on the determinants of derivatives usage - bi the determinants of derivatives usage ......
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BI Norwegian Business School - Thesis
On the Determinants of Derivatives Usage - Survey on Medium-Sized, Private, Non-F inancial F irms in Norway -
Supervisor: Paul Ehling
Exam code: G R A 19003
Written by:
Jannicke Mansika Olsen Louise E. E. Samuelsson
Hand-in date: 03.09.2012
Campus: BI Oslo
Program: Master of Science in Business and Economics – Major in Finance
This thesis is part of the MSc program at BI Norwegian Business School. The school takes no
responsibility for the methods used, results found and conclusions drawn.
Thesis in GRA 19003 03.09.2012
Page i
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A BST R A C T .................................................................................................................................... I I!
I . IN T R O DU C T I O N ................................................................................................................. 1!
I I . PRI O R L I T E R A T UR E A ND H YPO T H ESIS D E V E L O PM E N T .................................... 3!
A .! Prior empirical findings ................................................................................................ 3!
B .! Focus area ..................................................................................................................... 5!
B .1. ! C E O compensation ................................................................................................... 5!
B .2.! F inancial distress ..................................................................................................... 6!
B .3.! Foreign exchange exposure ..................................................................................... 7!
B .4.! F irm size ................................................................................................................... 7!
B .5.! Industry ..................................................................................................................... 8!
I I I . D A T A ................................................................................................................................... 11!
A .! Data collection ............................................................................................................ 11!
B .! Dependent variable ..................................................................................................... 12!
C .! Independent variables ................................................................................................. 12!
D .! Descriptive statistics .................................................................................................... 14!
E .! Correlations ................................................................................................................. 14!
I V . G E N E R A L R ESU L TS ........................................................................................................ 16!
A .! Regression results ....................................................................................................... 16!
V . M A IN A N A L YSIS ............................................................................................................... 19!
A .! U tility theory and managerial compensation ............................................................. 19!
B .! Convexity versus concavity ......................................................................................... 20!
C .! Main results ................................................................................................................. 22!
C .1.! Robustness test: Subsample analysis ..................................................................... 24!
V I . C O N C L USI O N .................................................................................................................... 26!
BIB L I O G R APH Y ......................................................................................................................... 27!
APPE NDI C ES ............................................................................................................................... 30!
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This article investigates the determinants of derivatives usage as part of risk
management in Norwegian private firms of medium size. The data is based on a
survey conducted in 2011 and financial data for fiscal year 2010. !"#$%&'&("#)&*+,-#
net income as a proxy variable to define whether CEO cash bonus is a convex or
concave function of firm value. When incorporating this variable with other firm
characteristics, we find that firms awarding their CEOs cash bonuses that have a
concave function are significantly more pronounced derivatives users than both
(1) firms awarding their CEOs cash bonuses that have a convex function and (2)
firms with no CEO cash bonus policy. These findings are further supported by a
subsample analysis and we conclude %./%#/#)&*+-, derivatives usage is positively
affected when the firm has a concave cash bonus structure as part of their CEO
compensation. Further, we find that firms with revenues in foreign currencies are
more likely to use derivatives than firms with revenues in local currency, and
larger firms are more pronounced derivatives users than smaller firms.
Thesis in GRA 19003 03.09.2012
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Firms are facing various types of risks such as interest rate volatility, equity risk,
commodity risk and foreign exchange exposure. To be able to monitor and
mitigate these risks, it is important for firms to identify them. In this aspect, risk
management is an important activity of any firm and is an interesting research
field. Motivations as to why firms have incentives to hedge against risk include
liquidity issues, economies of scale arguments, financial distress and ownership
structures. Extensive studies have been conducted on the use of derivatives in risk
management, the majority of which focus on large, public firms. The main
purpose is often to identify what motivates the use of such financial instruments.
Several surveys have also been conducted on the use of derivatives, contributing
to different databases for academic research in several nations. For Norwegian
firms, research on the use of derivatives is limited.
This study therefore examines risk management activities of medium-sized,
private, non-financial firms in Norway in 2010. Specifically, we investigate
whether the use of derivatives in risk management is related to managerial
incentives, financial distress, foreign exchange exposure, firm size and industry.
Our focus is on medium-sized firms and due to the limited amount of information
regarding hedging activities in such companies, we have collected data from 173
firms through questionnaires. We have also retrieved financial information from
the Proff Forvalt database. To test what determines the use of derivatives we have
applied a logistic regression.
The results we document support several of the motivations for risk management.
We find a significant positive relation between the use of derivatives and
performance based compensation in the form of cash bonuses. The results imply
that firms where the CEO is compensated through cash bonuses are more likely to
use derivatives than firms without this type of compensation.!Due to this finding
we investigate cash bonus compensation further. Bonus plans are often
characterized by having a convex and concave region1, and these two regions
induce different managerial incentives for hedging. Smith and Stulz (1985) argue
1 See Kim et al. (2008).
Thesis in GRA 19003 03.09.2012
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that managers faced with a convex compensation structure are more likely to be
risk seeking and are thus not expected to hedge. Conversely, when faced with a
concave compensation structure, managers become more risk averse and should in
theory be more likely to hedge against risks. In order to determine whether !"#$%&
compensation plans are in the concave or convex region, we applied common
features of executive bonus plans to construct proxies. We used net income as a
proxy for the earnings measure. By comparing net income figures in 2010 to
2009, we defined a firm&s cash bonus structure as concave if earnings increased
during the period. If earnings '()#(*%('+,*,!"#$&%,)*%-,./01%,%2#1)21#(,"%,'(!"0(',
as convex. When constructing an interaction term for net income and cash bonus,
and treating it as a separate variable in the regressions, we find support for Smith
and Stulz (1985). Specifically, the results show that firms in the concave region
with cash bonus policies are significantly more pronounced derivatives users than
both (1) firms in the concave region but with no cash bonus policies and (2) firms
in the convex region, regardless of cash bonus policies. Furthermore, the results
from a subsample analysis that only consists of firms with cash bonuses as part of
their compensation policy make our findings more robust.
We further find that companies with revenues in foreign currencies are more
likely to use derivatives. We are not able to find a significant association between
derivatives use and firms with costs in foreign currencies. We also document that
firm size has a positive and significant impact on the use of derivatives, which
may be supportive of the economies of scale argument. The results also confirm
that sector has a significant effect on derivatives usage. The analysis show that
firms operating in the primary products sector are more pronounced derivatives
users than both firms in the manufacturing sector and the service sector. Finally,
we find no significant relationship between firms´ debt-to-equity ratios or
liquidity ratios and the use of derivatives. Prior studies regarding this topic deliver
mixed results.
The remainder of the paper is structured as follows. In section II we discuss prior
literature and develop hypotheses. Section III describes the data and examines the
descriptive statistics. Section IV covers general results while we in section V
present and discuss the main results for this study. Section VI concludes the study.
Thesis in GRA 19003 03.09.2012
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Financial theory provides several descriptions of incentives for derivatives usage,
and there are numerous international studies on the use of derivatives.
A . Prior empirical findings
The Wharton surveys raise important questions regarding risk management
practices suitable for academic research.2 One of the main conclusions across all
three surveys is that the use of derivatives is heavily tilted towards large non-
financial firms and is significantly less amongst smaller firms. From their four
broad classifications of risk; interest rate, foreign exchange, commodity, and
equity risk, they find that the most commonly managed risk is the foreign
exchange risk. Finally, they conclude that the use of derivatives was mainly for
risk management purposes with the main objective of reducing cash flow
volatility.
A more recent study conducted by Bartram et al. (2009) investigates 7,319 firms
across 50 countries, focusing on the underlying motives for the use of derivatives.
They test several financial theories regarding the use of derivatives, but their
findings are ambiguous. They find support for the financial distress hypothesis, as
their data indicate that firms that use derivatives have higher leverage and fewer
liquid assets. However, they also find that these firms are of larger size and have
longer debt maturities, characteristics that contradict the hypothesis. Furthermore,
theory predicting that management incentives are correlated with derivatives
usage is tested. Their expectation was that senior managers who have highly
undiversified positions will use derivatives to hedge diversifiable risk. However,
their findings exhibit no support for this hypothesis. Finally, their findings
indicate, inter alia, that derivatives usage can have significant effects on other firm
decisions such as the level and maturity of debt, dividend policy, holdings of
liquid assets and the degree of operational hedging.
2 In total, the Wharton School has engaged in three consecutive questionnaire- based surveys
regarding non-financial corporations in the United States, carried out in 1994, 1995 and 1998. See
Bodnar et al. (1995), Bodnar et al. (1996) and Bodnar et al. (1998).
Thesis in GRA 19003 03.09.2012
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Research on the use of derivatives in Norwegian firms as part of their risk
management is limited. Børsum and Ødegaard (2005) investigates how
Norwegian, non-financial firms protect themselves against flutctuations in
currency markets and what measures are undertaken to hedge this risk. They find
that 91% of the responding firms use some form of currency hedging techniques,
whether it is derivatives or natural hedging. Out of these firms, 61% report using
derivatives, thereby making it the most applied technique. They also find that
larger firms use derivatives to a greater extent than smaller firms, which is
consistent with the international empirical findings. This fact is often supported by
the economies of scale argument. They further find that 86% of the firms protect
themselves against currency volatility, both for revenues and costs. 43% of the
companies say that the motive for protecting themselves against currency
fluctuations is to reduce the risk for the owners. Only 3% of the companies report
that their motive is to speculate in the currency market, which is consistent with
the finding in the Wharton surveys.
Storm (2011) investigates Norwegian, private, non-financial firms, with data
collected through a survey where 82 firms out of 309 respondents report using
derivatives. He finds that 45% of the users are large firms, which may be support
for the economies of scale argument. Furthermore, the study concludes that the
degree of foreign exhange exposure will impact the use of derivatives.
Our study complements the survey conducted by Storm (2011), with new
questions regarding performance based compensation of CEOs. Our study differ
from Storm (2011) in that our main focus is on the relation between manager
incentives and the potential effect on firms& risk management decisions. Smith
and Stulz (1985) argue that the structure of managerial compensation can have an
(!!()2, /0, $*0*3(#%&, #"%4, *5(#%"/06, 78()"!")*99:+, "!, 2-(, incentive structure is a
concave function of firm value, making the managers utility to be concave in firm
5*91(+, 2-(,$*0*3(#, ;"99, -*5(, "0)(02"5(%, 2/, #('1)(, #"%4, *0', "02(0%"!:, 2-(, !"#$&%,
hedging activity. However, if the structure is a convex function of firm value,
making the managers utility to be convex in firm value, they suggest that the
manager becomes less risk averse and is therefore expected to hedge less.
Empirical research regarding the predictions of Smith and Stulz (1985) provide
Thesis in GRA 19003 03.09.2012
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mixed results. Rogers (2002) and Tufano (1996) both find that firms where
managers hold options use less derivatives, consistent with Smith and Stulz
(1985). Haushalter (2000) was not able to find this relationship. Kim et al. (2008)
investigate the relation between managerial bonus plans and corporate derivatives
usage, with focus on how bonus plans often have both convex and concave
regions. Their findings support Smith and Stulz (1985) as they found a negative
relation between derivatives usage and managerial bonus plans with a convex
function and a positive relation for managerial bonus plans with a concave
function.
B . Focus area
Theory suggests that the use of derivatives in risk management can, inter alia,
increase firm value, reduce cash flow volatility and/or impact managerial
incentives. These factors may be a motivation for using derivatives. In this thesis
we investigate such motivations and analyze the determinants of derivatives
usage. We will study the five hypotheses listed below, where the main focus will
be to determine if CEO compensation has an impact on derivatives usage.
B .1. C E O compensation
Executives, like most people, usually have a highly undiversified financial
position as they receive substantial wealth from their employment by the firm. If
managers are risk averse, they will hedge diversifiable risk. With this hypothesis
we will investigate the potential relationship between the use of derivatives and a
!"#$%&,)/$8(0%*2"/0,8/9"):<
!"#$ CEOs receiving performance-based compensation are more likely to
engage in derivatives usage.
Compensation schemes are important when trying to align CEO incentives with
shareholder incentives = that is, increasing firm value in order to maximize
shareholder value. Thus, incentives should be constructed in such a way that when
the CEO maximizes own expected utility, he also maximizes shareholder value.3
Smith and Stulz (1985) argue that compensation that is similar to options will
3 See Smith and Stulz (1985) for further details.
Thesis in GRA 19003 03.09.2012
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induce managers to hedge less as the compensation structure will be more convex.
They use bonus plans as an example of a convex structure, where the manager
receives a bonus only in the scenario where accounting earnings meet a specific
target. Prior studies produce mixed findings regarding the relationship between
derivatives usage and compensation. Wysocki (1998) find no association between
the use of derivatives and the risk profile of CEO compensation. Rogers (2002)
find a significant negative relation between CEOs stock and options holdings and
!"#$%&,'(#"5*2"5(%,1%*3(+,which is consistent with theory. This also indicates that
derivatives are most commonly used as hedging instruments and not used for
speculative purposes. Rajgopal and Shevlin (2002), investigating firms in the oil
and gas industry, also find that the use of executive stock options has a negative
impact on derivatives usage. We use options, cash bonus and restricted stock as
proxies for performance based compensation.
B .2. F inancial distress
Theory predicts that the use of leveraged financing increases the likelihood that a
firm will use derivatives. Risk management can reduce the expected costs
associated with financial distress.4 By reducing the chance of financial distress, an
optimal debt-ratio can more easily be obtained. Smith and Stulz (1985) argue that
firms with existing debt can benefit from having a reputation for hedging, as
hedging may reduce the cost of debt. Several previous studies have ambiguous
findings. Nance et al. (1993); Mian (1996); Geczy et al. (1997); and Guay (1999)
are all studies that test whether economic theories for optimal hedging can predict
derivatives usage by firms. Two of these studies find support for a positive
relation between hedging and leverage while the remaining two fail to find such a
connection. Regarding liquidity, Clark et al. (2006), find that firms using
derivatives for hedging purposes have significantly lower levels of liquidity
relative to non-hedgers. Bartram et al. (2009) document the relationship regarding
debt and liquidity in their 2003 survey. They find that derivatives users have
higher leverage as well as lower quick ratios and fewer tangible assets. Based on
these theories we test the following hypothesis:
4 See Rampini and Viswanathan (2010).
Thesis in GRA 19003 03.09.2012
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!%#$ Derivatives users have significantly higher leverage and fewer liquid
assets.
We use debt-to-equity5 as a proxy for leverage and liquidity ratio
6 as a proxy for
liquid assets.
B .3. Foreign exchange exposure
Many firms are exposed to the risk of fluctuating exchange rates. The settlement
of contracts, cash flows, and firm valuation are affected by changes in exchange
rates. A company is exposed to exchange rate risk if its value is affected by
fluctuations in a foreign currency.7 This exposure can take a direct form through
import or export and buying or selling domestic goods/ services denominated in a
different currency. Based on this, we predict that companies exposed to different
currencies related to revenues and costs are more actively using derivatives.
Bodnar et al. (1998) find evidence of this relationship. We test the following
hypothesis:
!&#$ There is a significant relation between foreign exchange exposure and
derivatives usage.
The proxy used for foreign exchange exposure is the percentage amount of
revenues and costs denominated in a foreign currency.
B .4. F irm size
There are several reasons why the size of the firm may affect the incentive to
hedge. Financial distress can lead to situations where the firm faces direct legal
cost. For smaller firms, this cost might be a higher portion of the market value of
the firm which implies that these firms are more likely to hedge.8 In addition,
small firms are likely to have fewer natural hedging alternatives. These firms
might have a smaller product range, thereby making them more exposed to
volatility in demand. This is an additional argument as to why one can expect that
5 We define debt/equity as the debt-to-equity ratio.
6 We define total current assets/ current liabilities as the liquidity ratio.
7 See Børsum and Ødegaard (2005).
8 See Nance et al. (1993) and Warner (1977).
Thesis in GRA 19003 03.09.2012
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smaller firms in fact should use more derivatives than larger firms. However,
several studies argue that large firms are more likely to have the resources to
warrant the use of derivatives compared to smaller firms.9 This is based on an
economy of scale argument, meaning that larger firms are more likely to employ
managers with the specialized information to set up a derivatives program.
Moreover, large firms often have more developed risk management systems than
smaller firms. Finally, the market for trading derivatives includes a portion of
transaction cost. By once again looking at economies of scale, it can be argued
that this cost is easier to bear for larger firms.10
Based on these incentives, we
study the following hypothesis:
!'#$ There is a significant relation between firm size and derivatives usage.
We use total assets11
as the proxy for firm size.
B .5. Industry
We believe that the idiosyncratic risk specific for each industry may be a
significant determinant for firms risk management policies and their use of
derivatives for this purpose. The use of derivatives is more feasible for certain
industries, as the underlying assets are widely exchanged. However, in certain
industries, hedging by derivatives is not even possible, as there is no derivative for
the product. We therefore investigate the following hypothesis:
!(#$ There is a significant relation between industry and derivatives usage.
The Wharton surveys consistently document that derivatives usage is highest
among firms in the primary products sector, followed by the manufacturing sector.
Firms in the service sector have the lowest level of derivatives usage, although the
number increases throughout the period (1995 = 1998). Two proxies are used
when testing the association between industry and derivatives usage. The first is
based on industry defined by NACE codes developed by the European
9 See Pennings and Garcia (2004), Bodnar et al. (1998), and Block and Gallagher (1986).
10 See Nance et al. (1993).
11 See Guay and Kothari (2003).
Thesis in GRA 19003 03.09.2012
Page 9
commission.12
The second divides the sample of firms based on aggregate sector
level, which includes primary products, manufacturing and service sector.
Our predictions are summarized in Table I.
12 See http://ec.europa.eu/environment/emas/pdf/general/NACEcodes_en.pdf.
Thesis in GRA 19003 03.09.2012
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Table I (Predictions)
Based on prior empirical research we present a table of predictions with respect to
the variables in each hypothesis. Among others, we base these predictions on the
following previous literature: Smith and Stulz (1985), the Wharton surveys, Clark
et al. (2006), Nance et al. (1993), and Pennings and Garcia (2004).
Independent variables Our prediction !
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13 With respect to prior studies and existing theory, we expect there to be a negative association
between the use of derivatives and firms compensating CEOs through options (ESOs), restricted
stock and cash bonuses. 14
We expect to find a positive association between leverage and derivative usage, while we
expect a negative relation between liquidity and derivatives usage. 15
Due to previous conflicting results we are not sure what to expect in regards to firm size. 16
Testing industry based on NACE codes will impose an extensive amount of variables in a
regression. Due to a relatively small sample size we expect that it will not give any significant
results. Dividing the sample firms based on aggregated sectors will however impose fewer
variables into the regression. As the primary and manufacturing sectors usually have more liquid
exchanges for the underlying asset, we expect there to be a positive relationship between the use of
derivatives and firms in these sectors. However, we expect a negative relation between derivatives
usage and firms in the service sector. 17
Based on previous findings we expect to find a positive relationship between foreign exchange
exposure and derivatives usage, both in regards to revenues and costs.
Thesis in GRA 19003 03.09.2012
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((()* 8&$&
Currently, there is no available database containing information about Norwegian,
8#"5*2(, !"#$%&,1%(,/!,'(#"5*2"5(%6, >0,/#'(#, 2/, %21':,'"!!(#(02, #(9*2"/0%-"8%, "0, 2-"%,
market, data needs to be collected. We find that the best way to answer our
research question and to test the hypotheses in this study is through a survey. Our
research is based on cross-sectional data with financial data retrieved from the
fiscal year of 2010.18
A . Data collection
Financial firms seldom act as an end user of derivatives as they often deal with
such instruments on behalf of clients or for other trading purposes. Because of the
0*21#(, /!, !"0*0)"*9, !"#$%&, operations, they are not considered in this study.
Moreover, the majority of prior research on this topic investigates large, public
firms.19
The ownership structure in larger firms is often centralized, whereas it is
more concentrated in smaller firms. Smith & Stulz (1985) argue that when the
ownership structure is more concentrated, the motivation to hedge increases as the
owners are less likely to hold well-diversified portfolios. Since the manager of the
firm often handles the hedging activity, his/ her risk aversion can be an important
factor for managing risk. In order to capture this relationship, this study will focus
on medium-sized firms.
The European Commission defines firm size based on headcount, turnover or
balance sheet size. For the purpose of this analysis we use turnover to define our
sample. For medium-sized enterprises, this corresponds to approximately NOK
100 million to NOK 400 million. We exclude Norwegian subsidiaries of foreign
companies. By using Proff Forvalt, a database containing firm =and financial
information on Norwegian companies, we obtain a sample of 2,449 firms.20
We
received 173 responses to our questionnaire, which gives a response rate of 7.1%.
18 We have replicated a survey conducted by Storm (2011) with some modifications. We used the
same software to distribute the questionnaire : Questback (2012). 19
See Nguyen & Faff (2002), Nance et al. (1993), and Brunzell et al. (2011). 20
This sample has been somewhat reduced due to the lack of contact information on some firms.
Thesis in GRA 19003 03.09.2012
Page 12
B . Dependent variable
In the questionnaire the respondents *0%;(#(',?:(%@,/#,?0/@,2/ whether they use
derivatives for risk management. Our dependent variable is therefore categorized
as a binary v*#"*.9(, 2-*2, "%, (A1*9, 2/, ?B@, "!, 2-(, !"#$, *0%;(#(', ?:(%@, C"6(6, 1%(,
'(#"5*2"5(%D+, *0', ?E@, "!, 2-(, !"#$, *0%;(#(', ?0/@6,We do not wish to investigate
derivatives usage for speculative purposes. Further, we do not include natural
hedging as part of the dependent variable, but we do observe from the
questionnaire that there are respondents who use this as part of their risk
management. Nevertheless, we will only investigate hedging by the use of
derivatives.
C . Independent variables
The proxies discussed under the five hypotheses in section II constitute our
independent variables, and can be viewed in Table II. We have continuous,
nominal and ordinal variables which can be seen from the table. The debt-to-
equity ratio and liquidity ratio were retrieved from Proff Forvalt based on
financial statements and key figures. From the questionnaire we collected the
percentage amount of revenues and cost that the firms report having in a foreign
currency. By multiplying these 8(#)(02*3(%, ;"2-, 2-(, !"#$%&, 2/2*9, #(5(01(%, *0',
costs retrieved from Proff Forvalt, we obtained the nominal amount denominated
in a foreign currency. For firms without a percentage of foreign exchange
exposure this amount is set to zero. Firm size "%,.*%(',/0,!"#$%&,2/2*9,*%%(2%6,F-(%(
numbers were also retrieved from Proff Forvalt. The three proxies for CEO
compensation are dummy variables. They take on the value /!, ?B@, "!, 2-(,GHI,
receives /82"/0%+,)*%-,./01%(%,/#,#(%2#")2(',%2/)4%+,*0',?E@,/2-(#;"%(6,>0!/#$*2"/0,
regarding such compensation was obtained through the questionnaire. For NACE
codes we have 17 different industries, which means that they take on the value
from 1 - 17. For aggregated sector level they are divided into three, where the
primary 8#/'1)2%,%()2/#, 2*4(,/0,2-(,5*91(,?B@+, 2-(,$*01!*)21#"03 sector is set to
?J@,*0',2-(,%(#5")(%,%()2/#,"%,%(2,2/,?K@6,>0'1%2#:,"0!/#$*2"/0,;*%,(L2#*)2(',!#/$,
Proff Forvalt. Based on industry information, we divided the firms into the three
different sectors. In total we have 10 different independent variables.
Thesis in GRA 19003 03.09.2012
Page 13
Table I I (Description of variables)
Variable De finition Type of variable SourceDerivatives Usage Nominal Survey
Debt-to-Equity Ratio Debt/Equity Continuous Proff Forvalt
Liquidity Ratio Total current assets/Total current liabilities Continuous Proff Forvalt
Foreign Currency Revenue % of revenues in foreign currency Continuous Survey/ Proff Forvalt
Foreign Currency Cost % of costs in foreign currency Continuous Survey/ Proff Forvalt
Total Assets Total equity + Total liabilities Continuous Proff Forvalt
NACE Industry Sample of firms divided into 17 different industries Nominal Proff Forvalt
Sector Sample of firms divided into 3 aggregated sectors Nominal Own division
Options Nominal Survey
Cash Bonus Nominal Survey
Restricted Stock Nominal Survey
Dummy that takes the value 1 if a firm reports using
derivatives and 0 if they report not using derivatives
Dummy that takes the value 1 if a firm reports rewarding
CEO stock options and 0 if not
Dummy that takes the value 1 if a firm reports rewarding
CEO cash bonus and 0 if not
Dummy that takes the value 1 if a firm reports rewarding
restricted stocks and 0 if not
Thesis in GRA 19003 03.09.2012
Page 14
D . Descriptive statistics
Appendix 1 presents a statistical summary of the characteristics of the variables.
Out of the 173 firms that responded to our survey, 73 state that they use
derivatives. On average, derivatives users have a higher debt-to-equity ratio than
non-users, which is in line with our expectations. However, we also observe that
derivatives users have higher liquidity ratios than non-users, which is conflicting
with our expectations. Furthermore, the descriptive statistics show that derivatives
users have higher degree of foreign exchange exposure compared to non-users.
This can be seen in Appendix 4. The average and median size of a firm within the
group of derivatives users is considerably larger than for firms within the non-user
group, measured in total assets. This indicates that our sample supports that larger
companies are more likely to use derivatives. For an overview of the industries
and their representation in our sample, we refer to Appendix 2. Due to the fact that
the sample size is relatively small, the breakdown of all respondents into different
industries based on NACE classification is most likely biased. Hence, there is a
chance that the sample cannot be generalized to all firms in each industry.
Therefore, dividing the firms into an aggregate sector level will provide a less
biased division. As can be seen in Appendix 3, derivatives usage is most dominant
in the primary product sector. With respect to performance based compensation,
40% of the firms report the use of cash bonuses for CEOs. 5% of the respondents
report the use of options as CEO performance based compensation, and only 3%
report that their CEO receives restricted stocks.
E . Correlations
We estimate the Spearman correlation coefficients in order to determine whether
there is a significant association between the dependent and the independent
variables, and if so, how they correlate with each other.21
As we have non-normal
variables, the Spearman correlation matrix is more appropriate to apply than the
Pearson correlation matrix as it does not require a linear relationship.22
We
observe that six of the variables are significantly correlated with the dependent
variable.
21 See Table III.
22 See http://datalab.morningstar.com/knowledgebase/aspx/Article.aspx?ID=550&Country=us.
Thesis in GRA 19003 03.09.2012
Page 15
Table I I I (Spearman correlation matrix)
Derivatives Usage Debt-to-Equity Ratio Liquidity Ratio Foreign Currency Revenue Foreign Currency Cost Total Assets NACE Industry Sector Options Cash Bonus Restricted Stock
Derivatives Usage 1 -0.036 0.034 0.451** 0.290** 0.276** -0.167* -0.287** -0.042 0.188* -0.034
Debt-to-Equity Ratio 1 -0.586** -0.126 -0.095 -0.075 0.199** 0.063 -0.100 -0.114 -0.206**
Liquidity Ratio 1 0.056 0.039 -0.007 -0.119 -0.010 0.112 0.102 0.104
Foreign Currency Revenue 1 0.558** 0.291** -0.229** -0.252** 0.048 0.264** 0.156*
Foreign Currency Cost 1 0.125 -0.157* -0.131 0.091 0.301** 0.145
Total Assets 1 -0.049 -0.358 0.109 0.113 0.063
NACE Industry 1 0.627** -0.118 -0.038 -0.051
Sector 1 -0.060 0.013 -0.058
Options 1 0.128 0.098
Cash Bonus 1 0.233**
Restricted Stock 1
*. Correlation is significant
at the 0.05 level (2-tailed).
**. Correlation is significant
at the 0.01 level (2-tailed).
Thesis in GRA 19003 03.09.2012
Page 16
(9)* :2+2%&1*%2#.1$#
A . Regression results
In Table IV we report the results of seven logistic regression models.23
Each
model contains different combinations of the independent variables. The results
identify several variables as being %"30"!")*029:,#(9*2(',2/,*,!"#$%&,'(cision to use
derivatives in their risk management programs. The findings suggest that a firm is
more likely to hedge if it has revenues denominated in foreign currency
(significant at 1 = 5% level), if the firm is large (significant at a 5 = 10% level),
and if it operates in the primary products sector (significant at a 1 = 5% level). We
do not find a positive association between the use of derivatives and leverage,
neither do we observe the expected negative relation between liquidity and
derivatives usage. In the case of costs denominated in foreign currencies, the
estimated coefficient is consistently positive as expected, but only significant in
one of the models (5% level).
Furthermore, for performance based compensation, which is the main focus of this
study, the coefficient for options is negative as expected but not significant. The
estimated coefficient for restricted stock is also negative, consistent with our
expectations, but is only significant in one of the models (10% level). Only cash
bonus exhibits statistically significant results across all four models where it has
been included. In two of the models, cash bonus is significant at a 10% level and
in the remaining two at a 5% level. The fact that there is a positive relation implies
that firms awarding CEOs cash bonuses are more pronounced derivatives users
than firms without this type of compensation. This goes against our initial
expectation. Bonus plans are structured to impose different managerial incentives.
Smith and Stulz (1985)24
argue that bonus plan compensation is a convex function
of accounting earnings and theory thus predicts that the manager will be more risk
= seeking, thereby being less likely to use derivatives. However, typical bonus
characteristics introduce both a convex and a concave region in the bonus plan. In
order to explain the documented positive relation between cash bonuses and
derivatives usage we want to control for the region of the compensation structure.
23 See Appendix 5 for further information on the logit regression model.
24 See page 403 in their article.
Thesis in GRA 19003 03.09.2012
Page 17
More specifically, we will investigate whether the CEOs in our sample who
receive cash bonuses have an end-of-period wealth which is a concave function of
the end-of-period firm value.
Thesis in GRA 19003 03.09.2012
Page 18
Table I V (General regression results)
This table represents the regression results from 7 logit models consisting of different combinations of the independent variables. The significance is given at a
1%(*), 5%(**) or a 10%(***) level. For the sector variable, the primary sector acts as the reference category, meaning that the impact that manufacturing and
service has on derivatives usage is compared to the reference. This gives us no coefficient for the primary sector. None of the 17 NACE industries are significant.
N=173 Coeff. Sig. Coeff. Sig. Coeff. Sig. Coeff. Sig. Coeff. Sig. Coeff. Sig. Coeff. Sig.
Debt-to-Equity Ratio -0.001 (0.323) 0.000 (0.789) -0.001 (0.190)
Liquidity Ratio 0.051 (0.567) 0.049 (0.438)
Foreign Currency Revenue 0.094** (0.03) 0.123* (0.000) 0.117* (0.000) 0.093* (0.002)
Foreign Currency Cost 0.014 (0.678) 0.010 (0.755) 0.067** (0.017)
Total Assets 0.006** (0.097) 0.009** (0.016) 0.007*** (0.095)
NACE Industry - - - -
Sector
Primary (0.03) (0.000) 0.012
Manufacturing -0.838 (0.129) -1.185** (0.018) -1.002** (0.056)
Service -1.323* (0.009) -1.792 (0.000) -1.408* (0.003)
Options -1.146 (0.118) -1.013 (0.265) -0.737 (0.336)
Cash Bonus 0.624*** (0.097) 1.321* (0.001) 0.997* (0.004) 0.642*** (0.063)
Restricted Stock -1.842*** (0.07) -1.175 (0.217) -0.912 (0.221)
Model 7Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
Thesis in GRA 19003 03.09.2012
Page 19
9)* ;&/+*&+&14#/#
A . Utility theory and managerial compensation
Smith and Stulz (1985) state that managers& expected utility depends on the
distribution of the firm&s payoff. They further assume that managers are risk
averse, and that the indirect utility function of wealth is strictly concave. Hedging
)-*03(%, 2-(, '"%2#".12"/0, /!, *, !"#$&%, 8*:/!!, which further changes managers&
expected utility. They also find that managers& hedging decisions have the
following properties:
(1) I!,2-(,$*0*3(#&% end-of-period wealth is a concave function of the end-of
period firm value, the optimal hedging strategy is to hedge the firm
completely, given that this is feasible. If the firm is completely hedged,
the manager&s expected income is maximized. They explain this through
M(0%(0&%, >nequality which states that the expected value of a concave
function of a random variable is smaller than the value of the function
evaluated at the expected value of the random variable. Hence, the
manager will only want to bear the risk if he is rewarded with a higher
payoff. This is not the case if the firm is fully hedged as the expected
income will be maximized, i.e. the manager does not want to take on risk.
(2) I!,2-(,$*0*3(#&% end of period wealth is a convex function of the end-of
period firm value, but the manager&s expected utility is still a concave
function of the end-of-period value of the firm, the optimal strategy will
generally be to eliminate some uncertainty through hedging. Here, the
manager&s expected income is higher if the firm does not hedge, since
his/her income is a convex function of firm value. However, since the
manager is risk averse he will therefore wish to give up some expected
income to reduce risk. Despite this trade off, the manager will generally
not choose a strategy that results in a riskless income.
(3) If the $*0*3(#&% end-of-period utility is a convex function of the end-of-
period firm value, Jensen&s Inequality implies that if the firm is not
hedged at all, the $*0*3(#&% end-of-period utility has a higher expected
Thesis in GRA 19003 03.09.2012
Page 20
value. Managers will thus be risk-seeking when the expected utility is a
convex function of the value of the firm.
Based on this, Smith and Stulz (1985) find that managers, whose compensation is
a concave function of firm value, have the incentive to reduce the risk of volatility
in cash flow, i.e. engage in derivatives for risk management. In our analysis we
found that firms with CEOs who receive cash bonuses are more pronounced
derivatives users than firms without this type of compensation. We therefore
proceed to investigate whether these CEOs have compensation structures that
make their end-of-period utility a concave function of the end-of-period value of
the firm.
B . Convexity versus concavity
Kim et al. (2008) investigate the effect of risk management incentives resulting
!#/$, $*0*3(#"*9, ./01%, 89*0%, /0, !"#$%&, '(#"5*2"5(%, 1%*3(6, F-(:, !/)1%, /0, -/;,
typical bonus plan payoffs have both a convex and a concave region which means
that managers can have an incentive to either increase or decrease a firm&s risk in
order to maximize their expected bonus payments. Their paper is based on Smith
and Stulz (1985) theories on concavity and convexity in compensation structures.
In order to determine whether the bonus plans are in the concave or the convex
region, Kim et al. (2008) look at the following features of bonus plans: First,
executives need to exceed a certain threshold level in order to receive a payoff.
Below this threshold, no bonus is received. Above this threshold, however, the
8*:/!!, "0)#(*%(%,;"2-,8(#!/#$*0)(,18,2/,*,)(#2*"0,?)*8@6 Most bonus plans have
this structure even though the details differ. Also, in a typical bonus plan, a target
payoff is established based on the achievement of a performance target. Murphy
(1998, 2000) concludes that the target levels that are set for these measures are
1%1*99:,.*%(',/0,8#(5"/1%,:(*#&%,8(#!/#$*0)(,/#,)1##(02,:(*#&%,.udget. In order to
understand how a bonus plan can affect the incentives to either take on risk or
reduce risk, consider the following two scenarios. In the first case, a CEO expects
the performance in the current year to be above the target that is already known.
The CEO is likely to believe that he/she is facing a concave function as he/she is
far from the threshold level but most likely closer to the cap. In this case, it is
Thesis in GRA 19003 03.09.2012
Page 21
desirable to lock in high bonus payments. This is because when the expected level
of performance is high, the expected payoff is also high as payoff is determined
based on performance. By locking in at this performance level the high bonus
payoff is thereby also secured. In the second case, the CEO expects their
performance to be below the target. In this scenario, the performance is much
closer to the threshold than the cap. This makes the incentive to reduce risk quite
small since locking in at this level might result in little or no bonus payment. The
CEO is therefore facing a convex payoff function.
In order to investigate this relationship it is desirable to know the detail of each
$*0*3(#&%,89*06,71)-,"0!/#$*2"/0,"%,0/2,3(0(#*99:,'"%)9/%(',*0',;(,'/,0/2,-*5(,
this information at hand. Neither did Kim et al. (2008) when constructing their
analysis. However, due to the common features of executive bonus plans it is
possible to construct proxies in order 2/, '(2(#$"0(, ;-(2-(#, 2-(, !"#$&%
compensation plan is in the concave or convex region. Kim et al. (2008) took
advantage of these common features and used net income as an earning measure.
By doing this, they constructed the convexity or concavity of the bonus payoff
function. They used net income as an earnings measure and found a ratio by
dividing net income for the current year by net income in the previous year. In this
scenario, firm performance in the current year is compared to the fi#$&%
performance in the previous year, making the previous year the target. They
defined the convex payoff group as those firms with a ratio less than or equal to
1.0, and the concave payoff group as those firms with a ratio greater than 1.0.
Based on this they hypothesize that CEOs in firms with a ratio below 1.0 are
likely to be closer to the threshold level than the cap (i.e. performance below the
target), which is defined as the convex payoff zone. They further argue that firms
with a ratio above 1.0 (i.e. performance above the target) are closer to the payment
cap than the threshold, which is defined as the concave payoff zone.
Kim et al. (2008) found a negative relation between derivatives usage and CEO
compensation for firms whose managers face a convex payoff function, and a
positive relation for firms whose managers face a concave payoff function. These
results support the prediction of Smith and Stulz (1985).
Thesis in GRA 19003 03.09.2012
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C . Main results
We have replicated the procedure used by Kim et al. (2008) in order to determine
whether the firms in our sample that compensate CEOs with cash bonuses also lie
within the concave payoff region. We use net income as a proxy for the earnings
measure. We construct a dummy for net income which is give0, 2-(,5*91(,?B@, "!,
net income is higher in 2010 than in 2009, i.e. the relevant firm is in the concave
region and above the target. Further, it "%, 3"5(0, 2-(, 5*91(, ?E@, "!, 0(2, "0)/$(, is
lower in 2010 than in 2009, i.e. the relevant firm is in the convex region and is
below the target. In order to investigate whether firms in the concave region,
combined with having a cash bonus compensation policy, are more pronounced
derivatives users than firms without both these characteristics, we constructed
further regressions. The results can be seen in Table V.
In Model 1 we have constructed a multiplicative regression where net income is
multiplied with cash bonus, i.e. the variable explains whether firms that use cash
bonuses as a compensation policy, and are in the concave region, have a
significant impact on derivatives usage. As seen from the results we find no
support for such a relation in this model. Theory suggests that one should always
include the two components in the model when having an interaction term.
However, there may be certain circumstances where it is preferable to only
include the interaction term if it has some particular substantive meaning. In this
instance, we are not interested in the effect that net income has on derivatives
usage alone and we have already documented the effect of having cash bonuses.
Instead, we want to test the effect cash bonus has on derivatives usage when net
income show a convex or a concave structure. Hence, we are only interested in the
interaction between the components and not the components themselves. In
addition, when the interaction term is highly correlated with the components, it
may cause problems with multicollinearity.25
We have therefore constructed
models where we consider the interaction term as a separate variable and include
some of our other previous proxies as control variables. The results are shown in
model 2, 3, and 4 in Table V.
25 See Appendix 6 for correlation matrix.
Thesis in GRA 19003 03.09.2012
Page 23
Table V (Main results)
This table presents 4 different models, *99, )/0%"%2"03, /!, 2-(, N0(2, "0)/$(, 2"$(%, )*%-, ./01%@, 5*#"*.9(, C2-(, "02(#*)2"/0, 2(#$D, "0, /#'(#, 2/, 9//4, *2, "2%, "$8*)2, /0,
derivatives usage. In the first model we look at the interaction term combined with its components while in model 2-4 we have excluded the components from the
regression. The significance is given at a 1%(*), 5%(**) or a 10%(***) level.
N=173 Coeff. Sig. N=173 Coeff. Sig. Coeff. Sig. Coeff. Sig.
Net Income times Cash Bonus 0.846 (0.204) Net Income times Cash Bonus 1.142* (0.006) 1.182* (0.003) 1.314* (0.003)
Net Income 0.164 (0.691) Debt-to-Equity Ratio 0.000 (0.506) -0.001 (0.155)
Cash Bonus 0.213 (0.682) Liquidity Ratio 0.149 (0.361) 0.052 (0.332)
Foreign Currency Revenue 0.105* (0.000)
Foreign Currency Cost 0.050 (0.110)
Total Assets 0.011** (0.018)
NACE Industry - -
Sector
Primary (0.004)
Manufacturing -1.136** (0.037)
Service -1.692* (0.001)
Options -1.139 (0.196)
Restricted Stock -1.240 (0.188)
Model 1 Model 2 Model 3 Model 4
Thesis in GRA 19003 03.09.2012
Page 24
As can be seen, net income times cash bonus is positive and significant at a 1%
level in all three models. The results show that firms in the concave region with
cash bonus policies are significantly more pronounced derivatives users than both
(1) firms in the concave region but with no cash bonus policy and (2) firms in the
convex region, regardless of cash bonus policy.
C .1. Robustness test: Subsample analysis
When removing the two components in the previous analysis, there is a risk that
our inferences about the results are not valid. Therefore, in order to find further
support for our findings, we construct an additional regression. In this sample,
only firms with cash bonuses as part of their compensation policy for CEOs are
included. This results in a weaker sample of 69, but we no longer have an issue
with the interaction term. In this case, we investigate the effect that the net income
dummy has on derivatives usage. More specifically, we examine whether firms
that use cash bonuses as part of the compensation for their CEOs and are in the
concave region have a higher use of derivatives than firms who also use cash
bonuses but are in the convex region. In this instance, we are able to only
investigate this relationship without having to include firms with no cash bonuses.
The results are provided in Table VI. The net income dummy is positive and
significant at a 5% level in two of the models and at a 10% level in the remaining
model. This means (despite having reduced the sample with 60%) that we still
manage to find a positive and significant relation between firms in the concave
region and derivatives usage. Moreover, the results show that firms with CEO
cash bonuses that have a concave structure are more pronounced derivatives users
than firms with CEO cash bonuses that have a convex structure.
The results from this subsample analysis make our findings more robust and we
conclude 2-*2,*,!"#$&%,'()"%"/0,2/,1%(,'(#"5*2"5(%,"%,8/sitively affected when the
firm is in the concave payoff zone and use cash bonuses as part of their CEO
compensation. Furthermore, we are able to support the prediction of Smith and
Stulz (1985) and the findings made by Kim et al. (2008).
Thesis in GRA 19003 03.09.2012
Page 25
Table V I (Subsample test)
This table includes 69 observations representing the firms in our sample where CEOs
receive cash bonuses. It investigates the effect net income has on derivatives usage. The
variable is a dummy, w-(#(,?B@,"%,'(!"0(',*%,2-(,)/0)*5(,#(3"/0,*0',?E@,"%,'(!"0(',*%,2-(,
convex region. The significance is given at a 1%(*), 5%(**) or a 10%(***) level.
N=69 Coeff. Sig. Coeff. Sig. Coeff. Sig.
Net Income 1.060*** (0.056) 1.172** (0.040) 1.255** (0.046)
Debt-to-Equity Ratio 0.014 (0.697)
Liquidity Ratio 0.028 (0.693)
Foreign Currency Revenue 0.029 (0.449)
Foreign Currency Cost 0.040 (0.316) 0.028 (0.525) 0.005 (0.517)
Total Assets 0.009 (0.123)
NACE Industry - -
Sector (0.170)
Primary -1.101 (0.242)
Manufacturing -1.670*** (0.068)
Service
Options
Restricted Stock
Model 1 Model 2 Model 3
Thesis in GRA 19003 03.09.2012
Page 26
9()* <,+'1.#/,+
F-"%, %21':, "05(%2"3*2(%, 2-(, '(2(#$"0*02%, /!, !"#$%&, #"%4, $*0*3($(02, 8#*)2")(%,
using data from 2010 on 173 Norwegian, private, non-financial firms that are of
medium size. One must be conservative when interpreting the results of a multi-
industry study of a few dozen observations. Keeping this in mind, our study offers
support for several findings in prior studies regarding certain firm characteristics,
and their effect on the use of derivatives.
First, we do not find significant results for the financial distress hypothesis. We
do, however, document a positive association between the extent of derivatives
usage and the amount of revenues denominated in foreign currencies. Although
the same results cannot be found for costs, we cannot reject the foreign exchange
exposure hypothesis. Furthermore, the evidence shows that both size and industry
affects hedging activity. Our results show that large firms are more actively using
derivatives. This might be because large firms often enjoy economies of scale
benefits. It could also be that larger companies have more competent management
and stronger focus on risk management, as well as typically having a more
developed risk management system, than smaller companies. In terms of industry,
we find that firms in the primary sector are more pronounced derivatives users
than firms in both the manufacturing and service sector. Finally, although we find
no significant results for CEO options or restricted stock, the evidence show that
firms where CEOs are rewarded cash bonuses are more pronounced derivative
users than firms with no cash bonuses. Bonus schemes often have thresholds that
must be met in order to trigger bonus payments+,*0',*9%/,*,?)*8@,2-*2, 9"$"2%, 2-(,
*$/102,2-*2,)*0,.(,#()("5('6,F-(,2-#(%-/9',9(5(9,*0',2-(,?)*8@,"02#/'1)(,*,)/05(L,
and a concave region to the compensation, inducing different managerial risk
behaviors. Based on Smith and Stulz (1985), we expected that cash bonuses with
a convex structure would induce CEOs to take more risk, and hence hedge less.
Conversely, cash bonuses with a concave structure would make CEOs more risk-
averse and therefore hedge more. Our results show that firms with a concave
payoff structure indeed use more derivatives than firms both in the convex payoff
zone (regardless of cash bonus) and firms that are in the concave region without
the use of cash bonuses. Based on this analysis we conclude that manager
incentives appear to affect choices made in the firms risk management.
Thesis in GRA 19003 03.09.2012
Page 27
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!552+-/'2#
Appendix 1 (Descriptive statistics)
The first window of this table display simple characteristics of all firms in our sample. The two subsequent windows breaks down the characteristics
into derivative users and non-users.
Min. Max. Mean Median STD Min. Max. Mean Median STD Min. Max. Mean Median STD
Derivatives Usage 0,00 1,00 0,42 0,00 0,50 1,00 1,00 1,00 1,00 0,00 0,00 0,00 0,00 0,00 0,00
Debt-to-Equity Ratio -8,61 4 559,85 47,34 2,21 369,35 -9,00 1 161 26,00 2,00 143,48 0,00 4 560 63,00 2,00 468,03
Liquidity Ratio 0,14 72,42 2,07 1,37 5,47 0,00 72,00 3,00 1,00 8,29 1,00 7,00 2,00 1,00 1,00
Foreign Currency Revenue 0,00 1 532 131 62 719 0,00 158 813 0,00 1 532 131 115 327 73 957 225 304 0,00 278 990 24 315 0,00 55 515
Foreign Currency Cost 0,00 1 426 022 52 409 0,00 121 078 0,00 1 426 022 78 196 45 221 170 043 0,00 234 403 33 584 0,00 58 432
Total Assets 4 882 19 917 752 578 513 117 211 2 117 813 4 882 19 917 752 1 090 391 176 685 161 830 23 144 2 818 608 204 842 87 284 361 165
NACE Industry 1,00 16,00 6,95 7,00 3,29 1,00 13,00 6,00 7,00 3,26 1,00 16,00 7,00 7,00 3,19
Sector 1,00 3,00 2,35 3,00 0,78 1,00 3,00 2,00 2,00 0,84 1,00 3,00 3,00 3,00 0,67
Options 0,00 1,00 0,05 0,00 0,22 0,00 1,00 0,00 0,00 0,20 0,00 1,00 0,00 0,00 0,24
Cash Bonus 0,00 1,00 0,40 0,00 0,49 0,00 1,00 1,00 1,00 0,50 0,00 1,00 0,00 0,00 0,47
Restricted Stock 0,00 1,00 0,03 0,00 0,18 0,00 1,00 0,00 0,00 0,16 0,00 1,00 0,00 0,00 0,20
A ll F irms Firms with De rivative s Usage Firms without De rivative s Usage
Thesis in GRA 19003 03.09.2012
Page 31
Appendix 2 (Representation by industry)
Appendix 3
(Representation by aggregate sector level)
NACE Classification
Arts & Entertainment 1 0 0 %
Human Health & Social Work 2 0 0 %
Administrative & Support Activities 6 2 33 %
Scientific & Technical Activities 14 5 36 %
Real Estate 8 5 63 %
Information & Communication 9 2 22 %
Accommodation & Food Service 1 1 100 %
Transporting & Storage 12 8 67 %
Wholesale & Retail Trade 48 14 29 %
Construction 18 3 17 %
Water Supply 4 0 0 %
Electricity & Gas 14 11 79 %
Manufacturing 28 18 64 %
Mining & Quarrying 3 2 67 %
Agriculture 4 2 50 %
Other 1 0 0 %
Number of
Respondents
Number of
Derivatives Users
% Derivatives Use
by Industry
Sector
Primary Product 33 23 69,7 %
Manufacturing 46 21 45,7 %
Service 94 29 30,9 %
Number of
Respondents
Number of
Derivatives Users
% Derivatives Use
by Sector
Thesis in GRA 19003 03.09.2012
Page 32
Appendix 4 (Representation by foreign currency exposure)
This table shows the percentage of derivatives users and non-users that are subject
to a foreign currency with regards to revenues and costs. It also shows the degree
of exposure; whether it is non-existing (0%) or as high as having all denominated
in a foreign currency (100%).
Revenues Costs
0% exposure 29 % 32 %
25% exposure 25 % 34 %
50% exposure 11 % 21 %
75% exposure 27 % 13 %
100% exposure 8 % 0 %
Total 100 % 100 %
Revenues Costs
0% exposure 75 % 60 %
25% exposure 13 % 24 %
50% exposure 5 % 7 %
75% exposure 6 % 9 %
100% exposure 1 % 0 %
Total 100 % 100 %
De rivative s Us e rs
Non-us e rs
Thesis in GRA 19003 03.09.2012
Page 33
Appendix 5 (Logit regression model)
When dealing with a binary dependent variable, an effective model to employ is
the logit model and is expressed as follows:
)*+ ,- . , / 0
Y is a function of the explanatory variables, so this is equivalent to expressing the
model as
)*+ ,- . , / $12 3415675
8
59"
Solving for P gives
,7 /-
- 3 :;<=>?@ =ABCADAEF G
This way, we will not incur probabilities that are either negative or greater than 1.
This model uses a cumulative logistic function to transform the model so that the
predicted probabilities lie within the correct range of 0 to 1. Another model, called
the probit model, applies a cumulative normal distribution to do the same. The
probit model can be expressed as follows:
H<I7G /-
JKLM:;
"%NOCPQ R
However, both the logit and the probit model will in most instances give
approximately the same results. The only situation where the two models will give
significantly different estimation outputs is when the distribution of the binary
dependent variable is heavily skewed towards either 1 or 026
. For our dependent
variable, the distribution is fairly balanced with 42% of the firms reporting the use
of derivatives and 58% reporting no use. Therefore, we will apply the logit model
in our estimation.
26 See Brooks (2008).
Thesis in GRA 19003 03.09.2012
Page 34
Appendix 6 (Correlation matrix)
Appendix 7
(Distributed questionnaire)
Survey on the use of derivatives in Norwegian private firms !This survey is conducted for our final thesis for the Master of Science degree at BI Norwegian
Business School. It seeks to identify the use of derivatives in Norwegian non-financial private
firms. You will anonymously be answering a questionnaire which will require only 5-15 minutes,
depending on your answers.!
!We are very grateful for your contribution and for the time spent to complete the survey.!
!Best of regards!
!Louise Samuelsson and Jannicke Olsen!
!
!!
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ID - number: 0855435 ID - number: 0857807
BI Norwegian Business School
- Preliminary Thesis Report !
Supervisor: Paul Ehling
Exam code and name:
G R A 19002 ! Preliminary Thesis in F inance
Hand-in date:
15.01.2012
Campus:
BI Oslo
Program:
Master of Science in Business and Economics ! Major in Finance
MSc Preliminary Thesis Report 15.01.2012
Page i
!"#$%&'(&)'*+%*+,&
SU M M A R Y .................................................................................................................................... I I!
IN T R O DU C T I O N ........................................................................................................................... 1!
R ESE A R C H PR O B L E M A ND M O T I V A T I O N .......................................................................... 1!
RESEARCH PROBLEM ..................................................................................................................... 1!
BRIEF LITERATURE REVIEW .......................................................................................................... 3!
M E T H O D O L O G Y ......................................................................................................................... 4!
QUESTIONNAIRE ........................................................................................................................... 5!
BIB L I O G R APH Y ........................................................................................................................... 6!
APPE NDI X ...................................................................................................................................... 8!
PROGRESS PLAN ............................................................................................................................ 8!
QUESTIONNAIRE ........................................................................................................................... 9!
MSc Preliminary Thesis Report 15.01.2012
Page ii
Summary
In our master thesis we will study private, non-financial Norwegian firms, with
emphasis on their usage of financial derivatives in risk management programs.
These criterions leaves us with a population of 4 237 firms that will be
investigated based on a questionnaire. We will replicate a survey conducted by
Storm (2010) with certain modifications. In addition, we will focus on the
following two topics:
1) How different sources of compensation to the CEO and CFO will affect
hedging, and also what types of compensations have a strong influence on
the use of derivatives.
2) How higher leverage and fewer liquid assets in the company may affect
hedging.
MSc Preliminary Thesis Report 15.01.2012
Page 1
Introduction
Firms are facing various types of risks, such as interest rate volatility, equity risk,
commodity risk and foreign currency exposure (Bartram, Brown and Fehle 2009)
(Bodnar, Hayt and Marston 1998). These risks are important for firms to be aware
of in order to monitor and handle them. Therefore, risk management is an
important part of the firm and an interesting focus area. There have been
conducted several surveys on the use of derivatives, contributing to different
databases for academic research in several nations. Even though Norway is also
exposed to the various types of risks, research on this area is very limited. In our
survey, we therefore wish to examine financial derivatives practice in risk
management programs for private, non-financial firms in Norway.
Research problem and motivation
Research problem
Theory suggest that the use of derivatives in risk management can increase firm
value, reduce cash flow volatility or handle managerial incentives, among other.
These may be motivations for using financial derivatives. However, because of
the complex nature of such instruments they are often used in the wrong way,
which can lead to firm destruction. The main research problem in this survey is:
How is the use of financial derivatives in risk management programs in
Norwegian, private, non-financial firms that are of medium size?
We will study the six hypotheses listed below:
Hypothesis 1: CEOs and C F Os receiving performance-based compensation are
more likely to engage in financial derivatives usage.
Most executives have a highly undiversified financial position as they receive
substantial wealth from their employment by the firm. This may lead to risk
aversion, which again leads to hedging of diversifiable risk. With this hypothesis
we will investigate if there exists a positive relationship between the use of
MSc Preliminary Thesis Report 15.01.2012
Page 2
!"#$%&'$%"()&*!)&)+$#,(-)./,0"*(&'$/*)0/1$.23)4/,0"*(&'$/*)(5.6)&()('/.7)/0'$/*)
plans or bonus schemes are often linked to firm performance. If there is a
substantial part of non-controllable risk for the CEO or CFO inherent in his/her
compensation, they might be more willing to use derivatives in order to hedge this
risk. This will be one of the main focus areas of our thesis. Wysocki (1998) find
no relationship between the use of derivatives and CEO/CFO compensation that
contains risk Wysocki (1998).
Hypothesis 2: Derivatives users have significantly higher leverage and fewer
liquid assets.
Companies that are in financial distress and have a high debt-ratio are more likely
to use derivatives for hedging purposes. Financial risk management can reduce the
expected value of cost associated with financial distress. Also, by reducing the
chance of financial distress, an optimal debt-ratio can more easily be obtained.
Previous studies also find this relation (Bartram, Brown and Fehle 2006).
Hypothesis 3: The main motivation for using derivatives is to reduce and manage
the volatility in cash flow.
Previous studies support this (Wharton Survey 1995, 1996 and 1998).
Hypothesis 4: There is a significant relationship between firm size and derivatives
usage.
Large firms are more likely to have the resources to warrant the use of derivatives
(Pennings and Garcia 2001). Previous studies confirm that derivatives usage is
heaviest among large firms (Wharton survey 1998). Also, other studies (Mian
1996 and Carter and Sinkey 1998), find evidence for a positive relationship
between a firms derivatives-practice and its size.
Hypothesis 5: There is a significant relationship between industry and derivatives
usage.
In the Wharton surveys, (Bodnar, Hayt and Martson 1996) (Bodnar, Hayt and
Marston 1998), there is evidence of a higher degree of derivatives usage in some
industries than others.
MSc Preliminary Thesis Report 15.01.2012
Page 3
Hypothesis 6: There is a significant relationship between foreign exposure and
derivatives usage.
We assume that companies exposed to different currencies related to cost and
income or assets and liabilities, are more actively using derivates. We also assume
that companies that are naturally hedged practice less derivative usage than
companies that are not. Bodnar and Martson (1998) find evidence of this.
Brief literature review
There exists an extensive amount of surveys conducted internationally on the use
of financial derivatives. Of international studies, the Wharton surveys raise
important questions regarding risk management practices suitable for academic
research. In 1994, the Wharton School undertook its first survey that was sent to
non-financial corporations in the United States (Bodnar, Hayt and Martson 1996).
They concluded from the survey that derivatives were mostly used to reduce cash
flow volatility, and not commonly used for speculation (Bodnar, Hayt, Martson
and Smithson 1995). In total, the Wharton School has engaged in three
consecutive questionnaire-surveys. Based on their second survey published in
1996, they conclude that less than half of all non-financial firms use derivatives
and that the usage is tilted heavily towards larger firms in the commodity and
manufacturing sectors (Bodnar, Hayt and Martson 1996). In their last survey from
1998, they found no evidence that the number of firms using derivatives had
declined over time (Bodnar and Martson 1998). They also concluded that the use
of derivatives in the service industry increased significantly faster than for other
industries. New questions were raised in this survey, especially related to foreign
currency.
Bartam, Brown and Fehle provide international evidence on financial derivatives
usage from 2006. The findings indicate, inter alia, that derivative usage can have
significant effects on other firm decisions such as the level and maturity of debt,
dividend policy, holdings of liquid assets and the degree of operating hedging.
Their analysis also examines the question of what motivates the use of financial
derivatives by corporations (Bartram, Brown and Fehle 2009).
MSc Preliminary Thesis Report 15.01.2012
Page 4
!"#"$%&'()*(+'"(,#"()-(-.*$*&.$/(0"%.1$+.1"#(.*(2)%3"4.$*(-.%5#6(%.#7(5$*$4"5"*+(
practice is limited. One significant contribution was conducted by Norges Bank in
the summer of 2004 and the results were summarized in 2005 by Børsum and
Ødegaard (2005). Their survey investigated how Norwegian firms can protect
themselves against flutctuations in currency markets and what measures were
undertaken. They find that 91 % of the responding firms use some form of
currency hedging technique, whether it is financial derivatives, natural hedging or
operational hedging etc. However, the most used technique is financial derivatives
which 61 %, of the firms reported using. They also find that larger firms use
financial derivatives to a greater extent than smaller firms, which is consistent
with international empirical findings. This fact is most often supported by the
argument of economies of scale. Larger firms have more resources available to
provide knowledge about derivatives and afford the use of them. Also, firms with
economies of scale in applying and continuing risk management operations are
found to use more derivatives (Adams 1999) (Pennings and Garcia 2004). They
further find that 86 % of the firms protect themselves against currency volatility in
income and cost. 43 % of the companies say that the motive for protecting against
currency fluctuations is to reduce the risk for the owners. Only 3 % of the
companies report that their motive is to speculate in the currency market.
Storm (2011) was the first to investigate Norwegian, private, non-financial firms
that are of medium-size. His findings support that firm size matters for the use of
derivatives. He also finds that different types of industries use derivatives on
different levels. Furthermore, the study concludes that the degree of foreign
exposure will impact the use of derivatives.
Methodology
Currently, there exist no database containing information about Norwegian,
8%.1$+"( -.%5#6(,#"()-(0"%.1$+.1"#9( :*()%0"%( +)( #+,0;(0.--"%"*+( %"/$+.)*#'.8#( .*( +'.#(
market, data needs to be collected. We find that the optimal way to answer our
research question and the hypotheses inherent therein will be through a survey.
Last year, the first survey regarding this topic was conducted by Storm (2011).
We will replicate the survey this year with some modifications.
MSc Preliminary Thesis Report 15.01.2012
Page 5
Questionnaire
The data will be collected through a similar questionnaire that will be based on
Storm´s survey, but with some modifications. Modifications of certain questions
are mainly due to poor response to the questions last year. We also modify some
questions to increase the degree of information that can be retrieved, and add new
questions for additional hypotheses testing. We will use the same software
(Questback 2012) as Storm (2010) to build and distribute the questionnaire.
In order to define our population we use the European Commissions definition of
firm size. They define firm size depending on headcount, turnover or balance
sheet total. Based on turnover, medium-sized enterprises are defined as having a
turnover between EUR10 million and EUR 50 million. This corresponds to
approximately NOK 100 million and NOK 400 million. By using Proff Forvalt, a
web site containing firm !and accounting information on Norwegian companies,
we can obtain the relevant population for our survey. By setting the relevant
"#$%&#$'()* +,#$-'%&* .$#/)0* 1$%2* '334'5* %4#36-&#* 7&%1&&3* 89:* ;<<* /$55$63* '3=*
NOK 400 million, excluding firms defined by NACE codes as financial firms), we
obtain a population of 4 237 firms (Proff Forvalt 2010).
The greatest concern regarding the questionnaire is the response rate. It is
expected that there will be non-responses, for example due to a refusal to
participate in the research, a lack of e-mail addresses or other reasons (Saunders,
Lewis and Thornhill 2009). In their survey, Eriksen and Wedøe (2010) made a
comparison of survey responses, and found that the average response rate of a
total of 10 surveys was 31.3 %. The lowest response rate was 20.7 % while the
highest was 76.6 %. Storm (2010) achieved a response rate of 25.7%. He used a
probability sample approach where 2000 firms were randomly selected out of a
total population of 5000 (Storm 2011; 7). In this survey we will include the total
population of 4 237 with the goal of increasing the number of firms responding.
MSc Preliminary Thesis Report 15.01.2012
Page 6
Bibliography
Adams, Don. "Why Corporations Should Hedge." ASX Perspective (Macquarie
University), 4th quarter 1999: 29-32.
Bartram, Söhnke M., Gregory W. Brown, and Frank R. Fehle. "International
Evidence on Financial Derivatives Usage." F inancial Management Vol.38, no. 1
(Spring 2009): 185-206.
Bodnar, Gordon M., Gregory S. Hayt, and Richard C. Marston. "1998 Wharton
Survey of Financial Risk Management by US Non-Financial Firms." F inancial
Management Vol.27, no. 4 (Winter 1998): 70-91.
Børsum, Øystein G., and Bernt Arne Ødegaard. "Valutasikring i norske
selskaper." Penger og Kreditt, January 2005: 29-40.
Carter, David A., and Joseph F Sinkey Jr. "The Use of Interest Rate Derivatives
by End-users: The case of Large Community Banks." Journal of F inancial
Services Research Vol.14, no. 1 (July 1998): 17-34.
circa.europa.eu. CIRCA.
http://circa.europa.eu/irc/dsis/nfaccount/info/data/esa95/en/een00070.htm
(accessed January 5, 2012).
Colquitt, L.Lee, and Robert E. Hoyt. "Determinants of Corporate Hedging
Behavior: Evidence from the Life Insurance Industry." Journal of Risk &
Insurance Vol.64, no. 4 (December 1997): 649-671.
Eriksen, Krister, and Ola Wedøe. "Foreign exchange risk management: How are
the largets non-financial companies in Norway managing their foreign exchange
rate exposure?" June 2010: 1-114.
Euromoney. Euromoneycountryrisk. June 3, 2011.
http://www.euromoneycountryrisk.com/ (accessed January 5, 2012).
MSc Preliminary Thesis Report 15.01.2012
Page 7
Géczy, Christopher, Bernadette A. Minton, and Catherine Schrand. "Why Firms
Use Currency Derivatives." Journal of F inance Vol.52, no. 4 (September 1997):
1323-1354.
Mian, Shehzad L. "Evidence on Corporate Hedging Policy." Journal of F inancial
& Quantitative Analysis Vol.31, no. 3 (September 1996): 419-439.
Nance, Deana R., Clifford W. Smith, and Charles W. Smithson. "On the
Determinants of Corporate Hedging." Journal of F inance Vol.48, no. 1 (March
1993): 267-284.
Pennings, Joost M.E., and Philip Garcia. "Hedging behavior in small and medium-
sized enterprises: The role of unobserved heterogeneity." Journal of Banking &
F inance Vol.28, no. 5 (May 2004): 951-978.
Proff Forvalt. PRO F F F ORVALT - utvidet firma- og regnskapsinformasjon. 2010.
http://www.forvalt.no/foretaksindex2/Default.aspx?show_advanced=1&search_ty
pe=segmented&search_result_type=stacked#searchresult (accessed January 9,
2012).
Questback. Questback Norge. 2012. http://www.questback.com/ (accessed
January 9, 2012).
Saunders, Mark, Philip Lewis, and Adrian Thornhill. Research methods for
business students. Fifth edition. Essex: Pearson Education Limited, 2009.
Storm, Johan Herman. "Survey on Financial Risk Management - Evidence on
Derivatives Usage by Norwegian Non-financial Firms." December 2011: 1-45.
Stulz, René M. Risk Management & Derivatives. 1. South-Western College/West,
2002.
Wysocki, !"#"$%&'%(Managerial Motives and Corporate Use of Derivatives: Some
)*+,"-."/%0123%45567%4-35.
MSc Preliminary Thesis Report 15.01.2012
Page 8
Appendix
Progress plan
Below is a schedule on our intended work progression on the master thesis.
January
- Produce the questionnaire in questback
- Obtain a list of all the 4 237 firms and belonging e-mail addresses
- Provide a list of firms where we could not obtain the belonging e-mail address
- Send out the questionnaire
F ebruary
- Send a reminder to firms that have not yet responded
- Start to structure current available data
- Initiate writing on parts of the thesis which does not require data
March
- Close survey and structure data
- Start hypothesis testing
April ! May
- Start to write results
June
- Finish first draft by June 20th
July
- Finish our thesis by the end of July
MSc Preliminary Thesis Report 15.01.2012
Page 9
Questionnaire
1) Does your firm use derivatives for financial risk management (futures,
swaps, options etc.)?
a. Yes
b. No
2) Please indicate the most important reason for not using derivatives:
a. Inefficient exposure to financial risk.
b. Exposure more effectively managed by other means
c. Derivatives are too complex for our business
d. Accounting matters
e. Concern to investors
f. Cost of managing the derivatives
g. Others, please specify
3) If your firm uses operational hedging, how is the operational hedging done
by your firm? (If you do not use operational hedging, please skip question)
a. Change in price strategy
b. !"#$%&'($')*+,-./0'1(23
c. Adjust to different markets and market segments
d. Order goods in different currencies
e. Change in suppliers
f. Charge customers more in NOK
g. Moving the firm or part of the firm abroad
h. Borrow or buy foreign currency
i. Other, please specify:
4) Approx. how many countries does your firm have subsidiaries in?
a. 0
b. 1-5
c. 6-10
d. 11-15
e. 16-20
f. More than 20
g. 4,$50'6$,7
5) How many subsidiaries of your firm are based abroad?
a. 0
b. 1-5
c. 6-10
d. 11-15
e. 16-20
f. More than 20
g. 4,$50'6$,7
MSc Preliminary Thesis Report 15.01.2012
Page 10
6) What share of your firms! revenue, cost, equity and liabilities are in
foreign currency?
None 25% 50% 75% 100% Not applicable
Revenue
Cost
Equity
Liabilities
7) How is the use of derivatives in your firm compared to before the financial
crisis of 2008?
a. Higher
b. Lower
c. Approx. the same
d. Do"!#$%"&'
8) Do you feel that your firm is financially constrained?
a. Substantially
b. Somewhat
c. A little
d. Not at all
e. (&"!#$%"&'
9) When approaching the following risks, how would you describe the
derivatives strategy when managing these risks? Which of the following
strategies best describes how your firm approaches the use of derivatives
to manage the following risk?
Interest Rate r isk Foreign E xchange r isk Commodity r isk Equity r isk
Exposure not managed
with derivatives
The firm has a formal
predefined strategy
of handling this type of
risk
The firm deals with this
type of risk on a
)*+,-to-*+,-$.+/0/
Other strategy
Not applicable
MSc Preliminary Thesis Report 15.01.2012
Page 11
10) Which of the following risks does your firm use derivatives to hedge?
a. Interest rate risk
b. Exchange-rate risk
c. Commodity risk
d. Equity risk
e. Other, please specify
11) For interest rate risk, what type of contracts does your firm use?
Not Applicable Never used Sometimes Used Regularly used Frequently used
a. Forward/Futures
b. Swaps
c. Options
d. Other, please specify:
12) For exchange-rate risk, what type of contracts does your firm use? Not Applicable Never used Sometimes Used Regularly used Frequently used
a. Forward/Futures
b. Swaps
c. Options
d. Other, please specify:
13) For commodity risk, what type of contract does your firm use? Not Applicable Never used Sometimes Used Regularly used Frequently used
a. Forward/Future
b. Swaps
c. Options
d. Other, please specify
14) How often does your firm review their a hedge? (approx.)
a. Once per day
b. Once per week
c. Once per month
d. Once every 2 months
e. Once every 6 months
f. Once every year
g. Less
h. Depends on the derivative, no formal strategy
i. Not until maturity
j. !"#$%&'#"(
MSc Preliminary Thesis Report 15.01.2012
Page 12
15) What percent of your derivatives have the following maturities? (All
derivatives position). 0% 1-25% 26-50% 51-76% 76-100% Not !"#$%&'#"(
applicable
90 days or less
91 to 180 days
181 days to one year
One to three years
More that three yrs.
16) How often does your firm transact in the interest rate derivatives market
to:
Not Applicable Never Sometimes F requently
Swap from fixed rate to floating rate
Debt
Swap from floating to fixed rate debt
Fix in advance the rate on new debt
Reduce cost or lock-in rates
based on market view
17) Please indicate which of the following contracts your firm has used in the
last year for the following exposures: Foreign exchange risk Interest rate r isk Commodity r isk Other risk
Standard European
Style
Standard American
Style
Average Rate
(price) Options
Basket Options
Barrier Options
Option combinations
!"#$%&'#"(
MSc Preliminary Thesis Report 15.01.2012
Page 13
18) Does your firm have a documented firm policy with respect to derivatives?
a. Yes
b. No
c. Other, please specify
d. !"#$%&'#"(
19) Is speculation with derivatives allowed in your firm? (actively taking
derivatives positions for profit)
a. Yes
b. No, not allowed
c. Other, please specify:
d. !"#$%&'#"(
20) How frequently is derivatives activity reported to the Board of Directors?
a. Never
b. Monthly
c. Quarterly
d. Annually
e. As needed
f. Not applicable
g. Other, please specify
21) How frequently does your firm value your derivatives portfolio?
a. Daily
b. Weekly
c. Monthly
d. Quarterly
e. Annually
f. As needed
g. Other, please specify:
h. !"#$%&'#"(
22) Please provide an estimate for the cost of managing the use of derivatives
within your firm (in NOK per year)
a. Unsure
b. Prefer not to answer
c. 0-1M NOK per year
d. 1M-2,5M NOK per year
e. 2,5M-5M NOK per year
f. 5M-10M NOK per year
g. 10M-25M NOK per year
h. 25M-50M NOK per year
i. More than 50M NOK per year
MSc Preliminary Thesis Report 15.01.2012
Page 14
23) Do you estimate the gain from using derivatives to be larger than the cost?
a. To a large degree, yes
b. To some extent, yes
c. It more or less balances
d. The costs exceed the gain to some extent
e. The cost clearly exceed the gain
f. !"#$%&'#"(
24) What is the most important reason for your firm to use derivatives? (Please
range from most to less important).
a. Reduce volatility in income/cost
b. Reduce volatility in cash flow
c. Reduce risk of financial problems
d. Reduce risk for owners
e. Make budgeting/accounting easier
f. Reduce liquidity risk
g. Other, please specify
h. !"#$%&'#"(
25) Does your CEO and CFO receive performance based compensation?
CEO CFO
a. Yes
b. No
c. Other, please specify
26) What kind of performance based compensation does your CEO and CFO
receive?
CEO CFO
a. Stock options
b. Cash Bonus
c. (Restricted) stock
d. Options
e. Other, please specify
27) What is the composition of compensation?
CEO CFO
a. Salary _____%
b. Cash bonus _____%
c. Stock options ____%
d. (Restricted) stock _____%
e. Options _____%
f. Other (please specify) _____%
g. Other (please specify)_____%