for a
short-span similar to post 2008 financial crisis with a ‘V’ price recovery or long-term
during Iraq-Iran war of 1986/88. The future precautionary demand from exogenous
events will continue to influence price fluctuation for crude oil. The year to date
percentage change in spot price were calculated from 1976-2012, referred in the
43
analysis as Impact. The global crisis chronological events were referred from EIA, 2015.
The crisis categorized into political, military, financial and terrorism.
Figure 26 Heat Map: WTI and Price fluctuation from Global events
The heat map technique used for WTI spot price and percentage change in WTI spot
price from various crisis events (refer Figure 26). The plot for the sample data of over
three decade indicates that crisis such as financial linked to recession and sovereign
debt as well as military associated with wars have most affected price fluctuation of
crude oil price among all global events. The map represent all major financial crises
occurred after 1976 at crude price over 50 dollar per barrel, reiterating the fact that
higher oil price followed by economic recession.
The ROC analysis curves (refer Figure 27) depicts that the data points that categorized
crisis types as ‘financial’ and ‘military’ have comparatively larger area under the curve
and thus technically more accurate as compared to ‘political’ or crisis from ‘terrorist
threats. Calibration plot (refer Figure 28) verify the hypothesis as the diagonal curve for
‘financial’ and ‘military’ crisis resembles a comparatively perfectly calibrated classifier.
The analysis shows crisis whether regional or global does influence the precautionary
demand for crude and hence its price. Although, there are inter-relation in many of the
military and financial crisis to the political decisions made at that time however does not
44
hold much of direct influence that fluctuates the oil price. The only recorded terrorist
activity that influenced the crude oil demand was 9/11. Nevertheless, with growing geopolitical conflicts against radical extremism that drastically reduced supplies from few
oil-exporting countries in recent times, one should not overlook the future influence on
oil price fluctuation from terror threats.
Figure 27 ROC Analysis: Global crisis events
45
Figure 28 Calibration Plot: Global crisis events
46
5 Conclusion
The emerging and Non-OECD economies will continue to drive the demand for crude in
near future. The efforts of these growing economies to access uninterrupted supply of
oil have increased in the last decade. The analysis has confirmed that the requirement
and consumption of oil from BRICS economy will influence the demand and subsequent
price of crude. In the absence of significant new discoveries for cheap oil outside
Middle East, OPEC will remain the powerhouse for global crude oil supply. However,
non-collective behavior of OPEC member states has led to inter-cartel competition.
Saudi Arabia and Iran will remain dominant political authorities in the Middle East and
North Africa (MENA) region. Saudi interest of lower oil price in one-way a savior for
emerging economies and oil-importing nations however Saudi’s intention for
permanently shut out its competitors on crude price crash by flooding the market with
excess supply has affected the economies of many oil-exporting countries. The policy’s
has resulted in deep impact on the price volatility and in securing Saudi Arabia an
influential role in world economy. The analysis indicates macro environmental factors
including price valuation, continuous adaptability and flexibility in shipment have come
together in favor of Brent over WTI in the last decade as the benchmark reference for
crude oil. The existence of multiple reference crude prices for trading has led to
imbalance in demand-supply and future commodity price. Commodity price in general
have direct correlation with regional or global events, however crude oil price is most
volatile among all the products. Historically, global events have occurred around oil or
have affected oil due to the stipulated source of supply and larger demand. The trend
will continue in future as long the global dependence on crude oil continues and not
substituted by an alternative easily accessible source of energy.
The new discoveries and state-of-art recovery technologies provided renewed reserves
of oil once considered lost that can meet the future demand with ease and in their way
shunned the peak oil theories. Undoubtedly, oil is important for modern society but
volatility of oil price is non-necessary.
47
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Appendix - Workflows
Work Flow 1 Non-OECD Consumption and Oil price
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Work Flow 2 Non-collective OPEC and Oil price
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Work Flow 3 WTI-Brent differential and Oil price
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Work Flow 4 Global Crisis and Oil price
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