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Master Thesis on Risk Management
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ID number: 0948108
Name: Evelyn Bobocea
Master Thesis
Risk management using
derivatives in the European
Union
Supervisor:
Salvatore Miglietta
Hand-in date:
02.09.2013
Campus:
BI Oslo
Examination code and name:
GRA19003 – Thesis seminar in Finance
Programme:
Master of Science in Financial Economics
“This thesis is a part of the MSc programme at BI Norwegian Business School. The school takes no
responsibility for the methods used, results found and conclusions drawn."
Master Thesis in GRA19003 02.09.2013
Page i
Content
CONTENT ........................................................................................................................................ I
SUMMARY .................................................................................................................................... II
I. INTRODUCTION ..................................................................................................................... III
II. LITERATURE REVIEW ......................................................................................................... 1
III. DATA AND METHODOLOGY ............................................................................................. 4
III. 1. SAMPLE DESCRIPTION .......................................................................................................... 4
III. 2. HYPOTHESIS, VARIABLES AND THE ECONOMETRIC MODEL .................................................. 6
III. 3. RESULTS OF THE EMPIRICAL ANALYSIS ............................................................................. 10
IV. CONCLUSIONS ..................................................................................................................... 17
APPENDICES ............................................................................................................................... 18
REFERENCES .............................................................................................................................. 34
RESEARCH PAPERS ...................................................................................................................... 34
BOOKS ........................................................................................................................................ 35
ELECTRONIC RESOURCES ............................................................................................................ 35
Master Thesis in GRA19003 02.09.2013
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Summary
The aim of the present study is to analyse the effect of derivatives use on firm
value for a sample of 40 companies selected from the crude petroleum and gas
industrial sector, selected from countries members of the European Union, but
also from Norway, in order to build a comparison between the two. The idea of
this research has been strongly incentivised by the poor number of studies in risk
management regarding European companies, and mostly from the European
Union, but also by the comparison that could be built in relation to Norwegian
companies. The author’s results concluded that derivatives use do not have an
impact on firm value, regardless of economic context, while other variables
proved to be highly influential, such as size, capital expenditures ratio or return on
assets.
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I. INTRODUCTION
Risk management is a widely debated and discussed, but rather controversial issue
in the financial world. Hedging against risks has always been a matter of concern
for all companies and also a subject tackled by many studies in the extant
literature. The interest has been growing even stronger with the arousal of
derivative financial products, which have come to be appealing for companies,
individual investors or any other types of economic actors who were seeking to
reach higher profits and gains by reducing the exposure to risks as much as
possible.
However, some important lessons have been drawn back from the intensive use of
derivatives in the last decade and the catastrophic effects they have had on the
global economy that led to the 2008 financial crisis. Hence, one of the questions
of the present study is whether firms should make use of derivatives in times of
economic downturn and if this has a significant impact on the firm value.
The purpose of this paper is to analyse in a comparative way the oil industry of
the European Union and the one of Norway for several reasons. First of all, given
its position as one of the world’s most important economic pillars, it is interesting
to see in this industrial field how EU companies decide to manage risks, if they
make use of derivatives and what is the overall effect on profitability. Secondly, a
country rich in petroleum resources like Norway which is not part of any
international economic block has grown to be rich and the local companies are
prosperous and competitive. Finally, all these taken together, making a parallel
between the European Union and Norway would give a comparative view of risk
management practices under the use of derivatives in the oil industry.
A strong motivation of the author of the current study is to bring a contribution to
the existing literature, which does not treat so many studies related to risk
management and derivatives on European companies. What is more, European
Union companies are even less present in previous studies, which make the
incentive of this research even more imperative.
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The remainder of this paper is organized as follows: section II reviews previous
researches of the existing literature, section III describes the variables, the sample,
the econometric model and the empirical results, and section IV presents the final
conclusions.
.
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II. LITERATURE REVIEW
According to the classic Modigliani-Miller paradigm of perfect capital markets,
financial hedging is seen as irrelevant and with no economic sense, since there are
no information asymmetries, taxes or financial costs (Modigliani, 1958).
However, the rising importance of various risk categories in direct relation with
the well-functioning and value of firms, has made risk management become one
of the key-objectives of financial executives (Scharfestein, 1993). Beyond solely a
theoretical concept, risk management is treated in depth in various empirical
studies who seek to offer a useful framework to be implemented in business
practice.
There are several rationales for corporate hedging presented in the extant
literature.
One of them is introduced by Stulz (1984) in his study „Optimal hedging policies”
and refers to managerial motives, that is, the outgrowth of managers’ risk
aversion, as they are often large holders in the firm’s stock. Still, Stulz’s theory
has its weaknesses in the sense that it implicitly assumes the significant costs
beared by managers when trading in hedging contracts for their own account,
which is a direct reason for involving the firm in hedging activities.
Froot, Scharfestein and Stein (1993) expose another strong determinant for
hedging, given by taxes. They argue the relevance for optimal hedging through
the representation of taxes as a convex function of earnings, verified in practice by
firms for which the probability of negative earnings is quite high. In a similar
light, an additional factor they talk about is related to costs of financial distress
and debt capacity, motivating that the latter can be enhanced through hedging
practice. Last but not the least, capital market imperfections and inefficient
investment are shown to be another powerful argument for hedging, taking into
account that this way investment distortions associated with debt finance can be
reduced and thus, add value to the firm.
Master Thesis in GRA19003 02.09.2013
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Financial risk management has come forward in the last three decades due to the
increasing popularity of derivative financial products. Derivatives as a means of
hedging have been set forward in the 1980s and the 1990s mostly in relation to
managing foreign currency exposure as many firms began to develop growth
opportunities, but there is also a focus on interest rate exposure as well. It is worth
mentioning here that the impact of derivatives use on firm risk has also been
accounted for in several studies. In this direction, Guay (1999) analyzes how
firms’risk exposures are affected by derivatives use and he concludes that
generally the effect is on risk reduction and that accounting rules also play a key
role in this process.
For example, Stulz (1984) tackles with the problem of using forward contracts in
order to manage foreign currency exposure. In that sense, he derives a model
based on optimal hedging policies addressed to risk-averse agents and also puts a
focus on value-maximizing firms with regard to active hedging policies. His
findings conclude upon the fact that active hedging policies are indeed employed
by firms described above and that optimal hedging policies suppose choosing
positions whether in forward contracts or foreign bonds.
Another relevant research belongs to Geczy, Minton and Schrand (1997) who
investigate the use of currency derivatives so as to draw a clear line between
existing theories of hedging behavior. They show that both higher growth
opportunities and tighter financial constraints, but also consistent foreign-rate
exposure and economies of scale, are strong determinants for firms to use
currency derivatives, in order to reduce cash flow variation.
In the same fashion, Howton and Perfect (1998) examine derivatives use in
currency and interest rate exposures for both companies included in the S&P 500
index, but also for randomly selected ones. Their study reveals that the most used
instruments in interest-rate and foreign currency hedging, are swaps and forwards
and futures, respectively. What is more, according to their final remarks,
determinants of derivatives use vary accross the considered samples, but are
largely consistent with hedging theory.
Master Thesis in GRA19003 02.09.2013
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With regard to firm value maximization, the first to investigate the contribution of
derivatives to value enhancement have been Allayannis and Weston (2001). They
set their attention on a sample of non-financial firms and they reach the
conclusion that there is a positive relationship between firm value and hedging.
With respect to the oil industry, which is the area of interest of the present paper,
an important research has been conducted by Jin and Jorion (2006), in which they
examine the hedging activities of 119 U.S. oil and gas producers and their effect
on firm value, on a time span between 1998 and 2001. Their results state that on
the whole there is no significant difference in firm value between hedgers and
non-hedgers, as it would have been expected and contrary to Allayannis’s and
Weston’s findings.
Finally, a more recent study belongs to Lookman (2009), who examines and
quantifies the impact of hedging for oil and gas exploration and production firms.
What is new in his approach, compared to Jin and Jorion (2006) is that he stresses
upon the difference between primary and secondary risks, in an attempt to
emphasize the level of influence they have on the financial operation of the firm.
His findings point out that hedging the primary risk leads to a value discount,
whereas hedging the secondary risk generates a premium of higher value than the
value discount. He also concludes that hedging itself does not lead to a higher
value of the firm and that other variables which have not been taken into account
have an effect in this sense.
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III. DATA AND METHODOLOGY
III. 1. Sample description
The author has constructed the sample of the current research by using the
Compustat database1 in order to gather financial data (on which the variables of
the econometric model will be developed) concerning companies from the oil
industry and which are also located in countries from the European Union and
Norway. According to the Standard Industrial Classification2, the oil industry is
divided in four segments with their corresponding codes. That is crude petroleum
and natural gas (1311); drilling oil and gas wells (1381), oil and gas field
exploration services (1382) and oil and gas field services (1389).
However, given the relatively poor amount of data available, the sample has been
narrowed to the crude petroleum and gas sector. An explanation for this could be
the small dimensions of the European oil market. As found on Compustat
database, the oil industry in Europe comprises 698 companies, compared to the
2667 in North America, which translates into a European market roughly 25% of
the North-American one. Hence, the final sample of this paper contains 40
companies which operate in the crude petroleum and gas sector from United
Kingdom, Ireland, France, Germany and Sweden as references to the European
Union, and Norway as a separate entity. The aim of this separation is to build a
comparison between the European Union as global economic actor and Norway as
a single economic power and with rich petroleum resources.
What is also worth mentioning is that the companies are listed on London Stock
Exchange, Stockholm Stock Exchange, Oslo Stock Exchange and Frankfurt Stock
Exchange.
1
http://wrdsweb.wharton.upenn.edu/wrds/ds/comp/gfunda/index.cfm?navGroupHeader=Compustat
%20Monthly%20Updates&navGroup=Global
2 http://www.sec.gov/info/edgar/siccodes.htm
Master Thesis in GRA19003 02.09.2013
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The sample is then divided in consonance with two key time periods, 2005-2007
and 2008-2012, so as to analyse the effects of hedging on firm value in the recent
years that have offered a period of economic boom, but also a shattering global
financial crisis. The purpose of this division is to see whether there is a difference
in the incentives of companies to hedge or not to hedge with financial derivatives,
given the two important economic moments mentioned above. A company is
considered a hedger if it makes use of at least one derivative financial instrument
to hedge at least one category of risk (as stated in the annual financial reports).
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III. 2. Hypothesis, variables and the econometric model
The global hypothesis this paper puts forward is in accordance with a variety of
studies in the hedging literature that state that firms using derivatives for hedging
are rewarded with higher valuation by investors, which should translate into
higher firm value overall. Thus, the current study tests the influence of derivatives
use on firm value on the sample previously presented. All the quantitative analysis
is conducted in Microsoft Excel program and Eviews software.
Given that the focus of this study is on the oil industry, the author has gathered
two categories of data. First one comprises the variables that will be used to plot
the econometric model and the second aims to draw a view of the core risk factors
companies from this industry are generally exposed to but also taking in account
the information gathered from the annual reports of the companies on the time
span between 2005 and 2012.
As main variable of interest and also the centre of analysis of this paper is Tobin’s
Q, a proxy for firm value. Tobin’s Q is defined as the ratio of the sum between the
market value of equity and book value of total assets and the book value of equity.
This is in accordance with the study of Jin and Jorion (2006) and also the
algorithm of calculus undertaken my most of the researchers. The other variables
included in the analysis are divided in two wide categories: a hedging dummy
variable and a set of control variables (their formulas are presented in detail in
Appendix 2), that will be presented below.
Using a hedging dummy allows to control whether firms use derivatives of any
kind to hedge any type of risk they are being exposed to. This variable takes the
value of 1 if the firm uses derivatives for hedging and 0 if otherwise.
Control variables have the role of checking whether changes in the value of the
firm are due to other reasons that do not refer to hedging.
Master Thesis in GRA19003 02.09.2013
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In this sense, the control variables chosen are:
a) log of total assets as a proxy for firm size. Since there is not a clear
evidence on whether size leads to higher firm value, its sign
regarding Q is ambiguos,
b) a dividend dummy, which is used as a proxy for firms’access to
financial markets and takes the value of 1 if a firm paid dividends
in the year of interest and 0 otherwise,
c) ratio of long-term debt to book value of equity, an indication of
leverage, but also with an ambiguous sign,
d) return on assets, typically a measure of profitability which is
expected to be positively correlated with Q, as higher profitability
leads to higher firm value,
e) capital expenditures ratio¸ which is computed by scaling the total
capital expenses to sales and measures the investment growth and
should be positively related to Q,
f) research and development ratio, which is computed by dividind
the research and development expenses to total assets.
Basing itself on the empirical model developed by Allayannis and Weston
(2001), but also on a similar recent research made of Spyridon Kapitsinas on
Greek companies (2008), the econometric model of this current research has the
following shape:
( ) √
√
√
√
√
The explanation for choosing using square roots and radicals of third order for the
control variables instead of a linear regression relies on the similarity between the
graphical representations of the logarithm and the radical functions. Also, after
running a pile of tests and regressions in the software used, the author came to the
conclusion that the linear regression is not an adequate model for the current
research, as it leaded to no concluding result, and it turned to using radicals for
mathematical considerations.
Master Thesis in GRA19003 02.09.2013
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Since we are working with panel data, the methodology of calculus implies that
the variables put in the regression to be computed as averages of the annual values
that were gathered from Compustat.
For each time span, 2005-2007 and 2008-2012, there is a certain average that is
taken as value to be implemented in the model. An important detail to be pointed
out here is that due to unavailability of data concerning the market value of equity
on Compustat, the author has computed it using the returns of stocks and the
number of outstanding shares.
In order to compute the returns, daily prices have been collected for the time
period 2005-2012. The values of the returns have been calculated as a natural
logarithm of the ratio between the daily values of two consecutive trading days.
The computed daily stock returns have been average in order to determine a single
value for the 2005-2007 period and for 2008-2012 respectively.
Then, these amounts have been multiplied with the number of shares outstanding
so as to obtain the values of the market value of equity which is to be used in the
computation of Tobin’s Q. To mention as well that the number of outstanding
shares has been found on the Compustat database, and the daily prices of stocks
have been extracted from various sources, such as Yahoo! Finance3, Google
Finance4, Oslo Stock Exchange
5 website and Stockholm Stock Exchange
6
website.
Moving on to the second category of data, the author has gathered information
regarding the main sources of risks that the companies from the sample face.
Statistically speaking and in relation with the the companies’ annual financial
reports, interest rate risk, foreign-exchange rate risk and oil price risk are the
general exposures faced by the companies.
3 http://finance.yahoo.com/
4 http://www.google.com/finance
5 http://www.oslobors.no/
6 http://www.nasdaqomxnordic.com/
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As interest rates indicators, EURIBOR is assigned as interest rate for the
companies from the United Kingdom, Ireland, France and Germany, STIBOR for
Sweden and NIBOR for Norway. The data has been collected on a time span from
2005 to 2012, in annual represention, from the official sites of the central banks of
Norway7 and Sweden
8 and from the official website of EURIBOR
9 of the
European Union.
Concerning the exchange rates, the key exposures that the companies that operate
in United Kingdom and Ireland are to the GBP-USD rate, those from Germany
and France to the EUR-USD rate, and the SEK-USD and NOK-USD rates are
assigned to companies from Sweden and Norway respectively. The values of the
exchange rates have been collected from x-rates.com10
, in annual representation as
well, between 2005 and 2012.
As about the oil price risk, the indicator in this sense is the price of Europe Brent
crude oil, colected from U.S. Energy Administration website11
, in annual terms,
on a time period between 2005 and 2012.
Following the methodology of calculus, the interest rates, exchange rates and the
price of crude oil have been averaged in order to result in two key values for
2005-2007 and 2008-2012, respectively.
The summary statistics for both the variables analyzed in the model and the risk
factors are presented in tables 1 and 2 . Additionally, some robustness checks have
been performed to test the goodness of fit of the econometric model and the
results are encompassed in appendix 1.
7 http://www.norges-bank.no/en/price-stability/exchange-rates/
8 http://www.riksbank.se/en/Interest-and-exchange-rates
9 http://www.euribor-ebf.eu/euribor-org/euribor-rates.html
10 http://www.x-rates.com/historical/
11 http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=RBRTE&f=A
Master Thesis in GRA19003 02.09.2013
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III. 3. Results of the empirical analysis
The outcome of the empirical analysis, as presented in the equation of the
econometric model, is in accordance with what Jin and Jorion found in their
research (2006), but not with Allayannis’s and Weston’s findings (2001), as the
overall result of the current paper is that derivatives use for hedging does not have
any influence on the firm value.
Table 1 presents summary statistics of the whole sample, with the two time spans
highlighted.
We can see that generally, companies have not been so incentivised to hedge
through derivatives during 2005-2007, as the mean value of the hedge dummy is 0
for this period. This is in connection with the companies’ risk management
policies which stated that the degree of exposure to various risk factors was not of
a consistent or critical level so as to determine them to employ derivatives. What
is more, there are companies who have reported that use of derivatives as means
of hedging is not at all included in their risk management practice.
A different view is given by the 2008-2012 period, which reflects an increased
drive for firms to turn to derivatives in their hedging practice and risk
management policy. This is shown by the mean value of the hedging dummy
variable of 0,5220. This is again consistent with the collected information from
the companies’ annual financial reports. Still, the discussion is more complex, as
some firms who did not choose to use derivatives to hedge against risks between
2005 and 2007 decide to turn to these instruments from 2008 to 2012, some who
used in the past, do not use them anymore and there are also firms who whether
used derivatives as means of hedging in all the two time spans or did not use at
all.
Master Thesis in GRA19003 02.09.2013
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It is worth pointing out that the companies from Norway have employed
derivatives in their risk management policy all along 2005 until 2012, according
to their financial reports and their most used instruments were interest rate swaps,
and forwards, which is quite the same in the case of the companies from the rest
of the sample
Table 2 summarizes the key statistics for the risk factors taken into consideration
for the current paper.
For the first time span analysed, between 2005 and 2007, we can see that interest
rates vary from a minimum value of 3,11% to a maximum of 3,87%, with a mean
value of 3,41%. Exchange rates know the highest volatility of all the three risk
categories, with a standard deviation of 32,27% and the values move between a
minimum of 0,1426 and a maximum of 1,3215.
As for 2008-2012, there is a strong arousal in the oil price, reaching a value of
92,23$/barrel, compared to 64,05$/barrel in the previous time span. There is also a
general increasing in volatility for all the risk factors, but interest rates however
know a downturn in value, ranging from 2,18% to 3,74%. Exchange rates are
facing a growth in value as well, but the interval range is not significantly
different from the one registered in 2005-2007, with a minimum value of 0,1414
and a maximum of 1,3470.
Tables 3 and 4 express the regression outputs of the sample analysis, for each time
period. Corely speaking, the coefficient of the hedging dummy variable proved
not to be significant for neither of the two time periods considered, which
emphasizes the fact that the use of derivatives does not have an impact on firm
value. The dividend dummy proved not to be relevant in drawing any conclusion
on the influence on firm value, as all the companies from the sample did not pay
any dividends during the whole time period from 2005 to 2012.
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What is worth mentioning is that the statistcally significant variable for the 2005-
2007 period is the return on assets, which means that profitability was high
enough to determine a strong influence on the value of the firm and the sign of the
coefficient is positive, which means a positive association with Q.
As for 2008-2012, capital expenditures ratio and size are the significant variables,
which means that growth opportunities and company dimension have contributed
to changes in the firm value. The capital expenditures ratio is possitively
associated with Q, due to the positive sign of the coefficient, while size is
negatively associated. The explanation would therefore be that growth
opportunities have enhanced firm value, while big size means lowered firm value
and analogous for small size.
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Table 1: Summary statistics for the full sample
The table presents the summary statistics for all the variables included in the OLS
regression. The variables are: Tobin Q, Hedging dummy-a dummy variable that
equals 1 if firms use derivatives in the analyzed period and 0 otherwise, Debt
ratio, ROA-Return on Assets, Capital expenditures ratio, Size, R&D- ratio-
research& development ratio.
Table 1 presents descriptive statistics for the all of the variables included in the
OLS regression. There has been a slight decrease in the debt ratio from 37.62% to
35.55%, and also for ROA from -14.13% to -18.58%. It can be also noted that
companies recorded an in increase in capital expenditures, and a decrease of 4%
in the research and development expenditures. Furthermore, while in the first
period 2005-2007, the mean firm size was 0. 6737, in 2008-2009 there has been
an increase up to 0.9093.
No. of obs. Mean Median Std.dev. Min. Max. Skewness Kurtosis
Ln of Q 40 4.5956 4.9131 3.0266 -0.1235 13.2999 0.3941 0.3270
Hedging
dummy40
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
Debt ratio 40 0.3762 0.2124 0.4021 0.0000 1.2188 0.4585 -1.3023
ROA 40 -0.1413 -0.3046 0.4765 -1.0222 0.6582 0.2743 -1.1543
Capital
expenditures
ratio
40
1.2114 0.8467 1.2704 0.0000 6.6104 2.9827 10.1554
Size 40 0.6737 0.9184 1.0715 -1.4071 2.0553 -0.4167 -1.1231
R&D ratio 40 0.0076 0.0000 0.0281 0.0000 0.1620 4.7207 24.5408
Ln of Q 40 5188.2869 46.5847 20639.0334 1.0000 105307.9064 4.3856 18.6602
Hedging
dummy40
0.5250 1.0000 0.5057 0.0000 1.0000 -0.1041 -2.0967
Debt ratio 40 0.3555 0.3712 0.3594 0.0000 1.1846 0.4172 -1.1433
ROA 40 -0.1858 -0.2920 0.4913 -1.4732 0.6022 -0.2050 -0.4792
Capital
expenditures
ratio
40
1.5192 0.8611 3.2411 0.0000 20.9752 5.8244 35.6055
Size 40 0.9093 1.3384 1.0825 -1.6662 1.9511 -1.2259 0.4289
R&D ratio 40 0.0072 0.0000 0.0311 0.0000 0.1800 5.0160 26.4291
PANEL B 2008-2012
PANEL A 2005-2007
Master Thesis in GRA19003 02.09.2013
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Table 2: Summary statistics for risk factors
This table presents the summary statistics for the stock returns, oil price, interest
rates, and exchange rates returns. The table depicts the descriptive statistics for
both of the periods analyzed.
Table 2 reports the summary statistics for the risk factors in the two analyzed
periods. There is an increase in the average return for two of the risk factors
analyzed. For the other two, stock price return and interest rate, the mean return
has decreased from -0.0002 to -0.0021, respectively from 0.0341 to 0.0233. The
same evolution can also be noted for the median value.
No. of obs. Mean Median Std.dev. Min. Max. Skewness Kurtosis
Stock price
return 40 -0.0002 0.0005 0.0023 -0.0094 0.0026 -2.0638 5.9165
Oil price 40 64.0567 64.0567 0.0000 64.0567 64.0567 0.0000 0.0000
Interest
rates 40 0.0341 0.0340 0.0015 0.0311 0.0387 1.4696 5.2717
Exchange
rates 40 0.9717 1.0824 0.3227 0.1426 1.3215 -2.1395 3.1569
Stock price
return 40 -0.0021 -0.0005 0.0087 -0.0554 0.0022 -6.1562 38.5492
Oil price 40 92.2360 92.2360 0.0000 92.2360 92.2360 1.0394 -2.1081
Interest
rates 40 0.0233 0.0218 0.0042 0.0218 0.0374 3.0110 8.0137
Exchange
rates 40 1.0835 1.2118 0.3613 0.1414 1.3470 -2.2802 3.4575
PANEL A 2005-2007
PANEL B 2008-2012
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Table 3: Regression output for the 2005-2007 period
This table presents the coefficients, standard errors, t-statistics, p-values from the
regression output for the period 2005-2007. The model used in a multifactor OLS
regression. The dependent variable is Tobin Q. The independent variables
include: Hedging dummy-a dummy variable that equals 1 if firms use derivatives
in the analyzed period and 0 otherwise, Debt ratio, ROA-Return on Assets,
Capital expenditures ratio, Size, R&D- ratio-research& development ratio. The
regression output also reports the R Square value.
Regression Statistics
Multiple R 0.7238
R Square 0.5238
Adjusted R Square 0.4373
Standard Error 2.2704
Observations 40
Coefficients
Standard
Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95%
Upper
95%
Intercept 4.5356 0.7552 6.0060 0.0000 2.9992 6.0720 2.9992 6.0720
Hedging
dummy 0.8334 0.9122 0.9136 0.3676 -1.0226 2.6893 -1.0226 2.6893
Debt
ratio -1.5718 1.1369 -1.3826 0.1761 -3.8849 0.7412 -3.8849 0.7412
ROA -3.1329 1.0298 -3.0422 0.0046 -5.2281 -1.0377 -5.2281 -1.0377
Capital
expenditures
ratio 0.2230 0.3273 0.6813 0.5005 -0.4429 0.8889 -0.4429 0.8889
Size -0.5868 0.5429 -1.0809 0.2876 -1.6913 0.5177 -1.6913 0.5177
R&D
ratio 11.0868 13.2091 0.8393 0.4073 -15.7874 37.9610 -15.7874 37.9610
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Table 4: Regression output for the 2008-2012 period
This table presents the coefficients, standard errors, t-statistics, p-values from the
regression output for the period 2008-2012. The model used in a multifactor OLS
regression. The dependent variable is Tobin Q. The independent variables
include: Hedging dummy-a dummy variable that equals 1 if firms use derivatives
in the analyzed period and 0 otherwise, Debt ratio, ROA-Return on Assets,
Capital expenditures ratio, Size, R&D- ratio-research& development ratio. The
regression output also reports the R Square value.
Multiple R 0.6054
R Square 0.3665
Adjusted R Square 0.2513
Standard Error 17858.3340
Observations 40
Coefficients
Standard
Error t Stat
P-
value Lower 95%
Upper
95% Lower 95%
Upper
95%
Intercept 26068.4743 7763.4361 3.3579 0.0020 10273.64486 41863.3037 10273.6449 41863.3037
Hedging
dummy -1488.3300 6591.3634 -0.2258 0.8227 -14898.55963 11921.8996 -14898.5596 11921.8996
Debt
ratio 9712.5879 10249.8401 0.9476 0.3502 -11140.86870 30566.0444 -11140.8687 30566.0444
ROA 11949.7658 9278.2056 1.2879 0.2067 -6926.88549 30826.4171 -6926.8855 30826.4171
Capital
expenditures
ratio -2206.2499 1030.6937 -2.1405 0.0398 -4303.21206 -109.2877 -4303.2121 -109.2877
Size -18493.3681 5386.5839 -3.4332 0.0016 -29452.45551 -7534.2807 -29452.4555 -7534.2807
R&D
ratio -162554.5179 109182.3836 -1.4888 0.1460 -384687.74754 59578.7118 -384687.7475 59578.7118
Regression Statistics
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IV. CONCLUSIONS
The present study has shown that even in the presence of exposure to risk,
companies who hedge do not differ from some who would choose not to do it, in
terms of firm value.
We were able to observe that the majority of the companies included in the
sample did not show incentives to hedge with derivatives during the 2005-2007,
while a significant number of non-hedgers decided to become hedgers in the next
time period from 2008 to 2012. This behavior could be characterized in terms of
fear of worse outcomes at the brutal contact with the financial crisis. However, we
can not omit the companies who decided to stick on their risk management policy
principles and not include derivatives in their hedging practice. This can be an
outspeaking proof of strong corporate governance that does not allow flows so as
to take into consideration the use of derivatives as means of hedging.
A conservative behavior could be attributed to the companies from Norway as
well. Given that the risk management practice suffered no changes regarding
hedging before or during the financial crisis, this could be motivated by the fact
that Norway is a closed economy and the degree of exposure to risk factors is not
as strong as for the companies in the European Union.
Companies from Norway could be given as example of prosperity using
derivatives in crisis and in good economic turns, but the picture could be a bit
biased due to the fact that this country is not a player on the global economy
scene, so the benefits of the firms might be available only in a local context.
Given the small dimensions of the European Union oil and derivatives markets,
compared to North America, the economic results of the studied companies are
quite impressive, as they are not affected neither by hedging, nor by not hedging.
Finally, the author is engaged in further research on this topic, so as to improve
the econometric model and the methods used for the quantitative analysis, so as to
attain maximum of accuracy on results and additional information.
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Appendices
Appendix 1
Table 1 Results of Augmented Dickey Fuller Unit Root Test
This table summarizes the results of Augmented Dickey Fuller Test. The null
hypothesis of this test is that series have unit root. In order to reject or accept this
hypothesis, the absolute values of the numbers presented above are compared with
the critical values: 1% - 3.6155, 5% - 2.9411, 10% -2.6090. If the numbers of the
coefficients presented above are higher in absolute values than the critical values,
then the null hypothesis is rejected. As it can be seen, all series do not suffer from
unit root bias.
Augmented Dickey Fuller Test Regression 1 Regression 2
TOBIN Q -4.9734 -4.5350
CAP EXPENDITURE -5.3131 -3.9757
DEBT RATIO -5.3157 -5.9851
HEDGING -5.9555 -5.6627
R&D RATIO -6.5680 -5.7171
ROA -4.2460 -4.3306
SIZE -5.2454 -5.0245
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Table 2 Results of Jarque Bera Test
This table presents the results of Jarque Bera test. In order to accept the null
hypothesis which assumes that the residual series are normally distributed, JB
statistic has to be lower than the critical values presented above. As it can be
noticed, the residuals are normally distributed so the coefficients of the estimators
are reliable.
Table 3 Results of Variance Inflation Factors Test
This table shows the results of the test I applied in order to test for
multicollinearity. I used the Centered Variance Inflation Factors and the cutoff
level of 5. As it can be seen all the values for both regressions are below 5 which
means that the series are not correlated. Therefore, the regressions are not affected
by multicollinearity.
Jarque Bera Test Regression 1 Regression 2
JB Stat. 9.5819 0.0309
Degrees of freedom 6 6
Critical values
1% level 16.8120 16.8120
5% level 12.5920 12.5920
10% level 10.6450 10.6450
Probability 0.0083 0.9846
Variable Regression 1 Regression 2
CAP EXPENDITURE 1.3045 1.3589
DEBT RATIO 1.5571 1.6593
HEDGING 1.2536 2.5412
R&D RATIO 1.0792 1.3646
ROA 1.7534 4.1582
SIZE 2.5847 1.4058
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Table 4 Results of White Test
This table shows the results of White test. I used this test in order to test the errors
series for heteroskedasticity. If the errors are not homoscedastic then the p-values
of the estimators are altered. As it can be seen above, the probability of F-statistics
is higher than the standard levels of 1%, 5% or 10%, which means that the null
hypothesis of no heteroskedasticity is rejected. The errors are homoscedastic and
the estimators are reliable.
Table 5 Results of Durbin Watson Test
This table shows the results of the Durbin Watson test, which I used to test for
autocorrelation. K – the number of estimators, N – the number of observations, D
lower and D upper are extracted based on K and N. As it can be seen above both
regressions are positive correlated.
White Test Regression 1 Regression 2
F-statistic 0.6057 0.2698
Prob. F 0.8672 0.9977
Durbin Watson Test 5%
level of significanceRegression (1) Regression (2)
K 6 6
N 40 40
DL 1.2305 1.2305
Du 1.7859 1.7859
DB Stat 1.6085 1.5736
DB Stat < DL No Positive Correl No Positive Correl
DB Stat > Du Positive Correl Positive Correl
Du< DB Stat < DL Inconclusive Inconclusive
(4 - DB Stat) < DL No Negative Correl No Negative Correl
(4 - DB Stat) > Du No Negative Correl No Negative Correl
Du < (4 - DB Stat) < DL No Negative Correl No Negative Correl
Master Thesis in GRA19003 02.09.2013
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Appendix 2 – Formulas
)
)
) (total assets)
)
) (
)
6)
)
)
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Appendix 3 – Preliminary thesis report
BI Norwegian Business School
MSc Financial Economics
Preliminary thesis report:
Evaluating risk management in the oil
industry using derivatives
Date of submission:
15.01.2013
Supervisor:
Salvatore Miglietta
Written by:
Evelyn Bobocea
ID: 0948108
– Oslo –
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Table of Contents
ABSTRACT ................................................................................................................................... 24
INTRODUCTION......................................................................................................................... 25
LITERATURE REVIEW............................................................................................................. 26
DATA AND METHODOLOGY .................................................................................................. 31
REFERENCES .............................................................................................................................. 32
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ABSTRACT
The purpose of this paper is to analyze different risk management approaches
under the use of derivatives for a number of 73 companies from the petroleum
industry selected from relevant countries in America and Europe.
The main goal of this study is to determine the best risk management alternatives
to be put in practices by firms in relation to the price of crude oil, the interest rate
and the inflation rate for a time pattern chosen.
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INTRODUCTION
The petroleum industry is amongst the most volatile ones, therefore companies
operating in this sector need to give particular attention to the risks they are being
exposed to, so as to find the best hedging methods that will minimize their losses.
Given the global financial crisis that started in 2007 and still resides in the general
economic context in the present days, it is even of greater importance to have an
attentive look at one of the most prominent industry fields in the world and how
risk management practices should work.
In the present study, the focus targets risk concerning price, interest rates and
inflation rate, as these are the main factors which affect the winnings of
companies operating in the petroleum industry.
Price risk is the most important risk factor which could affect the winnings of an
oil-operating company as there is a strong correlation between the evolution of
crude oil price and the price of stocks related to the companies in discussion.
Secondly, interest rate risk is another key-element in a risk management analysis
because the various moves it suffers during a certain time period is reflected in the
evolution of a company’s profits.
Last but not least, the inflation rate is another indicator which we have chosen to
analyze through the lens of risk because an industry like the petroleum one is very
sensitive to the ups and downs of the inflation rate, therefore it is more than
necessary to take it into account when analyzing risk for an oil-operating
company.
Looking at these three risk elements, we should be able to decide which type of
derivatives are best to be used so as to minimize the risk exposure for the firm.
Nevertheless, besides this quantitative analysis, it is also important to consider
several other factors such as corporate governance issues, cultural dimensions and
the political and economic contexts which are determinant for our overall
conclusions of the study.
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LITERATURE REVIEW
The literature of speciality has tackled many key issues concerning risk
management practices and analysis.
The literature on oil price impacts can be broadly divided into macroeconomic
impacts and impacts on stock market returns in general and market return of oil
and gas firms. The debate on the macroeconomic impacts of oil price shocks
began in the mid-1970s.
The earlier studies regressed GDP on oil prices (Rasche & Tatom 1997a, 1997b).
In fact it was Hamilton's, 1983 work indicating that oil price increases have
reduced US output growth between 1948 and 1980, which sparked debate on this
topic.
Hamilton (1983) showed that an oil price hike preceded all but one recession (in
1960) in US since second World War.
Gisser and Goodwin (1986) corroborated the results of Hamilton (1983). Studies
by Bohi (1989) and Mork (1989) focused on the asymmetric impacts of the oil
price change; the argument being that oil price movements up and down have
opposite effects on the production possibility curve of firms, causing changes in
resource allocation.
Hamilton's (2000) updated study for the period 1948–2000 showed that GDP
decreased by 1.4% in the fourth quarter after the initial price shock. However, the
study by Rotenberg and Woodford (1996) for the same period as Hamilton (2000)
showed a much larger output loss (2.5% of GDP).
Empirical studies have also examined the relationship between oil price changes
and stock prices at the (a) firm and (b) aggregate level. At the firm level, one of
the earlier studies on the relationship between oil prices and returns of oil firms
was that of Al-Mudhaf and Goodwin (1993). They used a multi-factor of the
arbitrage pricing theory (APT) model to analyze and explain the difference in the
Master Thesis in GRA19003 02.09.2013
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market and oil price returns in 29 US oil companies (listed in New York Stock
Exchange) in a period surrounding the oil shock of 1973.
They found that oil price shocks drove up returns for oil firms. Rajagopal and
Venkatachalam (2000) studied 25 petroleum refining companies and concluded
that earnings of these firms exhibited a strong correlation with the firms' oil betas
(in the range of 0.55 to 0.66).
A few studies concentrate on the impact of oil prices on stock market returns at
the industry level. Lee and Ni (2002) find that for industries that are oil-intensive
in production, such as petroleum refinery and industrial chemicals, the
predominate impact of oil shocks is on the cost-side, while for other industries,
such as the automobile industry, the main effect of oil price shocks is on the
demand-side. Gogineni (2010) provides empirical evidence that oil price changes
affect stock returns of industries on the cost-side and demand-side.
Park and Ratti (2008) show that Norway as an oil exporter shows a statistically
significant positive relationship between stock market returns and oil prices.
Hammoudeh and Li (2005) based on daily data for the period 1986–2003, on the
relationship between oil prices and the return in the stock markets in oil-based
countries (Mexico and Norway) and two major oil-sensitive industries (US oil and
transportation industries), found that oil price growth leads stock returns of oil-
exporting countries. But they also found a negative association with the world
stock market index (MSCI World Index) and returns of the US transportation
industry and oil prices. Boyer and Filion (2007) using the multifactor framework
to analyze the determinants of Canadian oil and gas stock companies, reveal a
significant relationship between oil price changes and stock returns.
Park and Ratti (2008) found that the impact of oil prices on the variability of stock
returns is greater than that of interest rates. A rise in oil prices is associated with a
significant increase in the short-term interest rates in the U.S. and most European
countries. Similarly, Sadorsky's (2001) study of Canadian oil and gas companies
for the period of 1983:04 to 1999:04 found that crude oil prices, exchange rate and
interest rates have a large and significant impact on stock prices. Sadorsky's study
finds a significant positive relationship between the oil and gas equity index and
Master Thesis in GRA19003 02.09.2013
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the price of crude oil, with a 1% change in oil prices being associated with a
change of 0.03% in the value of the oil and gas equity index. Papapetrou's (2001)
study using impulse response functions found that oil prices are an important
factor in explaining stock price movements in Greece.
The study by Cormier and Magnan (2002) found evidence of income smoothing
among Canadian oil and gas companies. They found that there is a close
relationship between stock market evaluation and future cash flows. Byard,
Hossain, and Mitra (2007) examined earnings management of U.S. oil and gas
firms after the devastating impact of hurricanes Katrina and Rita in 2005. Oil
prices peaked after the effects of both hurricanes. Normally, large rises in oil
prices trigger politicians and regulators that wealth is transferred to oil and gas
firms at the expense of consumers (Watts & Zimmerman 1986). According to the
political cost hypothesis, managers have a strong incentive to engage in earnings
management designed to lower reported earnings during periods of severe
political scrutiny. Byard et al. (2007) find significant abnormal income-decreasing
accruals immediately after the impact of hurricanes Katrina and Rita.
On the contrary, studies by Chen et al. (1986) argue that there is no special reward
for oil price risk in the stock market. Huang et al.'s (1996) study found a
significant relationship between daily oil futures returns and daily US stock
returns. They found that oil future returns had no impact on the broad based
market index such as the S&P 500.
Malliaris and Urrutia (1995) provide evidence of share prices reacting negatively
to the Persian Gulf crises. Studies on the impact of oil prices on the stock markets
of various countries have also revealed interesting results. The study by Jones and
Kaul (1996) (for the period 1947–1991) on the impact of oil prices on expected
returns of oil firms in Canada, Japan, the United Kingdom and the USA. Using a
standard cash flow dividend valuation model they test whether the reaction of
international stock markets to oil shocks can be justified by current and future
changes in real cash flows. They concluded that the reaction of Canadian and US
stock prices to oil prices can be completely accounted for by the impact of these
shocks on real cash flows. However, they did not find a strongrelationship for
Master Thesis in GRA19003 02.09.2013
Page 29
similar firms in Japan and United Kingdom. Similarly, the study by Faff and
Brailsford (1999) reports a significant positive impact of oil price change on oil
and gas and diversified industries in Australia. On the other hand, oil-dependent
industries (where oil is an input) like paper and packaging, transport were found
to be negatively impacted. Kilian and Park's (2009) study, based on monthly data
for the period of 1973 to 2006 found that demand and supply shocks driving the
global crude oil market jointly account for 22% of the long-run variations in U.S
real stock returns. A similar study by Bhar and Nikolova (2010) for Russia found
that global oil price returns have a significant impact on Russian equity returns
and volatility. El-Sharif, Brown, Burton, Nixon, and Russell (2005) examined the
influence of the price of crude oil on equity values in the oil and gas sector using
data relating to the United Kingdom, the largest oil producer in the European
Union. Their evidence indicates that the relationship is always positive, often
highly significant and reflects the direct impact of volatility in the price of crude
oil on share values within the sector. In addition, their empirical results indicate
that for non-oil and gas industries the effect of oil price volatility on equity returns
is minimal. These results confirm that industries are not homogeneous and that
different variables can impact industry returns in various ways (Faff & Brailsford
1999).
There is a related strand of literature that considers corporate governance as
important determinants of firm performance. Studies by Morck, Shleifer, and
Vishny (1988), McConnell and Serveas (1990) and Thomsen and Pedersen (2000)
investigated the relationship between ownership concentration and firm
performance. They show that there is a nonlinear relationship between ownership
concentration and firm performance beyond a certain point, which indicates
entrenchment of incumbent management or large shareholders.
Gompers, Ishii, and Metrick (2003) find that firms with strong shareholder rights
outperform, on a risk-adjusted basis, firms with weak shareholder rights. This
result indicates that that good governance has a positive impact on corporate
performance. Bhagat and Bolton (2008) find that better governance, stock
ownership of board members, and CEO-Chair separation is significantly
Master Thesis in GRA19003 02.09.2013
Page 30
positively correlated with operating performance. Wolf (2009) uses a
comprehensive dataset of oil and gas companies, covering both privately and
publicly owned firms over the period 1987–2006, to examine whether or not
ownership matters in economic terms.
The study supports the hypothesis that private ownership encourages better
performance and greater efficiency than state ownership does. A review of the
aforementioned studies showed that crude oil prices have a positive impact on the
financial performance of oil and gas companies at the firm level while has a
negative impact on oil-using (where oil is used as an input) firms.
At the aggregate (overall stock market) level, the evidence is mixed: in oil stock
dominated stocks markets like Canada and the USA, the impact of an oil price
change is generally positive, but it is weak in non-commodity based stock markets
like Japan and the United Kingdom. It seems plausible that commodity prices are
to some extent reflected in the share price, but less of an effect on the accounting
profit measures.
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DATA AND METHODOLOGY
We have selected daily closing values for the stock prices of 73 companies from
America and Europe, that is 25 companies from the Americas and 48 from Europe
respectively, for a time span ranging from January 1st 2000 to December 31st
2012.
The time span has been chosen so that it encompasses the period before the
financial crisis in 2007 has started, the period in which the crisis has been most
prominent – 2007-2009 and post-crisis from 2010 to 2012. It is important to
analyze each of these periods in order to be able to draw up conclusions that could
also apply as a general case when the economy offers a boom followed by a
considerable depression.
Also, we have selected the daily values for the price of crude oil WTI, the interest
rates for the countries considered and the inflation rate for the same time horizon.
The idea of this analysis is to check whether there is a connection between the
three economic factors just above and the evolution of the companies’ winnings.
For this we will employ a set of regressions to see the influence that each of the
risk factors has on each of the companies and how strong this is. In order to do so,
we will set up as the dependent variable the companies’ stocks prices, which we
will analyze in connection with the price of crude oil WTI, interest rates and
inflation rate as independent variables.
In addition to this, it is also important to check whether the variables in our
analysis are cointegrated. For this, we will employ a series of Granger tests in the
Eviews program.
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REFERENCES
1. Al-Mudhaf,A., & Goodwin, T. H. (1993), Oil shocks and oil stocks: Evidence
from the
1970s. Applied Economics, 25, 181–190
2. Apergis, N., & Miller, S. (2009), Do structural oil-market shocks affect stock
prices?
Energy Economics, 31, 569–575
3. Arellano, M., & Bond, S. (1991), Some tests of specification for panel data:
Monte Carlo evidence and an application to employment equations. Review of
Economic Studies, 58, 277–297
4. Barsky, R. B., & Kilian, L. (2004), Oil and the macro-economy since the
1970s. Journal of Economic Perspectives, 18, 115–134
5. Bhagat, S., & Bolton, B. (2008), Corporate governance and firm performance.
Journal of Corporate Finance, 14, 257–273
6. Bhar, R., Hammoudeh, S., & Thompson, M. A. (2008), Component structure
for nonstationary time series: Application to benchmark oil prices. International
Review of
Financial Analysis, 17, 971–983
7. Bhar, R., & Malliaris, A.G. (in press), Oil prices and the impact of the
financial crisis of 2007–2009, Energy Economics, 33
8. Bhar, R., & Nikolova, B. (2010), Global oil prices, oil industry and equity
returns: Russian experience. Scottish Journal of Political Economy, 57, 169–186
9. Boyer, M. M., & Filion, D. (2007), Common and fundamental factors in stock
returns of Canadian oil and gas companies. Energy Economics, 29, 428–453
10. Byard, D., Hossain, M., & Mitra, S. (2007), US oil companies' earnings
management in response to hurricanes Katrina and Rita. Journal of Accounting
and Public Policy, 26,
733–748
11. Driesprong, G., Jacobsen, B., & Maat, B. (2008), Striking oil: Another
puzzle? Journal of Financial Economics, 89, 307–327
12. Elekdag, S., Lalonde, R., Laxton, D., Muir, D., & Pesenti, P. (2008), Oil
price movements and the global economy: A model based assessment. IMF Staff
Papers, 55, 297–311
Master Thesis in GRA19003 02.09.2013
Page 33
13. El-Sharif, I., Brown, D., Burton, B., Nixon, B., & Russell, A. (2005),
Evidence on the nature and extent of the relationship between oil prices and equity
values in the UK,
Energy Economics, 27, 819–830
14. Fama, E. F., & French, K. R. (2004), The capital asset pricing model:
Theory and evidence, Journal of Economic Perspectives, 18, 25–46
15. Gisser, M., & Goodwin, T. H. (1986), Crude oil and the macro-economy:
tests of some popular notions. Journal of Money, Credit and Banking, 18, 95–103
16. Gogineni, S. (2010), Oil and the stock market: An industry level analysis. The
Financial Review, 45, 995–1010
17. Hamilton, J. D. (2008), Oil and the macroeconomy. In S. N. Durlauf, & L. E.
Blume (Eds.), The New Palgrave Dictionary of Economics (2nd Edition). .
Hampshire, England: Palgrave Macmillan.
Master Thesis in GRA19003 02.09.2013
Page 34
REFERENCES
Research papers
Adam, T., & Fernando, C. (2006). Hedging, speculation, and shareholder value.
Journal of Financial Economics.
Allayannis, G., & Weston, J. (2001). The Use of Foreign Currency Derivatives
and Firm Market Value. The Review of Financial Studies.
Geczy, C. M. (1997). Why firms use currency derivatives. The Journal of
Finance.
Guay, W. (1999). The impact of derivatives on firm risk: An empirical
examination of new derivative users. Journal of Accounting and
Economics.
Hodder, J., & Jackwerth, J. (2009). Managerial responses to incentives: Control of
firm risk, derivative pricing. Journal of Banking & Finance.
Howton, S. P. (1998). Currency and interest-rate derivatives use in U.S. firms.
Financial Management.
Jin, Y. J. (2006). Firm value and hedging: evidence from U.S. oil and gas
producers.
Jorion, P. (1990). The Exchange-Rate Exposure of U.S. Multinationals. The
Journal of Business.
Kapitsinas, S. (2008). The Impact of Derivatives Usage on Firm. Munich
Personal Repec Archive.
Lookman, A. (2009). Does Hedging Increase Firm Value?Comparing Premia for
Hedging "Big" versus "Small" Risks. Working paper, Carnegie Mellon
University.
Modigliani, F. M. (1958). The cost of capital, corporation finance and the theory
of investment. The American Economic Review.
Scharfestein, S. (1993). Risk management: Coordinating corporate investment and
financing policies. Journal of Finance.
Stulz, R. (1984). Optimal hedging policies. Journal of Finance and Quantitative
Analysis.
Master Thesis in GRA19003 02.09.2013
Page 35
Wang Z., C. P. (2010). Hedging and Firm Value: Evidence from the Integrated
Oil and Gas Industry. School of Business, China University of Petroleum
at Beijing.
Books
Mc Donald, R., Derivatives markets, third edition, 2013
Chance, M.D.; Brooks, R., An introduction to derivatives and risk management,
nineth edition, 2013
Electronic resources
http://www.activaresources.com/index.php?id=anualreports
http://www.petroleum.fo/Default.aspx?pageid=8761
http://www.woburnenergy.com/company_reports.htm
http://regalpetroleum.com/search.aspx?kw=annual+reports&x=0&y=0
http://www.globalenergyplc.com/reports2012.asp
http://www.fp.fo/Default.aspx?pageid=1012
http://www.presidentenergyplc.com/investor-information/financial-
reports/?year=2012
http://www.ascentresources.co.uk/pages/reports-accounts
http://www.bowleven.com/investor-relations/reports-results
http://www.northcote.co.uk/default.asp?SDL=NI03179
http://www.wresources.co.uk/category/investors/annual-reports/
http://www.europaoil.com/
http://www.northcote.co.uk/company_links/alpha.asp?SIT=1&ALR=E&SDL=NI
03253
http://www.siriuspetroleum.com/media-
news/searches/495e7bd1e4341f29366c68509d064c9d/
http://www.siriuspetroleum.com/investor/
http://www.petrolatinaenergy.com/investor_07.php
http://www.equatorexploration.com/investors/
http://www.northcote.co.uk/company_links/alpha.asp?SIT=1&ALR=E&SDL=NI
00916
http://www.egdon-resources.com/Company_Reports
Master Thesis in GRA19003 02.09.2013
Page 36
http://www.towerresources.co.uk/investor/downloads.html
http://www.northcote.co.uk/company_links/alpha.asp?SIT=1&ALR=A&SDL=NI
01997
http://www.gulfsands.com/i/digitalreports/May2013/sources/indexPop.htm
http://www.gulfsands.com/s/AnnualReports.asp
http://www.gulfsands.com/i/digitalreports/May2013/sources/indexPop.htm
http://www.bordersandsouthern.com/investor_relations/presentations_and_reports
http://www.northcote.co.uk/default.asp?SDL=NI02128
http://www.investor-hardyoil.com/reports.aspx
http://www.soundoil.co.uk/investors/financial-reports
http://www.clontarfenergy.com/investor-centre/annual-reports_.aspx
http://www.forumenergyplc.com/news/downloads/2007-annual-report-and-
accounts.aspx
http://www.forumenergyplc.com/DocumentLibrary/FEP.AR.20210.pdf
http://www.medoilgas.com/investor/annual-reports.aspx?year=2013
http://www.xtractresources.com/financials.htm
http://matrapetroleum.com/m/index.php?page_id=31
http://www.salamander-energy.com/investor-centre/reports/archive.aspx
http://investors.dom.com/phoenix.zhtml?c=110481&p=irol-reportsAnnual
http://www.northcote.co.uk/company_links/alpha.asp?SIT=1&ALR=A&SDL=NI
00155
http://www.petroceltic.com/investor-centre/financial-reports/fr-2009.aspx
http://www.petrelresources.com/investors/financial-reports
http://www.circleoil.net/financial-reports_2.aspx
http://www.lundin-
petroleum.com/eng/financial_reports.php?surf_next_page=1&s_order=desc&PHP
SESSID=3ebb6c8e8b831d9245a26a93c0c1b66b
http://www.allianceoilco.com/en/annual-reports?afw_id=1067884
http://www.paresources.se/en/Investor_Relations/Financial_Reports/
http://www.dno.no/investor-relations/download-center/annual-reports/?year=all
http://norseenergycorp.no/index.php?name=Investor_Relations%2FFinancial_rep
orts%2FAnnual_reports.html
http://www.iasplus.com/en/standards/ias/ias39
http://www.rocksource.com/archive/category262.html
http://www.interoil.no/?page_id=52
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http://www.detnor.no/en/investors/detnorske-financial-reports/quarterly-and-
annual-reports
http://detnor.no/ar2012en/annual-accounts/
http://www.noreco.com/en/Investors/Reports/
http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=RBRTE&f=A -
oil
http://www.norges-bank.no/en/price-stability/interest-rates/nibor-effective-rate-
annual-average-of-daily-observations/
http://www.norges-bank.no/en/price-stability/exchange-rates/
http://www.euribor-ebf.eu/euribor-org/euribor-rates.html
http://www.riksbank.se/en/Interest-and-exchange-rates/search-interest-rates-
exchange-rates/?g5-SEDP12MSTIBOR=on&from=2013-07-29&to=2013-08-
28&f=Day&cAverage=Average&s=Comma#search
http://www.x-rates.com/historical/
http://www.sec.gov/info/edgar/siccodes.htm
http://wrdsweb.wharton.upenn.edu/wrds/ds/comp/gfunda/index.cfm?navGroupHe
ader=Compustat%20Monthly%20Updates&navGroup=Global
http://www.oslobors.no/