The Influence of Change in Crude Oil Prices on Equity Market Returns

 
 
Department of Business Studies

               MSc Finance and International Business




 The Influence of Change in Crude
      Oil Prices on Equity Market
                         Returns:
an empirical study in the transport sector analysed with the use of
             Hubbert’s curve and the peak oil theory




                 Author: Nataliya Georgieva Pavlova

    Academic Supervisor: Thomas Berngruber




            Aarhus School of Business, Aarhus University

                          December 2011
The Influence of Change in Crude Oil Prices on Equity Market Returns


      Summary

      We live in a world that is changing with ever accelerating pace. What
was science fiction just a few decades ago is now a common everyday reality.
And all the new technology, transportation, agriculture, and the economy as a
whole is build on the abundance of affordable energy – the black gold – oil.

     In 1956 the geologist Martin King Hubbert published his peak oil theory
and made a very accurate prediction that USA will reach a peak oil point in
the 1970s and from them on the production of oil will decline very rapidly. At
the time he was discredited for his theory but in 1970 the American oil
production began to decline. The country’s economy is now especially
dependent on import for its energy needs. But how long can this be sustain?
At the present 33 out of 48 oil-extracting countries already peaked. Basic
economic law tells us that while oil keep decreasing price will keep
increasing. In valuing companies on the stock market the analytics use an
assumption that there will be infinitive stream of relatively cheap oil. So if the
peak oil theory come to be that means all the companies are overvalued.

     In this empirical study the relationship between stock rate of return and
the oil price is studied for the United States transport industry in the last 11
years. The results of the study are not conclusive since some the coefficients
in the regressions are not statistically significant. Despite that there is evidence
for relationship between oil prices an equity market.

     This correlation means that in case of peak oil the transportation sector
will be fully affected in negative direction. To transfer the whole sector away
from the oil as an energy source will be long an expensive process. Since the


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economy depends so heavily on the transportation to function it can affect all
areas of the economy.

     Despite of being such a big threat for the economy the problem off
limited oil supply is not extensively researched. Few papers argue the validity
of Hubbert’s model, but not many make the connection between the
theoretical model and its application in evaluating companies or predicting
market research.

     This paper reaches as far as analysing the results from an empirical study
using the influence of Hubbert’s curve over the economy. It involves some
speculations and educated guesses but all models have their assumptions. So
does this one.




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Table of content

Summary ................................................................................................................................ii

Table of content ....................................................................................................................iv

1. Introduction ..................................................................................................................... 1

     1.1. Motivation .................................................................................................................1

     1.2. Problem statement .................................................................................................... 2

     1.3. Applied methodology ................................................................................................3

     1.4. Boundary delimitations .............................................................................................3

     1.5. Structure of the paper ................................................................................................4

2. Theory .............................................................................................................................6

     2.1. Oil price volatility .....................................................................................................6

     2.2. Oil price shocks .......................................................................................................10

     2.3. Oil prices and the economy......................................................................................11

     2.4. Oil prices and the stock market................................................................................13

     2.5. Dependency of crude oil .........................................................................................16

     2.6. Hubbert’s curve and peak oil theory .......................................................................17

           2.6.1. What is peak oil theory ................................................................................17

     2.7. Literature review......................................................................................................22

           2.7.1. Supporting Hubbert’s theory ........................................................................24

           2.7.2. Opposing Hubbert’s theory ..........................................................................24

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3. Hypothesis ......................................................................................................................26

4. Statistical methodology...................................................................................................27

     4.1. Linear Regression Model with Ordinary Least Squares (OLS) ..............................27

     4.2. Principal component analysis .................................................................................28

     4.3. Linear and non-linear dimensions of xi ...................................................................31

     4.4. Hypothesis tests ......................................................................................................31

     4.5. Residual tests ..........................................................................................................32

5. Empirical analysis ..........................................................................................................33

     5.1. Data and model .......................................................................................................33

     5.2. Descriptive statistic .................................................................................................35

     5.3. Linear regression .....................................................................................................41

     5.4. Principal Components Regression ..........................................................................43

          5.4.1. Linear rate of return of oil prices .................................................................50

          5.4.2. Non-linear oil price increases .......................................................................51

          5.4.3. Other explanatory variables .........................................................................52

     5.5. Hypotheses tests ......................................................................................................52

     5.6. Residual tests ..........................................................................................................54

     5.7. Discussion ...............................................................................................................55

6. Conclusion ......................................................................................................................59

     6.1. Limitations ..............................................................................................................60

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     6.2. Further research........................................................................................................60

References.............................................................................................................................62

Appendixes:

Appendix A: List of companies included in the study............................................................a

Appendix B: Distribution of included in the study companies’ rate of return over time……b

Appendix C: Distribution of the included in the study variables’ rate of return aver time...c




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          1. INTRODUCTION

          This chapter is dedicated to explaining the purpose the objectives of this paper, as
well as the motivation for its writing. It also contains a section with some limitations as
well as a description of the structure of the paper.




          1.1.     Motivation




                 “For the first time since the Industrial Revolution, the geological supply of an
                                 essential resource will not meet the demand.” Deffeyes (2005)

                  “Oil is so significant to the international economy that forecasts of economic
                 growth are routinely qualified with the caveat: provided there is no oil shock.”
                                                                                  Adelman (1993)




          The purpose of this paper is to study the effects of change in global crude oil price
over the equity market and more specifically over the transport industry which is so
dependable on oil. The results are discussed in the light of Hubbert’s curve and peak oil
theory.

          The International Energy Agency is referring to crude oil as the number one energy
source in the world and the most actively traded commodity. The present global situation is
far from perfect partly because it is built on the available cheep energy of petroleum. The
developing countries are causing rapid demand growth, far greater than the growth in
production, which slowed even more with the conflict in Libya. This asymmetry between
demand and supply is keeping the prices at one of the highest ever. Prices above $100 per
barrel on the other hand are weighing down the economic development and already
unstable financial market, raising the prices of other commodities, keeping inflation high as



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well as concerns about speculation. The energy market is experiencing one of the most
uncertain periods in history.

       But the beginning of petroleum usage has been far less turbulent. In fact the oil
prices have been fairly steady up until the 1970s. In 1973 OPEC (Organization of
Petroleum Exporting Countries) placed embargo over the oil price which led to oil prices’
raise four times in a few short months and causing a following recession. For the next 40
years the price of oil has continued to vary in a general upwards direction and has become
more and more essential to the world’s economy.

       Soltes (2010) states that the oil price will keep increasing because of the limitations
in supply just like Hubbert’s model predicts. This must have an effect on the economy by
reducing the expected return and thus reducing the price of equity. There are a few studies
on the effects of oil price fluctuation but none of their results are discussed from Hubbert’s
curve point of view.

       This is the motivation conducting such a study and analysing the results from the
perspective of Hubbert’s model.




       1.2.    Problem statement

       Petroleum is non-renewable energy source and it will be depleted at one point in the
future. Since the whole modern world is build on the availability of oil as cheap energy, if
people want to sustain today’s lifestyle, oil have to be replaced by another type of energy.
Considering these points come the big question of what will happen to all those industries
that depend on oil as their main resource.

       The transport industry is the key to our modern civilization, because it enables trade.
It allows companies to make big cost savings from scale and scoop, by using one big
production site and distributing the finished product to the clients. It affects our very
survival since nowadays huge part of the food cost is the price of fuel, as well as other
chemicals used in the production – almost all of which are on the basis of oil. Besides food

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is not produced close to the people who consume it, but on huge fields and later on it is
shipped to supermarkets. This makes the transportation industry vital for today’s economy.

       This study employs the stock price of listed companies with field of business in
land, water and air transportation of people or goods as a benchmark for the overall
industry. It allows for the influence of changes in oil price over the industry to be studied.

       To summarise the objectives of this study:

       1)      To summarise the results from the discussions regarding the validity of
Hubbert’s peak oil theory and prove that it should be a guiding tool for the economical
policies.
       2)       To illustrate the relationship of crude oil prices and equity prices through
conducting empirical study.

       The limitations of supply on economies most important energy source is an
important issue. But almost all of the studies discuss the effect of Hubbert’s curve over the
macroeconomical variables. This paper aims to connect it with the state of the equity
markets as well and prove that low supply of crude oil will affect every aspect of the
economy.




       1.3.    Applied methodology

       This paper will present an empirical study to answer the problem statement.
Theoretical and empirical literature will be used as alternative data and estimating
procedures as well as comparative instruments (how close this study come to the finding of
other similar studies). Principal component analysis is the analytical tool of choice. The
description and specification of the statistical model can be found in chapter four
“Statistical methodology”.




       1.4.    Boundary delimitations

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       The empirical study is limit to one industry so that the results can be analyzed more
thorough. The reason for choosing the airline industry is that it is very dependent on oil so
the relationship between oil price and stock price will be clearer. For many industries that
are not so oil dependent this relationship can be lost in the noise of many other factors
influencing a stock price.

       Another limitation is that the data is taken from the US market. This country was
chosen for several reasons: 1) it is very dependable on oil, so the whole economy reacts
very strongly to any shocks in oil prices; 2) there is a rich database with available and
reliable data going far back in time.




       1.5.    Structure of the paper

       The structure of the paper is presented graphically in figure 1. The first chapter
presents the chosen subject and gives a brief description of the problem statement. Chapter
two studies the theoretical background, including a review of several relevant literature
sources and empirical studies. This helps forming a valid hypothesis in the next chapter.
Chapter four is dedicated to explaining the statistical method used to analyse the data –
principal component analysis, and explaining why this particular study is conducted with
this particular tool. Chapter five gives a description of the data and the results from the
analysis. The last chapter is conclusion and further research.




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I. Introduction

•   Motivation
•   Problem statement
•   Applied methodology
•   Boundary delimitations

II. Theory

•   Oil price volatility
•   Oil price shocks
•   Oil price and the economy
•   Oil price and the stock market
•   Hubbert's curve and peak oil theory
•   Literature review

III. Hypothesis


IV. Statistical methodology

• Linear regression
• Principal component analysis
• Additional tests

V. Empirical analysis

• Data and model
• Descriptive statistics
• Discussion

VI. Conclution

• Limitations of the paper
• Further research



     Fig. 1: Structure of the paper – graphic representation of the key point in the
                                                                       Master Thesis.
                                                                             Page | 5
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       2. THEORY

       The theoretical part of this thesis is divided into several parts. The first five parts are
dedicated to the price of crude oil, examining its volatile nature, and the dynamics between
oil and the economy and oil and equity market. The next two sections are dedicated to
Hubbert’s peak oil theory, explaining the nature of his model and reviewing some relevant
literature of debates about the validity of the curve.




       2.1.    Oil price volatility

       Figure 2 shows the movement of nominal and real oil prices since 1974 until present
days. The graph is constructed based on monthly data so the daily highest and lowest peaks
are slightly softened. Despite that it is clear that crude oil is a commodity with highly
volatile price – for the last 35 years presented here the price have varied between a
minimum value of $9.39 per barrel (December 1998) and a maximum value of $127.77 per
barrel (July 2008).




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                              Nominal and Real Crude Oil Price ($/barrel)
 140,00                                                                                                                                                                                                                                               Oil price bubble
                                                                                                                                                                                                                                                      and financial
 120,00                                                                                                                                                                                                                                               crises

 100,00

  80,00
                                                                                                                                                                                                           East Asian
  60,00                                                                                                                                                                                                    crises
                                                                          Iran – Iraq
  40,00                                                                                                                                                             Persian
                                                                          war
                                                                                                                                                                    Gulf War
  20,00           OPEC
                  embargo
   0,00                                                                   Collapse                                                                                                                                                                                                 Recession in
                        Юли 1975


                                                 Юли 1978


                                                                           Юли 1981


                                                                                                    Юли 1984


                                                                                                                             Юли 1987


                                                                                                                                                      Юли 1990


                                                                                                                                                                               Юли 1993


                                                                                                                                                                                                        Юли 1996


                                                                                                                                                                                                                                 Юли 1999


                                                                                                                                                                                                                                                          Юли 2002


                                                                                                                                                                                                                                                                                    Юли 2005


                                                                                                                                                                                                                                                                                                             Юли 2008


                                                                                                                                                                                                                                                                                                                                       Юли 2011
                                                                                                                                                                                          Януари 1995




                                                                                                                                                                                                                                                                     Януари 2004
          Януари 1974


                                   Януари 1977


                                                            Януари 1980


                                                                                      Януари 1983


                                                                                                               Януари 1986


                                                                                                                                        Януари 1989


                                                                                                                                                                 Януари 1992




                                                                                                                                                                                                                   Януари 1998


                                                                                                                                                                                                                                            Януари 2001




                                                                                                                                                                                                                                                                                               Януари 2007


                                                                                                                                                                                                                                                                                                                         Януари 2010
                                                                          of OPEC                                                                                                                                                                                                  US




                                                                                                                    Nominal Price                                                            Real Price



                          Fig. 2: The nominal and real price of crude oil from 1974 presented as monthly
                          average. Real oil price is computed by dividing the nominal price for particular
                                       month to the Consumer Price Index (CPI) for the same month to account for
                                                                                                                         inflation (data source: US Energy Information Agency).




          There is clear pattern of rising nominal prices over time. With real prices there is
not such an obvious trend. However the real prices keep values under $40 for the period
before 2004, with the exception of the war periods in the Middle East – a value that is
briefly reached during the drop in 2008 when the price bubble burst. Adjusting energy
prices for inflation can be considered unnecessary since energy price increases are the main
drivers of inflation (LeBlanc and Chinn, 2004) and thus a vicious cycle is created. For this
empirical study nominal prices will be used.

          Before the 1970s the price of crude oil has been varying very slightly in
comparison. During this period USA was still the biggest consumer but also the biggest
producer and even exporter. In 1973 short after the US peak in production the Yom Kippur
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war led to the OPEC embargo and cause a surge in oil prices and recession. Next oil price
shock can be attributed the Iranian revolution and the Iran – Iraq war from 1980 – political
instability in the major oil exporting region. The prices suddenly fall when in 1986
disagreement in OPEC cause the organization to collapse and the market was flooded with
oil. During the Persian Gulf War (1990) when Iraq occupied Kuwait the oil price almost
double. It was quickly restored because of Saudi Arabia’s quick reaction to increase
production.

       During the 1990s new power emerged and started increasing the demand – the
developing countries with leaders China and the Asian Dragons. These countries started to
industrialise their economies, causing gradual increase in oil prices, with the exception of
the period between 1998 and 1999 when the East Asian crises caused collapse in the
financial systems of the regions.

       The next dip in the market was caused by the recession in the US in 2001. This was
also the year of the terrorist attack in New York. After that the global economy had several
years of high economic growth which caused increase in oil demand and price until 2008.
For these years there were several spikes and dips in the market caused by conflicts in Iraq
and Nigeria, strikes in Venezuela, the peak in production of several substantial fields. But
the biggest fall of oil price in history came with the financial crises of 2008 when the price
dropped from $145 per barrel (all time highest price for crude oil) to $39 per barrel in
several short months. Hamilton (2011) argues that the prices may be unusually high
because of speculations on the market, which led to oil price bubble bursting and ledding to
the significant fall. Since then the oil prices have been steadily claiming back to values over
$100 per barrel.

       From this historical overview can be concluded the before 1990s main drivers for
oil price surges were wars, conflicts and OPEC’s control over production (Hamilton, 2011).
Since then most spikes and dips are a result of the economical and financial instability and
increased demand without the corresponding increase in supply.

       As showed above crude oil is quite volatile commodity. The factors that influence
the movement in price can be separated in to several categories:

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        -      Global oil supply and demand – just like every item that is subject to trade,
crude oil dependents on the supply and demand law of economics. The main factors that
drive the price of oil are global changes in supply and demand. This is not however entirely
competitive market. The production is controlled by OPEC. The organization’s aim for the
past decade has been to keep oil prices stable. With time however this task has proven
increasingly difficult and oil prices have been bouncing up and down in response to major
global events or speculations.

        -      War and natural disasters – war and devastating disasters are among the
main external factors affecting oil prices. The region of Middle East holds the largest
amount of oil supply in the world. At the same time it is one of the most politically unstable
regions. During the wars in Iraq and Afghanistan the concerns that delivery of oil would
stop was among the reasons that led to increase in oil prices up to $136 per barrel in July
2008.

        The price rise high in 2005 as well when Hurricane Katrina stopped the oil
production in the South Gulf Coast area. With less supply and the same demand the price
rose in a short period of time and forced President Bush to release 30 million barrels from
the Strategic Petroleum Reserve of the United States to bring the prices down.

        -      Changes in the social and political structure – events in the social or political
scene influence the petroleum market. For instance general increase in strike activity can
disrupt any of the supply or demand sides. Some of the historical spikes in oil prices are
caused by strikes in the energy sector (1952 – strike by oil, coal and steel workers, 1969 –
strikes by oil workers, 1970 – strike by coal workers).

        Before the last decade of XX century most of the world’s economies were
agricultural in nature. Since then many of them started transitioning to more industrial
economy which in turn led to increase in oil consumption. Among these countries are
China, India and the Asian Dragons (Hong Kong, Singapore, Taiwan and South Korea).
The accelerated development of Asian countries accounts for as much as 70% of the
increase in oil consumption for the last two decades. China was the third biggest consumer
of crude oil for 2010 (9.189 million barrels/day), behind only USA (19.150 million

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barrels/day) and the European Union (13.730 million barrels/day) (data source: Central
Intelligence Agency, publication: the World Factbook)

          -       Recession and the decreased demand for oil – Oil prices have very complex
relationship with the state of the economy. Empirical research (Hamilton, 1983) has shown
that oil price shocks can cause a recession. At the same time a recession reduces
production, which in turn lowers the demand. Decrease in demand is a force that drives the
price down.

          -       Speculation on the market – some changes in oil price cannot be linked to
actual changes in supply and demand but can be attributed to speculations in the market.
Former Algerian energy minister and president of OPEC Boussena said in interview in
September 2007: “Non-commercial participants are playing bigger role in the oil markets.
Funds are investing more capital in oil markets because of the volatility, diversification,
and opportunities to produced outsized returns.”
          Despite the fact that there are many factors influencing the movement on the
petroleum market, they all work by pushing up and down the demand and supply lines. The
price is volatile because the demand and supply is constantly changing. The general
tendency however is of constant growing need for more energy to fuel the economic growth
and limited supplies of oil which is reducing the extraction growth rate and lowering the
supply.




          2.2.    Oil price shocks
          The rapid change in oil prices are known as oil shocks. These shocks can be
classified and measured in three ways: 1) linear oil price shocks; 2) non-linear oil price
shocks; 3) asymmetric oil price shocks.

          Hamilton (1983) estimate oil price shocks by using the log difference of nominal
oil prices to estimate a linear model for oil prices.

          Asymmetric oil price shocks represent both significant increases and significant
decreases of oil price treated as separate variables. Mork (1989) discovered stronger

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statistically significant relationship between oil price and economic variables using
asymmetric oil price model compared to Hamilton’s (1983) linear oil price model.

       Non-linear oil price model was researched by Hamilton in later paper (1996). He
points out that most of the increases in oil prices are followed by immediate and sometimes
even bigger decreases. These decreases are mere corrections to the previous surges rather
than a real movement away from stable environment. He suggests an alternative model for
estimating change in oil price – Net Oil Price Increases (NOPI). This model suggests that
the oil price should be compared to its rate from the previous year. As value for the oil
price is assumed the difference between present value and the maximum value measured
for the previous year or zero if the number is negative.




       2.3.    Oil prices and the economy

       For several decades petroleum has played the part of the main energy source for the
industrialized countries. So it is not a surprise that a vast volume of literature is developed
to study the effects of oil over various macroeconomic variables such as Gross Domestic
Product, economic stability and growth, international debt, inflation, interest rates.

       Crude oil prices play very important role in the US economy (Hamilton, 1983;
Mork, Olsen and Mysen, 1994; Gisser and Goodwin, 1986).

       There is an obvious link between oil prices and the basic macroeconomic variables.
In his research Hamilton (1983) studies the influence that oil price shocks have over the
economy. He proves that after World War II all but one of the recessions in the US can be
directly correlated with large increases in oil prices. His paper points out some facts about
the poor performance of the United States after the 1973 embargo: 1) the real GDP growth
has fallen from an average of 4% for the previous decade to 2.4%; 2) for the same period
the inflation has more than double; 3) and the unemployment rate of 6.7% was higher than
in any year between 1948 and 1972 (with the exception of the recession of 1958). Of course
these symptoms of deep economic crisis following a reduction in oil supply can be merely a
coincidence. Hamilton however prove at 1% significance level that there is a systematic

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relation between oil prices and output – increases in oil prices are followed by decreases in
economic activity three to four quarters later. This is one of the first researches done on the
effects of oil prices on the economy.

       Kato (2005) however argues that current oil price surges has not lead to extreme
inflation and reduction in corporate earnings in Japan, as it happened in USA in 1970s,
suggesting there is another cause for the recession but oil price shocks.

       Gisser and Goodwin (1986), Mork, Olsen and Mysen (1994) show similar results –
negative correlation between oil prices and economical output. Mork, Olsen and Mysen
(1994) find asymmetric correlation pattern when there are price increases and price
decreases – the coefficients for price decreases tend to be with the opposite sign to the
coefficients of price increases. These results are sharpest for the United States as a
developed economy and show that the economic performance goes up when the price of oil
goes down.

       Bjørnland (2009) points out that the reasons behind oil price increase is important to
evaluate the effect of this increase over the economy. Recent studies point out increased
economic growth simultaneously with increased oil price, suggesting that oil spikes caused
by increase in demand have different effect then if caused by limited supply, like in US in
the 1970s.

       Often the change in oil price affects decisions on the highest governmental level.
The example that LeBlanc and Chinn (2004) give is from September 2000 when the price
of crude oil in United States tripled its levels from December 1998 and remained high and
volatile way into 2001. The increase in oil prices raised some legitimate concerns about
raising inflation. The Federal Open Market Committee and the Federal Reserve Board
raised the federal funds rate on six different occasions and one of the reasons was the
increased oil price. The price lowered only when the US economy went into recession and
reduced the demand.




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       2.4.    Oil prices and the stock market

       The relationship between oil prices and stock market has not been researched as
extensively as the relationship between oil prices and the economy. This is probably due to
the short period of time since the oil price has become so volatile. It is logical however, if
the oil prices play such crucial role in the economy as showed above, that oil prices and
financial markets are correlated. Stock prices are indicators for invertors’ expectations for
future profits, and as such give different perspective regarding oil price change. Several key
empirical studies will be mentioned in this section with regard to building some
expectations about this particular study.

       Figure 3 presents the changes in S&P 500 index in comparison to Brent crude oil
price for the last 11 years. It gives a little insight to the correlation between oil price and
financial markets. This period includes the 2001 recession and 2008 financial crises which
can be seen as two serious dips in the S&P 500 graph, but also a number of smaller
variations of the index. Both graphs on figure 3 seem to have synchronized large variations
that may suggest the existence of variables to which both oil and stock market react
simultaneously.




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                                     Brent Crude Oil
    160
    140
    120
    100
     80
     60
     40
                                                                                  Brent Crude
     20                                                                           Oil
      0




                                           S&P 500
    1800
    1600
    1400
    1200
    1000
     800
     600
                                                                                       S&P 500
     400
     200
       0




               Fig. 3: Movement of Brent Crude Oil price and S&P 500 index from 2000 until
                                                                2011 (data source: Datastream)




          In an efficient market the expectation is that oil and equity prices are correlated.
They are both highly volatile and the prices in both markets are often changing due to the
same economic or geopolitical events. Cochrane (2001) suggests inflation shocks hit
simultaneously oil price and stock market with the same factor thus affecting both their
returns and creating a link. If the fluctuations in oil price are affecting real output as


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discussed in the previous section then it has to be affecting the expected earnings of
companies and subsequently their stock prices.

        Kaul and Jones (1996) and Sadorsky (1999) are one of the first papers that find the
relationship between oil and financial market. Later Ciner (2001), Park and Ratti (2008),
Lai, Wang and Chen (2011) build on to these earlier researches and find with statistical
significance that the change in oil price really affects the equity returns. All these studies
use different data and estimation techniques but reach the same conclusions – crude oil
prices have a negative relationship with stock prices.

        Lai, Wang and Chen (2011) give very logical explanation of this negative
relationship. A rise in crude oil price is an increase in the price of an important commodity.
This will increase the costs for companies and the price for customers (reduced sales), both
of which have negative effect on profitability, causing drop in stock prices. This of course
does not apply for oil producing companies, which increase profits margins when spikes in
oil price occur.

        Positive correlation between oil price and stock market is found by Bjørnland
(2009) in his study on Norway. He explains the results by the fact that this is an oil
exporting country, so the economy benefits from higher oil prices. This is consistent with
studies on OPEC (Bina and Vo, 2007; Mehrara and Sarem, 2009).

        Huang, Masulis and Stoll (1996) research the relationship between oil prices and
stock market indexes and with selected companies whose stock prices are most likely to be
sensitive to oil shocks using oil futures. He found no statistically significant connections,
with the exception of oil companies. Ciner (2001) argues that the reason for lack of
correlation in their study is that they research only for linear relationship. Ciner’s (2001)
empirical study suggests that oil price shocks affect the return on equity in non-linear
fashion. He also finds that stock market performance affect oil futures market (feedback
relation).




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       Special emphases on the transport sector can be seen in Nandha and Brooks (2009)
paper. They find significant negative oil risk premium for the developed countries, in
particular if the analysis model is asymmetric.




       2.5.    Dependency of crude oil

       Data source for this section is US Energy Information Administration unless
specified otherwise.

       United States dependency

       United States of America is the largest economy in the world and the single biggest
consumer of crude oil with 19.150 million barrels/day for 2010 (data source: Central
Intelligence Agency). It satisfies 37% of nation’s energy needs – the highest of all energy
sources (the rest are coal, natural gas, nuclear energy and renewable sources).

       The official oil reserves in US are 30.5 billion barrels which is 2.4% of world oil
reserves. Before the 1970s US has been oil exporting country. In fact it is still the 3rd largest
oil producing country in the world. The consumption however has grown and the reserves
lowered. At present US is oil importing country – 63% of the consumed in the country oil
for 2009 is imported.

       Transport industry dependency

       “Over the next 25 years, demand for petroleum and other liquid fuels is expected to
increase more rapidly in the transportation sector that in any other end-use sectors” states
IEA report from 2007. Currently US transportation uses are fuelled by 95% petroleum
products and only 5% natural gas and renewable energy. During 2010 71% of US oil
consumption goes for transport. This is 2/3 of all petroleum.




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       2.6.    Hubbert’s curve and peak oil theory

       In 1956 Marion King Hubbert, geophysicist doing research for the Shell lab in
Houston, Texas, predicted that US oil production will peak in the early 1970s. At that point
oil was abundant and both scientists and oil industry rejected his work. But in 1970 the US
production of crude oil peaked. Since 1985 US production is slightly higher than Hubbert
predicted, mainly because of some successful discoveries in Alaska and the off-shore Gulf
Coast, but besides that his analysis turned out to be accurate. During 1990s several
scientists applied Hubbert’s model to the world supplies of oil trying to calculate the year
of a possible global peak. Some of the results predicted a peak as early as 2004. The
estimations continue to around 2050.




       2.6.1. What is peak oil theory?

       Peak oil theory developed by Hubbert (1956) is a model that was initially created to
predicted a path for depletion of oil resources in the United States, but at present is also
used to analyse other fossil fuels like natural gas (Reynolds and Kolodziej, 2009) and coal,
non-renewable natural resources like metals and slowly renewable biological resources like
whale’s population (Bardi and Lavacchi, 2009). The bell shaped curve was not
scientifically proven in his paper. What Hubbert did was to plot past production under a
curve of his prediction. The total area of the bell curve was the total amount of petroleum
left in the ground according to his estimate. Using this method he made two peak estimates:
pessimistic in the middle of the 1960s and optimistic around early 1970s.

       In his later paper Hubbert (1959) developed his analysis adding other elements. He
noticed a pattern of discovery and production – their graphs had similar shapes but shifted
in time. By this time the discovery of new oil fields was already slowing down. Based on
the existing production fields and the rate at which new petroleum fields were found he
estimated remaining oil of 150 billion (pessimistic guess) to 200 billion (optimistic guess)
barrels. Another addition was the specification of a functional form for his model. Stating



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that the cumulative production follow a logistic curve he explains why he uses the bell
shaped curve in his initial report – it is the first derivative of a logistic curve.

        Figure 3 shows a rudimentary representation of Hubbert’s curve showed as opposed
to a curve of resource stock. The production grows over time as new oil fields are
discovered. At the same time the demand grows making necessary even higher production.
With the increase of production however the oil reserves decrease at faster rate. The pace at
which new oil is discovered slows down and then start to decline and some of the existing
fields are exhausted. The production is still increasing for some time after that – it takes
minimum of 10 year period of discovered oil fields to become operating production sites.
But eventually with the depletion of oil in stock comes the reduction in production which is
shown on figure 3 (it is presented how the production decreases simultaneously with the
depletion of the resource in stock). The classic Hubbert’s curve is symmetric bell-shaped
curve that peak when the resource is 50% depleted.




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The Influence of Change in Crude Oil Prices on Equity Market Returns



                                                                              a)




                  Production

                                                     Time




                                                                              b)
                  Resource stock




                                                     Time

                Fig. 3: Basic graphic representation of Hubbert’s curve: a)Hubbert’s curve:
                production before and after the peak; b)the reduction of the natural resource
                                                                                       supply.




       The graph of Hubbert’s curve is consisted of three elements: 1) gradual increase
from zero that rises at accelerated rate; 2) a peak representing the maximum level of
production; 3) a steep decline from the peak that become more gradual as approaching zero.

       If the area under the curve is denoted as Qt the peak will occur when the area

reaches    .    is the fraction of the total oil that is already produced and 1 -        is the

fraction that is yet to be produced. So the production P is:


                                         P=α+                  Q

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The Influence of Change in Crude Oil Prices on Equity Market Returns


       and it is linearly dependent on the fraction of oil left unexploited.

       After the US peak oil in 1970 exactly as Hubbert had predicted in his early papers,
his theory became very popular among researches concerned with the depletion of natural
resources.

       In more recent years the interest toward this model is renewed in the 1990s by
Campbell, who was among the first to apply Hubbert’s curve towards the global oil
resources (Campbell and Laherrere, 1998).

       The modern Hubbert’s model is a combination of techniques, most of which
developed by Hubbert, but some by other researchers after him. It includes three steps: 1)
analysis of past discoveries; 2) estimation of future discoveries; 3) projection of future
production. Past and future discoveries of oil fields are plotted on a curve. There are several
methods of estimating undiscovered oil. Brandt (2007) classifies them as Campbell’s
“creaming curve” method, plotting ultimate recovery by using the so called “Hubbert
linearization” method, or using statistical relationship such as extrapolating the future
discoveries based on the past (Laherrere, 1996). Using the discovery data a production
curve can be plotted so that the area under the curve equals total discovered and not yet
discovered oil. The most important part for this methodology to produce accurate
prediction is the total number of oil production. This is the area under the production curve
and it has extremely strong influence over the distribution of the curve over time.

       For the model to be practical some assumptions are often made. Most frequently
these are: production follows a bell-shaped curve; production is symmetric over time – year
with most production, or peak year, happens when the resources are half depleted,
discovery and production will have the same distribution with a constant time lag;
production increase and decrease in one cycle – there are no multiple peaks. In reality some
or all of these assumptions can be untrue. Their use however helps simplify the model and
give an approximate estimate for the peak year.

       Since the accuracy of Hubbert’s curve is so dependent on one estimated number –
total production – and is subjected to many simplifications, there is variation in the


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The Influence of Change in Crude Oil Prices on Equity Market Returns


estimations of different researchers. Even Hubbert’s original graph did not come to past as
he predicted. The peak did happen in 1970 as he estimated but since 1985 US have
produced more oil than the curve shows because of successful discoveries in Alaska and the
Gulf Coast. Also new technologies become available that allowed drilling in much deeper
waters than in the 1950s, when Hubbert first announce his discoveries, giving the
possibility of producing more oil from the ocean bottom.

       Despite the widespread use of Hubbert’s curve, it is not a perfect model predicting
the future. It is often criticized for being arbitrary so other methods are used as well to
calculate oil production, for example resource-to-production ratio (both parts of this ratio
are constantly changing so in the end the number has little meaning).

        In Hubbert’s curve there is a big accent of the physical limitations (the fact that oil
is a non-renewable energy source) and less consideration of the economic and political
reactions to the physical limitations (new legislations for limiting greenhouse gases,
different agreements between oil import and oil export countries, reducing the use of crude
oil when the price is too high and switching to natural gas instead, etc.). So the crude oil
depletion is not a question of physics or economics or politics alone. Only a combination of
all can explain the peak. And since geology cannot be change much of the discussion is
centred on the political and economical side of the issue.

       Even with all the imperfections the Hubbert’s model is the most accurate so far.
Many scientists seem to forget however that this is only a model and there has to be some
assumptions. After all the very definition of a model is a method to simplify the complex
reality. The purpose of any economical model in general is not to accurately predict the
future but to provide a tool for understanding patterns in the behaviour of the economy, to
give a basic idea of what to be expected.

       By simple macroeconomic rule, the increased demand for oil put together with the
physical limitations of supply with the approach of Hubbert’s curve should establish new
equilibrium at higher price. Deffeyes (2005) however believes that this is going to cause an
increase in volatility, much like the situation at present (in later paper Deffeyes (2009) he
stated that peak oil has occurred in 2008). The production and consumption systems are

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The Influence of Change in Crude Oil Prices on Equity Market Returns


dependent of political and economical factors and can be easily disturbed. But essentially
most of the oil use is in the transportation which is relatively inelastic in a short term.
Deffeyes advices not to dismiss the peak oil theory just because the price of oil sometimes
swings downwards.

       The long war for recognition of the problem of impending energy shortage came
one step closer to goal when in 1998 the International Energy Agency for the first time
forecasted a possible date of the peak in global oil production between 2010 and 2020,
validating Hubbert’s theory.




       2.7.    Literature review

       Hubbert’s peak oil theory has been a controversial one from the very beginning.
There are still many discussions concerning its credibility. A number of scientists support it
because it gives logical explanation for the present global situation concerning oil. Some go
as far as stating there is an inevitable collapse of the modern economic and financial
system, or even the end of the western society. Others are far less sceptical and dismiss this
theory explaining the increase in oil prices with the general inflation, political situation in
the Middle East, the monopoly of OPEC as main exporter, etc. In this section a review of
relevant literature concerning Hubbert’s theory will be presented. Different research papers
divided in supporting and opposing views on his model are summarised in Table 1.




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The Influence of Change in Crude Oil Prices on Equity Market Returns


                   Article                           Main point                          Summary

             Mohr and              Develop a theoretical model of production        Showing
             Evans (2008)          that validate Hubbert’s curve                    theoretical proves
             Brandt (2006)         Find Hubbert’s model as most useful,             for the validity of
                                   especially if allowance for asymmetry is         Hubbert’s curve
                                   made                                             and the bell-shaped
Supportive




             Bardi and             Show that Hubbert’s model is applicable to       distribution of
             Lavacchi (2009) several historical case even if the underlying         production (prove
                                   assumptions are minimized                        with some
             Soltes (2010)         Prove the existence of peak oil and use it as a historical data)
                                   basis for trading strategy


             Laherrere             Supports the idea that a multiple peak curve     Accepting eventual
             (2000)                best fit the global oil production               peak in oil
             Postill (2008)        Describes oil reserves and production as         production but
                                   asymptotical curve (it will approach zero but    questioning the
                                   never reach it)                                  credibility of
                                                                                    Hubbert’s curve
             (Reynolds and         Discuss the role of natural gas and prove that   Proposing plateau
Opposing




             Kolodziej,            Hubbert’s curve does not work for all            as more appropriate
             2009)                 regions; discuss role of institutions            form for oil
             Harris (2010)         Describes the peak oil moment as a drown-        production curve
                                   out plateau in the production with price
                                   spikes and dips; suggest the importance on
                                   natural gas
             N/A                                                                    Perpetually
                                                                                    growing oil
                                                                                    production

                             Table 1: Summary of literature review discussing the validity of Hubbert’s
                                                                              curve and peak oil theory.

                                                                                                  Page | 23
The Influence of Change in Crude Oil Prices on Equity Market Returns




         2.7.1. Supporting Hubbert’s theory

         There is a debate among the supporters of peak oil theory about when and how is
the global peak oil happening. The estimates are in range of more than 40 years (from 2004
up until 2047) with estimates for total oil supplies between two and three trillion barrels
(Mohr and Evans, 2008).

         Mohr and Evans (2008) attempt to construct the oil production profile without
having a particular production curve in mind. They develop a model based on simple
theoretical logic and then compare it with the existing data about production. The model
follows almost symmetric bell-shaped curve, similar to Hubbert’s model. Their estimation
of peak year is between 2010 and 2025, with ideal case peak in 2013.

         Brandt (2006) researches all oil producing regions individually and finds Hubbert’s
theory most widely fitting the historical data. He however makes some corrections to the
original model noticing that in most cases asymmetric bell-shaped curve fits better than
symmetric.

         Some researchers use Hubbert’s theory as basis for trading strategy. Soltes (2010) is
presenting astonishing profit of 399% for 7 months trading Brent Oil with long and short
Turbo Certificates. His strategy is less risky than initially assumed since he expects the oil
price to continue to grow in a long run.

         Laherrere (1999) makes summary of the official peak oil production forecasts
showing that many scenarios are beyond optimistic (US Department of Energy – 2025 –
2030).




         2.7.2. Opposing Hubbert’s theory

         The opposition of Hubbert’s model can be classified in two categories. There are
researchers that recognise that oil production will peak and then start to decline at some

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The Influence of Change in Crude Oil Prices on Equity Market Returns


point in the future. They however disagree with Hubbert’s bell shaped distribution of
production and look for an alternative model. The other category of researchers considers
the influence of more than simply physical factors over the global oil production and
predicts a production plateau, not a peak.

       Although a supporter of Hubbert’s theory Laherrere (2000) argues that the model is
applicable only when the production follows natural process of depletion, unaffected by
significant political or economical interference. He suggests a model with multiple
Hubbert’s peaks that can account for political and economical disturbance, for discovering
a major oil field after the production has already peaked, or for countries with too few oil
production sites.

       Postill (2008) argues that although the global oil reserves are finite, they will never
be depleted. Reserves and production are both asymptotically approaching zero value, so
the symmetric bell-shaped curve does not describe these tendencies. Harris (2010) also
does not support the bell-shaped curve. He claims that the oil production may look like a
peak at some point and there could have difficulty in supply but it is actually a plateau with
varying prices. Even Brandt (2006) who supports the model in his paper claims that in
some regions linear or exponential curve fits better the historical results.

       Research of natural gas from Reynolds and Kolodziej (2009) shows that Hubbert’s
curve work only for some regions, but not for all. They attribute this to the role of
institutions since the discovery graphs they plot are very Hubbert’s like, but the production
is highly regulated which distorts the curve. If managed correctly by institutions many
countries can avoid the Hubbert’s curve type peak and have a long plateau way before they
reach the full potential of production.

       Reynolds and Kolodziej (2009) and Harris (2010) put natural gas in the equation of
world’s energy needs because oil and gas can be interchangeable to some degree. 12% of
the crude oil needs in 2008 are met by natural gas and the percent is expected to grow to
25% until 2030, which should reduce some of the stress from the oil supply side of the
market.



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The Influence of Change in Crude Oil Prices on Equity Market Returns


       The reasons that some researchers reject Hubbert’s peak oil theory can be
summarised as: 1) new technology will be developed allowing companies to drill deeper in
search for oil and speed up the exploration process; 2) financial pressure for optimising the
production – when the price of oil become too high new technology will be developed that
will not require fossil fuels, thus reducing the demand; 3) political and social pressure for
reducing CO2 emissions will force some companies to switch to cleaner technologies which
will reduce the demand; 4) the volatility of oil prices is due more to market speculations
rather than real supply shortage; 5) OPEC is using its monopoly power by keeping the
supply low so that they earn abnormal profits. Many papers use one or combination of
several of these reasons.

       In table 3 there is a third category of opposition to the Hubbert’s peak theory –
completely rejecting peak oil theory’s main paradigm, that crude oil production will
eventually reach a maximum and start declining. This however is equal to suggesting that
oil production will keep growing in perpetuity which is physically and logically impossible
– since there is a limited amount of oil in the ground limited amount is available for
extraction. Not one paper was found that support the view of unlimited oil. Even
governmental institutions are forced to admit that fossil fuels have finite nature and correct
their development plans according. Still the notion of infinite supply of cheap energy is still
used in the evaluation of the price of equity.




       3. HYPOTHESIS

       The majority of the empirical studies researching the relationship between oil price
and equity return find a significant negative correlation.

       Many researchers find negative correlation between oil prices and market returns
(Kaul and Jones, 1996; Sadorsky, 1999; Ciner, 2001; Park and Ratti, 2008; Lai, Wang and
Chen, 2011). This is especially strong for economic sectors that are strongly dependant of
oil (Nandha and Brooks, 2009). Transport industry is very dependent on the prices of
gasoline, one of petroleum’s main products and according to IEA report this dependency


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The Influence of Change in Crude Oil Prices on Equity Market Returns


will only grow stronger in the next 25 years. The expectations are that it affects the industry
by increasing the costs and decreasing profits, which consequently lowers the market
return. Based on that the first two hypotheses suggest:

       Hypothesis 1: Linear oil price shocks have negative effect on the stock returns.

       Ciner (2001) argues that the only reason Huang, Masulis and Stoll (1996) didn’t
find any correlation between oil price and stock markets is because they tested with linear
distribution of the oil price. If Hamilton’s (1996) NOPI model is used the expectations are
that negative correlation exists.

       Hypothesis 2: Non-linear price shocks have negative effect on the stock returns.




       4. STATISTICAL METHODOLOGY

       The data is regressed using Ordinary Least Squares method with the Principal
component as variables.




       4.1.     Linear Regression Model with Ordinary Least Squares (OLS)

       Ordinary Least Squares in statistics is an approach that estimates the best linear
approximation of y from xj (j = 1,..., k) by minimizing the sum of the squared residuals. All
fitted values are on a straight regression line.

                                                   ŷi = xi’β.

       The difference between the observed and approximated value makes the error term

                                        yi = ŷi + εi = xi’β + εi or

                                               y = Xβ + ε,




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        where y and ε are n-dimensional vectors of dependant variables and error terms; X is
n×k matrix of variables x.

        For the statistical model to have econometric sense there are several conditions
(Gauss-Markov conditions): 1) the expected value of the error term is on average zero
(E{εi} = 0, i = 1,...,N); 2) X is a deterministic nonstochastic matrix – it is independent from
ε; 3) homoscedasticity – all error terms have the same variance (V{εi} = σ2, i = 1,...,N); 4)
no autocorrelation – zero correlation between different error terms (cov{εi,εj} = 0, i, j =
1,...N i ≠ j).

        As a test for statistical significance standard t-test statistic is used to test a single
restriction.


                                                   =        ,


        where        is estimate for β and          it standard error;     is a value chosen by the
researcher. The hypothesis that βk =         is rejected at the 5% level if tk > |0.96|. Using the
standard normal approximation the 95% confidence interval for βk is:

                                     {bk – 1.96se(bk), bk + 1.96se(bk)}.




        4.2.      Principal Component Analysis

        Principal component analysis is a research method used to analyse a large data set
of interrelated variables. The purpose is to retain as much as possible of the variation
present in the data by transforming it to a new set of variables called principal components.
The new variables are linear combinations of the original variables. Principal components
are uncorrelated and set in a descending order by the amount of variation present in all of
the initial variables – the last few principal components identify near-constant linear
relationships among the original variables and have very little variation. The expectations
of this study are that the oil price will be placed among the first few variables, thus account
for as much of the variability of the data as possible.

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