hedge or speculation insper
TRANSCRIPT
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Hedge or Speculation? Evidence of the use of derivatives by
Brazilian firms during the financial crisis
Jos Luiz Rossi Jnior1
Insper Institute of Education and Research
Abstract
This paper analyzes the use of foreign exchange derivatives by non-financial
publicly traded Brazilian companies from 2007 to 2009. Using balance-sheet data onfirms positions in derivatives and their foreign exchange exposure, this study finds thata significant number of companies speculated in the derivatives market. Two types ofspeculators are identified: companies that significantly increased the volume ofderivatives used during this period but used them in line with their currency exposureand companies that adopted positions that would have been inadvisable had the aim
been to hedge their currency exposure. Despite the differences between the two types,
th i i il it b th t i d t bt i i th h th ti f
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th i i il it b th t i d t bt i i th h th ti f
1. Introduction
Beginning in the 1980s, a vast body of theoretical literature on corporatefinance, intended to analyze why companies use derivative instruments, began to
develop. Some of the reasons cited include systems of progressive taxation, bankruptcy
costs, and agency costs. Based on these models, the empirical literature has attempted
to determine why companies use derivatives. The conclusions vary by sector, period,
country, and econometric techniques used in the analysis, thereby making it difficult to
generalize about the real motivations of companies using these financial instruments.
Most of these models assume that the use of derivatives is intended to minimize
firm-level cash flow volatility and that the interaction between imperfections in the
financial markets and this reduction in companies cash flow volatility can generate
gains to the firms that compensated the costs, leading to the use of derivatives to add
value to firms. Thus, the use of derivatives can be considered as hedging and a part of
risk management activities of the firm.
However, the recent global financial crisis shows that it is possible for
companies to use derivatives for reasons other than minimizing the volatility of their
cash flow. In many countries, especially emerging countries such as Brazil, Poland, and
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them for such behavior. In Campbell and Kracaw (1999) and Adam, Dasgupta, and
Titman (2007), speculation is the optimal outcome in equilibrium for firms withfinancial constraints and a profit function that is convex in investment. These authors
argue that factors such as a firms scale of operations, growth opportunities, liquidity,
and financial distress will influence whether it speculates.
Some studies involve attempts to empirically determine firm motivations for
speculation. Beber and Fabbri (2011) used data from a panel of North American non-
financial companies from 1996 to 2001 to show that companies adjust their derivative
positions according to past movements in the exchange rate. This idea is consistent
with the argument that firms select their positions according to their perspective on the
exchange rate trajectory. The authors show that companies led by CEOs who have
MBA degrees, are younger, and have less prior experience tend to speculate more.
They ultimately conclude that their results are consistent with the theory that confident
managers take more risks.
Aabo et al. (2010), using a survey targeted to Danish companies, found that the
involvement of non-financial departments in risk management increases the probability
of speculation by companies. In their paper, the authors suggest that firm size and
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The objective of this study was to analyze the factors that lead companies to
speculate in the currency derivatives market using data from publicly traded Braziliancompanies from 2007 to 2009. This study is innovative in several ways. First, this
study focuses on a different economic environment than previous studies focusing on
developed countries. Firms in emerging countries face a larger foreign exchange
exposure and more volatile exchange rates than do developed countries, which make
risk management activities more important for these companies.
Unlike other studies, this study has identified companies as speculators using
data from firms yearly balance sheets indicating their use of derivatives and foreign
exchange exposure. After the global financial crisis, the Brazilian legislature demanded
greater transparency. Not only must the value and position of all derivatives used by a
company be declared, but the degree of exposure must also be accurately reported. The
use of such data gives this study an advantage over previous ones, which identified
companies as speculators either through surveys (Geczy et al. (2007), Aabo et al.
(2010)) or through indirect proxies for speculation (Beber and Fabbri (2011)).2
The results show that a significant number of companies speculated in the
derivatives market and that this number varied in the established period. In 2008, out of
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determine their expectations regarding future movements and then they take positions in
the foreign exchange market based on their view of the exchange rate trajectory.The study shows that companies that allegedly have some type of informational
advantage in the foreign exchange market exporters and companies with foreign
currency denominated debt are more likely to speculate. No other theory on why
companies speculate is able to explain their behavior.
This study is divided as follows. Section 2 presents the data used and the
methodology proposed for classifying the companies as speculators or hedgers. Section
3 presents the econometric analysis. The last section presents the conclusion.
2. Data and Methodology for Classification
Two data sources were used in this research: Bloomberg and yearly firm balance
sheets. Bloomberg provides stock market data and accounting data for all Brazilian
publicly traded non-financial companies. The data on firms use of derivatives and
accounting exchange rate exposure were collected directly from their yearly balance
sheets. Information on derivatives and foreign-currency-denominated debt is available
in the explanatory notes on firms yearly balance sheets. The total amount of foreign-
currency-denominated debt is located underloans and financing, and the information
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According to the legislation, the explanatory notes on the use of financial
instruments must enable users to evaluate their relevance for the firm s financialposition and overall results. This statement is especially true for derivative financial
instruments. Businesses are required to provide tables that display the quantitative
information on the use of derivatives and the risks associated with each instrument.
Also based on statement 475/08, companies must now provide a sensitivity
analysis chart for each type of market risk deemed relevant by the administration, with
data for the financial instruments to which the entity is exposed, including all derivative
financial instruments. This chart must identify the types of risk that can result in
material losses for the company, including operations with derivative financial
instruments; identify the methods and assumptions used in preparing the sensitivity
analysis; define the most likely scenario in assessing the management (in addition totwo scenarios that, if they occurred, would yield in adverse results for the company);
and estimate the impact of those scenarios on the fair value of the financial instruments
operated by the company.
For the operations with derivative financial instruments, the company must
di l th bj t (th l t b i t t d) d th d i ti fi i l i t t
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a reduction in both the number of firms that use currency derivatives and the total
(notional) amount used by the firms.
The data presented in table 1 indicate a difference between international trends
and the Brazilian case. Among Brazilian firms, swaps are the most widely used
derivative because the devaluation of the domestic currency is seen as a risk for firms
that therefore hedge themselves through swaps.5 (Swaps are the most appropriate
derivative when firm exposure takes place over a longer, predetermined period, as when
companies have foreign-currency-denominated debt.6) An econometric analysis, to be
presented later, confirmed this motivation for the use of derivatives by Brazilian
companies.
Table 1 also shows the net position of firms in the derivatives market. This value
is calculated using the difference between firm long and short positions in US$ in the
various types of derivatives. Negative values indicate a short position in US$, whereas
positive values indicate the opposite. Again, a pattern has emerged from the analysis.
Between 2007 and 2008, there was an increase in the net short positions of Brazilian
firms in US$. The ratio between the net position of firms and their total assets rose from
2.34% in 2007 to 3.20% in 2008. In addition, the number of firms with net short
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semester, reaching a value of 2.37 R$/US$ in February 2009. As the crisis cooled, it
started to increase in value, reaching its pre-crisis rate only in 2011.
In an environment marked by the continuous appreciation of the domestic
currency (as shown in figure 1) and the strong performance of the Central Bank of
Brazil in buying international reserves7, companies would have been able to take
positions in the derivatives market that would have allowed them to profit from the
appreciation process by predicting that it would continue. Stulz (1996) and Geczy et al.
(2007) make a similar suggestion. The onset of the financial crisis in 2008, which was
an exogenous external shock, corresponded to a reversal in the trajectory of exchange
rates that led companies to reassess their positions in the derivatives market.
2.1 Identification of speculation
Distinguishing between firms that use derivatives for speculative purposes and
those that use them exclusively for hedging is the first step in this analysis of the
motivations of companies to speculate.
Ideally, the speculation by firms should be identified using an optimal hedging
model. Deviations from the optimal hedge ratio may be seen as indication that
companies would be speculating in the derivatives market. Beber and Fabbri (2011)
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their classification of speculation on surveys8, posing the following questions to
companies: How often does your view on exchange rates lead you to 1) change the
timing of hedging; 2) change the volume of hedging; 3) actively take a position in the
derivatives market.
Stulz (1996) uses the term "selective hedging" to refer to the strategies of
managers who incorporate their market views into their hedging policy. The first two
questions thus consider this form of speculation. Geczy et al. (2007) employ a more
restricted view of speculation. The authors consider firms as speculators if they
respond positively to the last question, arguing that this type of speculation is the type
that should be of most concern to regulators. In contrast, Aabo et al. (2010) consider all
questions as proxies for speculation.
The use of surveys for this purpose has potential drawbacks, such as selection
bias and low response rates, among others. Furthermore, these studies cannot clearly
indicate the position of companies in the foreign exchange market because they do not
consider the volume of derivatives; they analyze the intentions but not the real position
of the companies in the derivatives market.
Therefore, this study tries to identify a company as speculator directly based on
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exchange rate exposure. Essentially, net exporters (with positive exchange rate
exposure) that hold long positions in dollars and net importers (with negative exchange
rate exposure) that hold short positions in dollars. Furthermore, companies without
foreign exchange exposure that take positions in the derivatives market are also
considered speculators (SPEC1).
A second group of firms that speculate is identified if these companies take
positions in line with their foreign exchange exposure during one year but significantly
increase their exposure in the derivatives market relative to that of the previous year
without a proportional increase in their foreign exchange exposure in the same period.
This definition is more consistent with the definition of selective hedging provided by
Stulz (1996). (SPEC2)
Analyzing firms this way requires researchers to determine an ad-hoc value for
changes considered speculative. The study initially considered a change over 30% in the
total net notional amount to be indicative of speculation.9 Companies that initiated the
use of derivatives but did not continuously use them in subsequent years are also
considered speculators. We performed several exercises to verify the robustness of this
definition.
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Informational advantages in the foreign exchange market can be important in
getting firms to speculate. Stulz (1996) argues that speculation can occur when a
company believes that it enjoys a comparative informational advantage over the rest of
the market and thus is in a position to obtain gains. Empirically, Geczy et al. (2007),
Aabo et al. (2010), and Beber and Fabbri (2011) confirmed this hypothesis, establishing
a relationship between the international orientation of a company and its probability of
speculating on the foreign exchange market. We then use the ratio between foreign sales
and total sales (Foreign Sales), the ratio between foreign-currency-denominated debt
and total debt (Foreign Debt) and a dummy variable if the company had overseas
subsidiaries (Foreign Operations) to test this hypothesis.
Stulz (1996) discusses the possibility that there is a relationship between
speculation and financial distress. According to the author, companies with low
bankruptcy risk should be more likely to speculate because it will be easier for them to
absorb the negative outcomes that may result from speculation. The author also suggests
that the principal-agent relationship may lead managers of companies in distress to be
more likely to speculate because this action will benefit shareholders, whereas risk
management will only reduce the likelihood of good outcomes that improve the
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internal control systems specific to the use of derivatives can limit potential abuses. Lel
(2009) analyzed the impact of internal and external corporate governance structures on
the use of derivatives in companies from several countries exposed to foreign exchange
risk. The results of the study suggest that companies with strong governance use
derivatives to mitigate their exposure to changes in exchange rates, whereas companies
with weak governance tend to use derivatives in a manner that risks harming the
company. In a related study, Allayannis et al. (2009) used a sample composed of
companies from several countries to demonstrate that risk management policies add
value to firms with strong governance regimes. Thus, in this study, a proxy variable was
used for firm governance levels. The So Paulo stock exchange groups firms according
to different governance levels, from lowest to highest: new market, level 1, level 2,
traditional, and organized counter. The study then uses this classification system to
analyze the relationship between governance and speculation.
Finally, Beber and Fabbri (2011) show that past movement in the foreign
exchange rate is an important factor in companies decisions to speculate. Thus, this
study also used time dummies to analyze the likelihood that macroeconomic factors
common to all companies would affect their decision to speculate.
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dollars. This evidence is consistent with the fact that swaps are the derivative most
widely used by Brazilian companies, which have used it as a form of hedging their
foreign exchange-denominated liabilities.
On average for the period, the speculators exhibit positive foreign exchange
exposure and net short positions in US$. That is, they are net exporters that bet on the
appreciation of the domestic currency, hoping to obtain gains via their positions.
Interestingly, this market view is common to the two types of speculators. The
companies classified as speculators because they have taken positions that are
inconsistent with their exposure (SPEC1) show negative figures for their average
foreign exchange exposure (net importers) and hold short positions in dollars, with a net
position in derivatives similar to that of companies classified according to the second
classification (SPEC2) but with positive foreign exchange rate exposure (net exporters).
Similarly, in an analysis resembling this study but that only considered the first
type of speculators, Oliveira and Novaes (2007) discovered that companies with
positive foreign exchange rate exposure (net exporters) were long in dollars in 2002:
they were betting on the depreciation of the domestic currency. The authors argued that
this phenomenon happened because of the extraordinary volatility of the domestic
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The data in table 3 show that companies that use derivatives are less risky than
those that do not because they have less volatile returns than do non-users and users
present better governance than non-user.
The data in table 3 show the differences between the companies that use
derivatives for speculative purposes and those that use it for hedging. Considering the
whole period, the results indicate that speculators are smaller than hedgers. This finding
may indicate that financial restrictions may play a role in firm decision to speculate. As
discussed by Stulz (1996), companies that are believed to have an informational
advantage in the exchange market should tend to speculate more. Table 3 confirms this
theory; speculators exhibit a greater fraction of foreign-currency-denominated revenue
and debt and finally speculators present more volatile returns, indicating these firms are
riskier than hedgers but this result is not robust for 2009. In 2008, the results also
indicate that companies classified as speculators are more liquid than those that use
derivatives for hedging, but this fact is not robust for the whole period.
The data presented in table 3 confirm the differences between the two types of
companies classified as speculators. The companies that took an active position in the
derivatives market (SPEC1) have a higher proportion of their debt denominated in
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Interestingly, the sign of the dummy for 2008 is positive and significant,
implying that macroeconomic factors played a role in the use of derivatives by
companies. Some sectoral dummies (not shown) also had a statistically significant
impact in the use of derivatives by the companies.
The results presented in table 4 show that in the period under analysis, only the
proxy variables for company size and the ratio of foreign-currency-denominated debt to
total debt were robust to the likelihood that a company would be classified as a hedger.
This finding indicates that when Brazilian companies use derivatives as a hedge
instrument, they use them to protect their liabilities from exchange rate fluctuations. In
turn, these results confirm why swaps are the most widely used derivative, as also found
by Rossi (2007). Although they are only significant for 2008, the results shown in table
4 show a negative relationship between a companys use of derivatives for protection
and its revenue in a foreign currency, indicating that the exporters paid close attention to
market timing in the derivatives market in 2008. There is also(weak) evidence that
growth opportunities are important in the likelihood of a firm being a hedger.
Table 5 clearly indicates why companies speculated in the derivatives market.
Stulz (1996) argues that companies can speculate in the derivatives market if they
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In short, in the case of Brazil, continuous domestic currency appreciation made
companies take speculative positions in relation to the future trajectory of the exchange
rate, probably because they believed that they had superior knowledge of the evolution
of the exchange rate due to their international integration. As table 5 illustrates, the
results for all other possible reasons for the companies to speculate are statistically
insignificant and are not robust.11
3.1 Robustness
The estimations shown in tables 4 and 5 were performed using all of the
companies present in the sample. Usually, the analyses are performed only with
companies that have some type of exchange rate exposure. In the Brazilian context, this
separation is more difficult because even if the company does not have some form of
foreign currency revenue or debt, it may have foreign competitors or contracts adjusted
by the dollar or using type of price index highly correlated with the dollar.12 Therefore,
it was necessary to perform the analysis with all publicly traded companies. The results
presented in the first part of table 6 consider only companies with assets and liabilities
that were in some way exposed to exchange rate movements, therefore companies
without foreign revenues, debt or subsidiaries were excluded. The results shown in
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use derivatives in the period under study, smaller companies were more likely to
speculate. These results are consistent with those of Adam, Fernando, and Salas (2007),
who considered such findings an indication of a relationship between financial
restrictions and speculation.
Finally, in this study, it was necessary to analyze the robustness of the
definition of speculation used here. A change in the volume of derivatives was
considered the definition of the second type of speculator. The results (not shown) of
an analysis using several levels of such change indicate no significant changes in the
main results given variation in derivatives volume between 20 and 50%. Therefore, it
was concluded that the results were robust to the variation involved in the study.
Following Beber and Fabbri (2011), a two steps procedure can be used to
identify the speculation by the firms. Initially, the ratio of the total notional amount of
derivatives to total assets should be regressed against the variables that can explain why
companies use derivatives for hedging. Deviations are considered evidence that
companies change their position in derivatives based on factors other than hedging.
Companies with more volatile deviations are more likely to be speculating in the
foreign exchange market. The last two columns of table 6 use this methodology. The
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addition, the disclosure rules established by regulatory agents enable to obtain not only
the total (notional) amount of derivatives used by a particular company but also the net
position of the company in the foreign exchange derivatives market and the accounting
exposure of the company to exchange rate fluctuations. Therefore, unlike other studies,
this study distinguishes between companies that use derivatives for speculative
purposes and hedging purposes, using data from their annual balance sheets to evaluate
time-based changes in their position in the derivatives market and their exchange
exposure.
The results show that a considerable number of companies speculated in the
derivatives market in the period under analysis. In 2008, approximately 38.7% of
companies that used derivatives were classified as speculators. Furthermore, the study
confirms that in 2009, the proportion of speculative companies among those that used
derivatives fell to 21.0%.
The analysis of the net position of companies in currency derivatives and their
foreign exchange exposure over time made it possible to identify two types of
speculators: companies that significantly increased the volume of derivatives that they
used in this period but that used derivatives proportional with their exchange exposure
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Why companies believe that they can obtain gains by speculating in the
derivatives market is still an open question. Even the most internationalized companies
do not generally have sufficient expertise regarding the market to achieve significant
gains. This generalization is even truer in the foreign exchange rate market; even the
literature that tries to predict its movements indicates that no model is good enough in
all periods to predict the exchange rate. Whether for behavioral reasons on the part of
managers as suggested by Beber and Fabbri (2011) or because of implicit government
or Central Bank guarantees to firms, some reason might encourage managers to think
that they can obtain real gains by speculating. None of the existent theoretical models
show to be useful to explain companies behavior and it seems to be a fruitful way for
future research in the field.
References
Aabo, T., Hansen, M., and Pantzalis, T. Who pulls the trigger? Evidence on Corporate
Currency Speculation. Aarhus School of Business, 2010.
Adam, T., Dasgupta, S. and Titman, S. Financial Constraints, Competition, andhedging in Industry Equilibrium.Journal of Finance 62, 2445-2473, 2007.
Ad T d F d C H d i S l i d Sh h ld V l J l f
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Brown, G.W., Crabb, P. and Haushalter, D. Are Firms Successful at Selective
Hedging?Journal of Business 79, 29252949, 2006.
Burnside, C., Eichenbaum, M. and Rebelo, S. Hedging and Financial Fragility in Fixedexchange Rate Regimes.European Economic Review 45, 1151-1193, 2001.
Campbell, T. and Kracaw, W. Optimal Speculation in the Presence of Costly External
Financing. In Corporate Risk: Strategies and Management, G. Brown and D. Chew,
editors, Risk Publications, London, 1999.
Dolde, W. The Trajectory of Corporate Financial Risk Management. Journal of
Applied Corporate Finance 6, 33-41, 1993.
Froot, K., Scharfstein, D., and Stein, J. Risk management, coordinating investmentand financing policies.Journal of Finance 48, 1629-1658, 1993.
Geczy, C., Minton, B. and Schrand, C. Why firms use currency derivatives. Journalof Finance 52, 1323-1354, 1996.
Geczy, C., Minton, B. and Schrand, C. Taking a view: Corporate speculation,governance and compensation.Journal of Finance 62, 2405-2443, 2007.
Lel, U. Currency hedging and corporate governance: a cross-country analysis.Indiana University Working PaperNo. 858, 2009.
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Figure 1Trajectory of Exchange Rate R$ / US$Figure 1 shows the trajectory of the exchange rate of R$ / US$ from January 2004 to September 2011. Source: Central Bank of Brazil.
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Table 1Summary Statistics of the Use of Derivatives by the CompaniesTable 1 shows a summary by year of the use of derivatives by the companies. Notational / total assets is the ratio between the total notational value of derivatives and the bookvalue of assets of the company. Notational / external sales is the ratio between the total notational value of derivatives and the total value of revenue in foreign currency.Notational/ Foreign Currency Debt is the ratio between the total notational value of derivatives and the total value of the debt denominated in foreign currency. Net Position/Total Assets represents the ratio between the net total value of derivatives and the book value of assets. The net position is calculated from the difference between the total
notational amount of long and short positions in US$. Long means the total number of companies with long positions in US$, and Short represents the total number ofcompanies with short positions.
2007 2008 2009
Swap 57 63 51
NDF, Forward and Options 34 55 43
Both 14 20 16
None 123 102 122
Notational / Total Assets (all firms) 4.39% 6.19% 3.44%
Notational / Total Assets (Only Derivative Users) 11.4% 12.6% 8.73%
Notational / External Sales 53.0% 61.4% 60.9%
Notational / Foreign Currency Debt 47.7% 92.5% 78.5%
Net Position / Total Assets -2.34% -3.20% 0.24%Long 54 54 50
Short 23 44 26
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Table 2Reasons for Speculation and Company CharacteristicsTable 2 shows summary statistics for the main variables used in the study and the correlation between the different variables. Size is the log of the book value of the totalassets of the company (R$ millions). Foreign Sales represents the ratio of foreign currency sales over total sales. Foreign Debt represents the ratio of debt denominated inforeign currency over total debt. Growth is the ratio of market value of assets over the book value of assets. Debt Ratio represents the ratio between the book value of long-term debt and the total assets. Quick Ratio is the ratio between the current assets and the current liabilities. Foreign Operations is a dummy that takes the value of 1 if the
company has overseas subsidiaries, and Governance is a proxy variable for corporate governance, constructed according to the levels of governance adopted by the So PauloStock Exchange (BOVESPA). Volatility Stock Returns represents the ratio between the daily volatility of returns of the company and the volatility of the market index(Ibovespa). The statistics are calculated for all companies (N=200) from 2007 and 2009.
SizeForeign
SalesForeign
DebtForeign
OperationsGrowth Quick Debt Ratio Governance
VolatilityStock Returns
Mean 13.92 10.7% 11.6% 0.148 1.19 1.63 25.7% 1.95 2.33
Standard Deviation 1.98 19.7% 16.3% 0.365 1.04 1.48 20.6% 1.28 1.99
Size 1.00
Foreign Sales 0.18 1.00
Foreign Debt 0.30 0.40 1.00
Foreign Operations 0.18 0.22 0.11 1.00
Growth -0.13 0.06 -0.03 0.00 1.00
Quick -0.01 0.07 0.03 0.01 -0.03 1.00
Debt Ratio 0.42 0.13 0.36 0.07 0.02 0.02 1.00
Governance 0.36 0.10 0.16 0.19 0.09 0.12 0.27 1.00
Volatility Stock Returns -0.37 -0.08 -0.10 -0.13 0.05 -0.04 -0.20 -0.31 1.00
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Table 3 - Company Profiles
Table 3 shows the different profiles of the companies. The column User is a comparison between companies that use derivatives and those that do not. Furthermore, table 3 compares thecompanies classified as hedgers and speculators and the two types of speculative companies (SPEC1 and SPEC2). Net Exposure represents the net exchange rate exposure of companies; itscalculation is in the text. Net Derivative Position is the difference between the notational value of long and short positions in US$ of derivatives of the company. Size is the log of the bookvalue of the total assets of the companies (R$ millions). Foreign Sales represents the ratio of external sales over total sales. Foreign Debt represents the ratio of debt in foreign currency overtotal debt. Growth is the ratio of market value of assets over the book value of assets. Debt Ratio represents the ratio between the book value of long-term debt and the total assets. Quick Ratiois the ratio between the current assets and the current liabilities. Foreign Operations is a dummy that takes the value of 1 if the company has overseas subsidiaries and Governance is a proxyvariable for corporate governance, constructed according to the levels of governance adopted by the So Paulo Stock Exchange (BOVESPA). Volatility Stock Returns represents the ratio
between the daily volatility of returns of the company and the volatility of the market index (Ibovespa). *, ** indicates statistically significant differences at 5% and 10%, respectively.
2008 -2009 2008 2009
User Hedgers Specul. SPEC1 SPEC2 User Hedgers Specul. SPEC1 SPEC2 User Hedgers Specul. SPEC1 SPEC2
Number ofFirms
174 120 54 27 27 98 60 38 16 22 76 60 16 11 5
Net Exposure
(US$ million)-189.6 -361.4 +36.8 -400.5 +326.7 -189.1 -351.7 +67.69 -373.2 +388.3 -353.0 -371.3 -85.3 -440.2 +55.6
Net Derivative
Position
(US$ million)
+137.6 +257.7 -131.1 -208.5 -103.7 +82.6 +227.9 -146.8 -197.9 -109.7 +207.2 +287.5 -93.7 -223.8 -192.7
Size 15.0* 15.26* 14.52 14.48 14.56 14.9* 15.32* 14.26 14.22 14.32 15.2* 15.20 15.13 14.97 15.48
Foreign Sales 0.166* 0.098 0.316* 0.252 0.380* 0.172* 0.082 0.315* 0.213 0.389* 0.157* 0.115 0.317* 0.308 0.337
Foreign Debt 0.207* 0.162 0.305* 0.400* 0.210 0.228* 0.180 0.304* 0.422* 0.218 0.179* 0.144 0.309* 0.369* 0.178
Growth 1.02 1.06 0.926 1.08** 0.76 0.846 0.871 0.808 0.775 0.852 1.25 1.26 1.20 1.42* 0.708
Debt Ratio 0.332* 0.329 0.339 0.381** 0.297 0.337* 0.339 0.333 0.411* 0.276 0.326* 0.319 0.353 0.388 0.307
Quick Ratio 1.65 1.61 1.74 1.61 1.88 1.61 1.48 1.81** 1.62 1.94 1.71 1.74 1.59 1.59 1.60
Foreign
Operations 0.235* 0.250 0.203 0.074 0.333* 0.234* 0.250 0.211 0.125 0.272 0.236* 0.250 0.187 0.00 0.60*
Governance 2.33* 2.34 2.30 2.51 2.07 2.34* 2.42 2.21 2.43 2.04 2.32* 2.26 2.50 2.63 2.20
Volatility Stock
Returns1.73* 1.61 2.03** 2.14 1.92 1.62* 1.40 1.97* 2.11 1.87 1.88* 1.81 2.15 2.18 2.08
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Table 4 - Determinants of the Use of Derivatives and of Use of Derivatives for Protection
Table 4 shows the results of the regressions for the determination of reasons that lead companies to use derivatives and use them for hedging. All regressions are performed using a Logitmodel. For the regressions for derivatives users (User), the dependent variable takes a value of 1 if the company has used derivatives and 0 if it has not. For the hedger regressions, thedependent variable takes on a value of 1 is the company is classified as a hedger and 0 if it is not. Size is the log of the book value of total assets of the companies (R$ millions). Foreign Salesrepresents the ratio of external sales over total sales. Foreign Debt represents the ratio of debt in foreign currency over total debt. Growth is the ratio of market value of assets over the bookvalue of assets. Debt Ratio represents the ratio between the book value of long-term debt and the total assets. Quick Ratio is the ratio between the current assets and the current liabilities.Foreign Operations is a dummy that takes the value of 1 if the company has overseas subsidiaries, and Governance is a proxy variable for corporate governance, constructed according to thelevels of governance adopted by the So Paulo Stock Exchange (BOVESPA). Time and Sectoral dummies are added to some regressions as indicated. Robust standard deviations are indicated
between parentheses. *, ** indicates statistically significant differences at 5% and 10%, respectively. Panel is a Logit panel regression with random effects. Columns 2008 and 2009 only usedata from these respective years.
User Hedger
Logit Panel 2008 2009 Logit Panel 2008 2009
Size0.761
(0.130)*2.21
(0.49)*0.679
(0.245)*0.772
(0.186)*0.644
(0.140)*1.35
(0.47)*0.798
(0.229)*0.596
(0.178)*
Foreign Sales1.89
(1.02)**3.30
(1.16)*3.65
(1.53)*1.61
(0.84)*-1.38(1.20)
-3.88(2.61)
-3.26(1.86)**
-0.251(1.64)
Foreign Debt6.56
(1.04)*12.4
(2.82)*6.83
(1.92)*7.37
(1.94)*2.65
(1.06)*5.33
(2.51)*1.67
(0.47)*3.81
(1.62)*
Growth0.250
(0.104)*0.589
(0.302)**0.250
(0.278)0.266
(0.154)**0.299
(0.134)*0.491
(0.389)0.523
(0.282)**0.237
(0.150)
Debt Ratio-0.053(0.636)
-0.136(1.93)
0.537(1.09)
-0.734(1.24)
-0.425(0.775)
-0.712(1.78)
-0.526(1.21)
-0.346(1.08)
Quick Ratio-0.098(0.097)
-0.441(0.370)
-0.065(0.132)
-0.029(0.138)
0.042(0.067)
0.052(0.242)
0.098(1.32)
0.051(0.081)
Foreign Operations0.440
(0.360)0.976(1.38)
0.443(0.689)
0.356(0.642)
0.813(0.476)**
1.58(1.11)
0.883(0.694)
0.686(0.625)
Governance0.129
(0.103)0.383
(0.372)0.252
(0.197)-0.035(0.171)
0.061(0.115)
0.107(0.303)
0.189(0.179)
-0.041(0.163)
Stock Returns Volatility-0.045(0.060)
-0.262(0.222)
-0.075(0.101)
0.029(0.116)
-0.091(0.101)
-0.126(2.31)
-0.243(0.145)**
-0.025(0.128)
20080.733
(0.279)*
2.04
(0.268)*
0.056
(0.275)
0.038
(0.450)
20090.112
(0.276)0.179
(0.507)
Sectoral Dummies Yes Yes Yes Yes Yes Yes Yes Yes
N 600 600 200 200 400 400 200 200
R2 0.388 0.405 0.359 0.2768 0.338
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Table 5 - Determinants of Speculation
Table 5 shows the result of regressions for the determination of the reasons that lead companies to speculate with derivatives. All regressions are performed using a Logit model. For theregressions for all of the companies classified as speculators (Speculation), the dependent variable takes on the value of 1 if the company has been thus classified and 0 if it has not. For theregressions with the types of speculation (SPEC1 and SPEC2), the dependent variable takes on the value of 1 if the company was classified as their respective classification and 0 if not. Size isthe log of the book value of total assets of the companies (R$ millions). Foreign Sales represents the ratio of external sales over total sales. Foreign Debt represents the ratio of debt in foreigncurrency over total debt. Growth is the ratio of market value of assets over the book value of assets. Debt Ratio represents the ratio between the book value of long-term debt and the totalassets. Quick Ratio is the ratio between the current assets and the current liabilities. Foreign Operations is a dummy that takes the value of 1 if the company has overseas subsidiaries, andGovernance is a proxy variable for corporate governance, constructed according to the levels of governance adopted by the So Paulo Stock Exchange (BOVESPA). Volatility Stock Returns
represents the ratio between the daily volatility of returns of the company and the volatility of the market index (Ibovespa). Robust standard deviations are indicated between parentheses. *, **indicates statistically significant differences at 5% and 10%, respectively. Panel is a Logit panel regression with random effects. Columns 2008 and 2009 only use data from these respectiveyears.
SpeculationType of Speculation
SPEC1 SPEC2
Logit Panel 2008 2009 Logit Panel 2008 2009 Logit Panel 2008 2009
Size0.141
( 0.137)0.019
(0.176)-0.043(0.221)
0.299(0.145)*
0.154(0.215)
0.263(0.444)
-0.088(0.304)
0.846(0.316)*
0.158(0.131)
0.158(0.145)
0.021(0.203)
0.388(0.278)
Foreign Sales1.88
(0.89)*2.78
(1.43)**2.73
(1.27)*0.992
(0.49)*-1.72(1.34)
-4.55(3.90)
-2.91(2.03)
-1.57(2.40)
4.21(1.08)*
4.21(1.19)*
4.97(1.46)*
5.26(2.81)**
Foreign Debt4.90
(1.12)*6.10
(1.85)*4.53
(1.41)*6.27
(1.89)*6.49
(1.41)*12.95
(5.45)*5.51
(1.53)*11.57
(2.82)*0.285(1.14)
0.284(1.39)
1.14(1.18)
2.41(4.26)
Growth-0.147(0.343)
-0.317(0.318)
-0.495(0.465)
0.016(0.480)
0.244(0.314)
0.548(0.539)
-0.578(0.803)
0.688(0.492)
-0.374(0.271)
-0.374(0.337)
-0.496(0.441)
-0.486(0.481)
Debt Ratio0.475(1.14)
0.502(1.37)
1.06(1.40)
-0.933(2.58)
0.111(1.77)
-0.512(3.01)
2.92(2.15)
-6.17(6.37)
0.671(0.990)
0.670(1.23)
-0.496(1.24)
0.455(0.451)
Quick Ratio-0.149(0.145)
-0.225(0.220)
-0.0808(0.168)
-0.376(0.280)
-0.231(0.257)
-0.365(0.587)
-0.332(0.471)
-0.542(0.382)
0.021(0.102)
0.021(0.141)
0.103(0.150)
-0.560(0.432)
Foreign Operations-0.676(0.579)
-0.829(0.736)
-0.706(0.837)
-0.470(0.808)
-0.686(1.02)
-0.845(1.96)
0.110(0.915)
0.340(0.358)
-0.190(0.642)
-0.190(0.584)
-0.357(0.892)
-0.387(1.08)
Governance0.114
(0.194)0.215
(0.219)0.153
(0.277)0.172
(0.329)0.205
(0.284)0.555
(0.549)0.158
(0.430)0.371
(0.604)-0.208(0.199)
-0.208(0.198)
-0.124(0.242)
-0.378(0.521)
Stock Returns Volatility0.037
(0.091)
-0.0109
(0.149)
0.045
(0.114)
0.072
(0.198)
0.095
(0.129)
0.319
(0.356)
0.031
(0.218)
0.149
(0.312)
-0.022
(0.112)
-0.022
(0.134)
-0.038
(0.134)
0.026
(0.174)
20081.05
(0.405)*1.43
(0.55)*0.116
(0.478)0.565
(0.826)1.27
(0.488)*1.26
(0.469)*
Sectoral Dummies Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
N 400 400 200 200 400 400 200 200 400 400 200 2000
Pseudo-R2 0.3872 0.439 0.326 0.395 0.395 0.351 0.272 0.295 0.336
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Table 6 - Robustness Exercises
Table 6 shows the results of some robustness exercises. In (1), similar regressions to those presented in tables 4 and 5 are conducted, but only using the companies with exchange rate exposurepresent in the sample. In (2), the regressions are performed only in c ompanies present in the sample that use derivatives. In (3), a similar method to Beber and Fabbri (2011) is used to identifyfirms that speculate. In the first step, the determinants of derivatives usage are analyzed. The independent variable is the ratio of total notational amount of derivatives divided by the total bookvalue of assets. The volatility of regression residues is used as proxy for speculation. Size is the log of the book value of total assets of the companies (R$ millions). Foreign Sales representsthe ratio of external sales over total sales. Foreign Debt represents the ratio of debt in foreign currency over total debt. Growth is the ratio of market value of assets over the book value ofassets. Debt Ratio represents the ratio between the book value of long-term debt and the total assets. Quick Ratio is the ratio between the current assets and the current liabilities. ForeignOperations is a dummy that takes the value of 1 if the company has overseas subsidiaries, and Governance is a proxy variable for corporate governance, constructed according to the levels of
governance adopted by the So Paulo Stock Exchange (BOVESPA). Volatility Stock Returns represents the ratio between the daily volatility of returns of the company and the volatility of themarket index (Ibovespa). Time and Sectoral dummies are added to some regressions as indicated. Robust standard deviations are indicated between parentheses. *, ** indicates statisticallysignificant differences at 5% and 10%, respectively.
(1) (2) (3)
User Hedger Speculation Spec 1 Spec 2 Speculation Spec1 Spec2 First Speculation
Size0.517
(0.138)*0.482
(0.141)*0.139
(0.160)0.144
(0.228)0.145
(0.140)-1.07
(0.335)*-0.196(0.256)
-0.239(0.165)
0.030(0.008)*
0.0010(0.0024)
Foreign Sales1.40
(0.80)**-1.44
(0.90)**1.59
(0.94)**-2.23(1.48)
3.91(1.05)*
4.98(2.13)*
-3.11(1.76)**
5.20(1.18)*
0.120(0.063)**
0.0066(0.0023)*
Foreign Debt4.44
(0.97)*0.675
(0.273)*4.63
(1.15)*6.89
(1.53)*-0.018(1.12)
4.67(1.74)*
5.53(1.36)*
-3.61(1.78)*
0.497(0.064)*
0.084(0.025)*
Growth0.236
(0.141)**0.754
(0.287)*-0.444(0.321)
0.030(0.410)
-0.375(0.291)
0.084(0.483)
0.627(0.429)
-0.449(0.417)
0.033(0.012)*
0.011(0.0083)
Debt Ratio0.208
(0.780)-0.311(0.945)
0.408(1.08)
0.272(1.63)
0.515(1.06)
-1.13(2.42)
0.719(1.97)
-0.200(1.38)
-0.055(0.050)
-0.035(0.026)
Quick Ratio0.029
(0.121)0.329
(0.179)**-0.147(0.181)
-0.257(0.324)
0.091(0.152)
0.300(0.259)
-0.212(0.379)
0.203(0.194)
-0.015(0.0084)**
-0.0007(0.0017)
Foreign Operations0.445
(0.382)1.10
(0.54)*-0.680(0.615)
-0.419(1.00)
-0.104(0.693)
0.344(0.933)
-0.047(1.18)
0.119(0.643)
-0.037(0.027)
-0.016(0.011)
Governance0.018
(0.120)-0.051(0.144)
0.015(0.212)
0.037(0.260)
-0.233(0.210)
-0.186(0.275)
0.029(0.306)
-0.315(0.189)**
0.025(0.0080)*
0.0036(0.0045)
Stock Returns Volatility-0.072(0.066)
-0.082(0.098)
0.016(0.095)
0.043(0.144)
0.017(0.092)
0.505(0.354)
0.271(0.134)*
0.042(0.137)
-0.0011(0.0055)
0.0023(0.0018)
2008 0.820(0.308)*
-0.154(0.255)
1.08(0.430)*
0.041(0.530)
1.23(0.480)*
0.847(0.598)
-0.312(0.647)
1.02(0.60)**
0.029(0.011)*
0.0065(0.0084)
20090.151
(0.291)0.0013(0.012)
0.0044(0.0095)
Sectoral Dummies Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
N 425 282 282 282 282 174 174 174 600 600
R2 0.285 0.288 0.365 0.395 0.234 0.479 0.384 0.252 0.770 0.085