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Corporate Hedging and Speculation with Derivatives

Abstract

Using a unique data set on global derivatives usage, this paper presents international evidence onthe question of whether firms use derivatives for hedging or speculative purposes. Based on asample of 6,896 nonfinancial firms from 47 countries including the United States, the resultsstrongly suggest hedging motives of corporate derivatives use. In particular, users of derivativeshave higher gross or pre-hedging exposures to exchange rate risk (due to more foreign sales, for-

eign income and foreign assets) and interest rate risk (due to higher leverage and lower quick rati-os). They are also more likely to belong to commodity-based industries. Moreover, derivativesusers show significantly lower stock return volatilities compared to non-users, and firms that usederivatives have significantly lower net or post-hedging foreign exchange rate, interest rate andcommodity price exposures. Firms use derivatives for hedging purposes independent of access toderivatives or the strength of internal and external corporate governance. Nevertheless, the reduc-tion in risk and exposure is larger for firms in countries where derivatives are readily available.Moreover, derivatives users have bigger decreases in exposure if shareholder rights are strong andthe legal system is effective, which is in line with small speculative components of hedging.

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K d D i ti i k t h d i l ti t fi i t ti l

"We view them as time bombs both for the parties that deal in them and the economic system ...

Derivatives are financial weapons of mass destruction, carrying dangers that, while now latent, are

potentially lethal."

Warren Buffet, Letter to Shareholders, 2002,

Berkshire Hathaway Annual Report

1 Introduction

Today, most large nonfinancial corporations use financial derivatives. While derivatives can be effec-

tive and efficient tools for financial risk management, they are equally well suited for speculative pur-

poses, possibly even under the guise of hedging. In surveys, firms even admit to speculative uses of

derivatives. For example, two out of three firms alter the size or the timing of a hedge depending on

their market view on exchange rates or interest rates (Bodnar, Marston and Hayt, 1998).1 From a

shareholder perspective, it is important to know for what purpose nonfinancial firms employ deriva-

tives, as it may decrease (in the case of hedging) or increase (in the case of speculation) the risk charac-

teristics of the companys stock.

Financial theory suggests positive valuation effects of corporate hedging in the presence of cap-

ital market imperfections such as agency costs which can lead to underinvestment or asset substitution

(Bessembinder, 1991; Froot, Scharfstein, and Stein, 1993), bankruptcy cost and taxes (Smith and Stulz,

1985) and managerial incentives (Stulz, 1990). In contrast, gambling with derivatives at the firm level

may destroy firm value if it increases the expected costs of market imperfections. Nevertheless, there


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Despite its potential importance, only a few studies have addressed the relationship between

corporate derivatives use and risk measures. These studies have looked at mostly U.S. firms and the

conclusions are mixed. Faulkender (2005) finds evidence of speculation (market timing) in firms in-

terest rate risk management practices. Hentschel and Kothari (2001) find few, if any, differences in risk

between derivatives users and non-users. In contrast, Guay (1999) finds a slight reduction in the risk of

firms that initiate the use of derivatives. The results of Tufano (1996) and Allayannis and Ofek (2001)

are also consistent with the use of derivatives for hedging.

Since the consequences of derivatives use on firm risk are potentially important to a variety of

firm stakeholders, this paper aims to comprehensively address the question of whether firms are reduc-

ing or taking risks with derivatives. The analysis is based on a sample of 6,896 non-financial firms

from 47 countries including the United States, using a unique dataset of global derivatives usage.3In

particular, we investigate the systematic impact of the use of exchange rate (FX), interest rate (IR) and

commodity price (CP) derivatives on the risk characteristics of nonfinancial firms. Measures of risk are

the standard deviation of stock returns and market betas, as well as stock price exposures to exchange

rate, interest rate and commodity price risk. If firms are using derivative financial instruments for hedg-

ing purposes, derivative users may exhibit lower risk by these measures. In contrast, speculative uses of

derivatives would be consistent with higher risk, e.g. higher stock return volatility for derivatives users.

The results strongly suggest that firms use derivatives to reduce risk. Users of derivatives are

more exposed to exchange rate risk (due to more foreign sales, foreign income and foreign assets) and

i i k (d hi h l d l i k i ) b f id i h i l ff


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interest rate and commodity price exposures. These findings are consistent with hedging motives of

corporate derivatives use, but not with corporate speculation with derivatives. The results persist after

controlling for other factors that prior studies have identified as determinants of firm risk (e.g., size,

profitability, etc.) as well as the level of gross exposure. The results are also present in subsamples of

individual countries. In fact, there are notably little differences across countries in the relationship be-

tween derivatives use and measures of firm risk. The findings are also robust to controlling for differ-

ences in country risk as measured by exchange rate and interest rate volatility, political risk and trade

dependency. We investigate potential endogeneity problems between derivatives use and measures of

firm risk. While the use of derivatives is affected (among other things) by the risk and exposure of a

firm, accounting for this does not affect the finding of a negative impact of derivatives use on the risk

and exposures of firms that use derivatives.

Utilizing our international sample, we find that firms use derivatives for hedging purposes in-

dependent of shareholder rights, ownership concentration, creditor rights, legal environment, or access

to derivatives. Nevertheless, there are significant differences in the extent of exposure reduction for

different subsamples. In particular, the reduction in risk and exposure is larger for firms in countries

where derivatives are readily available, which is in line with hedging motives of derivatives use. In

contrast, the reductions in stock return volatility and exposures are smaller for firms in countries with

weak shareholder rights and ineffective legal systems, indicating small speculative dimensions of hedg-

ing with derivatives. Moreover, derivatives users in countries with weak creditor rights have signifi-

cantly larger reductions of their stock return volatility market betas interest rate exposures and com-


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sionally take positions with derivatives or adjust the size and timing of their derivatives position de-

pending on their market view. While it may be difficult to preclude all instances of improper or fraudu-

lent use of derivative instruments, the findings in this paper are reassuring for policymakers, regulators

and shareholders (as well as other stakeholders) regarding their concerns about widespread derivatives

speculation by nonfinancial corporations that might put the financial viability of firms at undue risk.

The remainder of the paper is organized as follows: The related literature is reviewed in Section

2, followed by the description of the methodology and data in Section 3. The main empirical results are

presented in Section 4, while Section 5 relates the findings to shareholder rights and access to deriva-

tives. Section 6 presents alternative specifications and robustness checks. Finally, Section 7 con-

cludes.

2 Related Literature

A large number of studies have documented the extent and nature of derivatives use by nonfinancial

firms. Many of these studies are based on questionnaires, such as the Wharton survey of U.S. nonfi-

nancial firms, which was conducted for several years (Bodnar, Hayt and Marston, 1998; Bodnar, Hayt

and Marston, 1996; Bodnar et al., 1995), as well as other surveys of U.S. firms (e.g. Nance, Smith and

Smithson, 1993). Surveys also have been conducted for selected countries outside the United States,

such as Belgium (DeCeuster et al., 2000), Canada (Downie, McMillan, and Nosal, 1996), Germany

(Bodnar and Gebhardt, 1999), Hong Kong and Singapore (Sheedy, 2002), the Netherlands (Bodnar,

Jong, and Macrae, 2002), New Zealand (Berkman, Bradbury, and Magan 1997), Sweden (Alkeback


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crease shareholder value in the presence of underinvestment or asset substitution problems (Bes-

sembinder, 1991; Froot, Scharfstein, and Stein, 1993), bankruptcy cost and taxes (Smith and Stulz,

1985) or managerial incentives (Stulz, 1990). Several papers have examined these theories empirically

and provide some, though in part mixed evidence for them (among others Nance, Smith and Smithson,

1993; Mian, 1996; Gczy, Minton, and Schrand, 1997; Allayannis and Ofek, 2001; Bartram, Brown

and Fehle, 2005). Nevertheless, evidence exists of other motivations for derivatives use such as specu-

lation, earnings management or principal-agent conflicts between managers and shareholders (Tufano,

1996; Brown, 2001; Core, Guay and Kothari, 2002). Several of the above survey studies indicate that

nonfinancial firms do not use derivatives for hedging purposes only, yet the gains from speculating (or

selective hedging) appear small at best (Adam and Fernando, 2005; Brown, Crabb, and Haushalter,

2006). To this end, Gczy, Minton, and Schrand (2005) use survey data on derivatives usage by U.S.

nonfinancial firms to document that firms with weak internal governance structures that allow for

greater managerial power and fewer shareholder rights are more likely to indicate in the Wharton sur-vey on derivatives usage that they take a view with derivatives, while these firms also have more ex-

tensive and sophisticated internal controls and monitoring mechanisms specifically related to deriva-

tives activities.

In contrast, the impact of financial derivatives use on corporate risk measures has only recently

become subject to empirical investigation. Hentschel and Kothari (2001) examine the risk characteris-

tics of a panel of 425 large U.S. nonfinancial firms in the context of their derivatives use. Their results

show no significant relationship between derivatives use and stock return volatility even for firms with


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es the exposure of the sample firms to exchange rate risk. In work on mutual funds, Koski and Pontiff

(1999) show that users of derivatives have similar risk exposure and return performance to nonusers.

3 Methodology and Data

3.1 Sample Definition and Data Sources

The markets for over-the-counter instruments and exchange-traded derivative financial instruments

(options, futures, forwards, swaps, etc.) on foreign exchange rates, interest rates and commodity prices

have exhibited exponential growth over the past 20 years (e.g. Bartram, 2000). As a result, notionalamounts outstanding for OTC derivatives reached almost $100 trillion in 2001, with interest rate deriv-

atives accounting for about three-quarters of the total (BIS, 2002). Along with increased use, regulation

for the disclosure of derivatives has developed, requiring firms in many countries to include infor-

mation about their derivatives positions in the annual report. In particular, firms in the United States,

United Kingdom, Australia, Canada and New Zealand as well as firms complying with International

Accounting Standards (IAS) are required to disclose information on their derivatives positions; many

other firms do so voluntarily.4The resulting availability of data makes the empirical analysis of the use

of derivatives by nonfinancial firms in different countries possible.

The sample in this study comprises 6,896 non-financial firms from 47 countries including the

United States. It consists of all firms that have accounting data for either the year 2000 or 2001 on theThomson Analytics database, that have an annual report in English for the same year on the Global Re-

ports database, that are not part of the financial sector (banking, insurance, etc.), and that have at least


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Firms are classified as users or non-users of derivatives based on a search of their annual re-

ports for information about the use of derivatives. The annual reports are evaluated by an automated

search. The list of search terms was compiled by manually analyzing a sample of 200 annual reports

across all countries.7After refining the list of search terms, the automated search routine led to an aver-

age reliability of 96.0% for a random sample of annual reports of 100 users and 100 non-users. Subse-

quently, an index was created based on search hits of terms that were too general to be included in the

electronic search, but that are likely to be related to derivative use. 8A total of 1,709 firms with high

scores that were classified as non-users and firms with low scores that were classified as users of deriv-

atives were checked and classified manually, since these firms have higher error rates. As a result, the

reliability of the classification improved further, yielding an error rate below 2%. 9 In addition to the

categorical data on derivatives, information on the underlying (i.e., foreign exchange, interest rates, or

commodity price) is collected. Dichotomous variables for the use of foreign debt and stock options are

created in the same fashion, since this information is not readily available elsewhere.

All capital market data (i.e. the firms stock return indices, stock market return indices, interest

rates, exchange rate indices and commodity price indices) are from Datastream. These data are provid-

ed at a daily frequency. For each firm, we calculate stock returns in local currency, local currency re-

turns of the corresponding Datastream national stock market index, the percentage change in the Bank

of England currency index (in local currency relative to the basket of foreign currencies), the percent-

age change of the Eurocurrency interest rate, the percentage change the yield of the Datastream

benchmark bond and the percentage change in the Goldman Sachs Commodity Index All time series


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Accounting data originate from the Thomson Analytics database.10Outliers are eliminated by

excluding observations in the top and bottom one percentile as well as exceeding more than five stand-

ard deviations from the median. This filter eliminates some apparent data errors where magnitudes

suggest data units are not properly reported (e.g., thousands instead of millions). Systematic differences

across countries and industries are controlled for with country and 44 industry dummy variables in the

regressions, or by regressing country, 44 industry and year dummy variables on the accounting varia-

bles and analyzing the residuals from this regression.

In some of our analysis systematic differences across countries and industries are controlled for

by regressing country, 44 industry and year dummy variables on the accounting variables and analyz-

ing the residuals from this regression. In order to avoid the results being influenced by the effect of the

economic cycle, we use three-year averages of variables where this impact seems most relevant (e.g.

coverage, foreign income).

3.2 Risk Measures and Derivatives Use

In order to study the motives of corporate derivatives usage, three different categories of risk measures

are employed. First, firms may differ with regard to their gross or pre-hedging exposure. 11 For in-

stance, measures of this with regard to foreign exchange rate risk include foreign sales (relative to total

sales), foreign income (relative to total income), and foreign assets (relative to total assets). In addition

to these individual proxies of foreign exchange rate exposure, we create a dummy variable Gross-FX-

Exposurethat is one if firms have non-zero values for any of these characteristics (and zero otherwise).


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wise. If firms are using derivatives primarily for hedging purposes, firms should be observed to use de-

rivatives if they have high measures of gross exposure.

Second, firms in different countries face different levels of macroeconomic or country risk. To

illustrate, firms operate in a more risky environment if located in a country that is characterized by high

volatility of interest rates (IR-Country) and exchange rates (FX-Country). A high ratio of (the natural

logarithm of) exports and imports relative to the Gross Domestic Product (LogEXIM/GDP) indicates a

stronger dependence of a country on international trade and thus vulnerability to exchange rate risk. In

contrast, larger economies (as measured by the logarithm of GDP) may provide a more stable operating

environment. Our aggregate measures of country risk are the International Country Risk indices that

provide inverse rankings of countries financial risk (ICR-Financial), economic risk (ICR-Economic),

political risk (ICR-Political) as well as overall country risk (ICR-Composite). It is expected that more

firms use derivatives in countries with high risk if hedging is the motivation for the use of these in-

struments.

Third, a firms net (or post-hedging) exposure is the results of the characteristics of its assets

and liabilities, and also includes the effects of off-balance sheet transactions such as derivatives.12

While the different components and their interactions are difficult to decompose, the assumption of ef-

ficient capital markets suggests that net exposures can be estimated empirically using a companys

stock price as an aggregate measure of all relevant information. Consequently, different corporate risk

measures are constructed from stock prices. In particular, for each firm the standard deviation of its

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is the percentage change of the commodity price index. 13The Newey-West procedure is used to correct

for autocorrelation and heteroscedasticity. Corporate use of derivatives for hedging purposes would be

consistent with lower stock return volatility and lower measures of post-hedging exposures as estimat-

ed in the regression framework. The estimated coefficients from this model provide our primary

measures of net exposures (risks). Specifically, net foreign exchange rate exposure is measured by j ,

which we call Net-FX-Exposure; net interest rate exposure is measured by j , which we call Net-IR-

Exposure; and net commodity price exposure j

, which we callNet-CP- Exposure. Overall (net) mar-

ket exposure is measured by j .

Additional firm characteristics are expected to be relevant for the relationship between deriva-

tives use and measures of risk and, thus, constitute important control variables. In particular, firm risk

is expected to be negatively related to industrial diversification (number of industry segments), firm

size (natural logarithm of total assets or alternatively the sum of equity market capitalization, total debt,

and preferred stock), and tangible assets (as a fraction of total assets). In contrast, firms with more

growth options, as measured by the book-to-market ratio, research and development expenses (relative

to sales) and capital expenditures (relative to total sales) are expected to exhibit higher risk.

3.3 Derivatives Usage, Corporate Governance and Derivatives Market Access

Allayannis, Lel and Miller (2003) and Lel (2003) suggest that corporate governance may be important

for the motivations of firms with ADRs to use derivatives in order to increase their firm value. There-


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future volatility of the underlying asset, possibly even under the guise of hedging, motivated by execu-

tive compensation schemes or by the objective of managers with inferior ability to increase the noise

associated with firm performance in order to hide their true skills (Breeden and Viswanathan, 1998;

DeMarzo and Duffie, 1995).

Firms in countries with poor investor protection have generally more concentrated share owner-

ship (Shleifer and Vishny, 1986, and La Porta, Lopez-de-Silanes, Shleifer, and Vishny (LLSV), 2000).

If investor protection is weak, ownership concentration can substitute for legal protection, since large

shareholders could better avoid expropriation by managers. Consequently, measures of the extent of

ownership concentration may possibly also proxy for investor rights. 15Our proxies for the strength of

investor rights are Shareholder Rights, One Share One Vote, Proxy By Mail, Shares Not Blocked, Cu-

mulative Voting, Oppressed Minority, Preemptive Rights, and Extra Meeting (all from LLSV, 1998).

Similarly, the following variables are used as (alternative) proxies for ownership concentration: Own-

ership By Three Largest Shareholders (from LLSV, 1998), Widely Held (from La Porta, Lopez-de-

Silanes, and Shleifer, 1999), Closely Held(Dahlquist et al., 2003, measure of ownership concentration)

and Closely Held Percentage(firm-level measure of shares held by insiders, pension/benefit plans, or

individuals who hold 5% or more of the outstanding shares).

One might also expect firms to use derivatives for hedging rather than speculation in the pres-

ence of strong creditor rights. Alternatively, lenders in countries with weak creditor rights might re-

quire firms to credibly commit to an effective risk management policy before providing funds. At the

i h f ff i l l i h hi h ( bli i ) l f


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Finally, easy access to derivatives may facilitate engaging in derivatives transactions for pur-

poses other than hedging because the costs of entering transactions (or more generally markets) are

lower and therefore less likely to require extraordinary actions on the part of managers. As a proxy for

access to derivatives markets we use the Derivatives Market Rank (from Bartram, Brown and Fehle,

2005), OECDmembership, and GDP per Capita. The definition of all variables is presented in Table

A-1 in the appendix. Table A-2 reports summary statistics of the main variables, and Table A-3 shows

their correlations.

4 Empirical Results

4.1 Univariate Tests

Summary statistics on the use of derivatives by the sample firms is presented in Table 1. Across all

countries, 60.5% of the firms in the sample use at least one type of derivative. FX derivatives are the

most common (45.5%), followed by interest rate derivatives (33.1%) and commodity price derivatives

(9.8%). Additional details are provided in Bartram, Brown and Fehle (2005). In order to study the rela-

tionship between the risk characteristics of the sample firms and derivatives use, we conduct nonpara-

metric Wilcoxon tests. Table 2 reports thep-values of these tests together with the means, medians and

standard deviations of firm characteristics for derivative users and non-users. While the results in Table

2 only refer to general derivatives use, the tests are also conducted for foreign exchange rate deriva-

tives, interest rate derivatives and commodity price derivatives, and differences are mentioned in the

text where appropriate.


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se tests, based on firm characteristics, are highly robust to analyzing derivatives on exchange rate risk,

interest rate risk or commodity price risk.

In addition to the business and financial risk of the firm, risks outside the company, such as

country risk, may impact a firms propensity to use derivatives for hedging or speculative purposes. To

this end, the evidence in Table 2 is mixed. The results suggest that firms in countries with higher for-

eign exchange rate risk and higher financial risk are using derivatives more frequently, which is con-

sistent with hedging motives. On the other hand, there is also evidence that more firms use derivatives

in countries with low interest rate risk, lower trade, lower aggregate country risk (economic risk or po-

litical risk) and larger GDP.16

The fact that asset, liability, and country risk are not independent suggests looking at more

comprehensive risk measures based on the firms stock returns, as well as employing a multivariate

analysis (presented in the following section). Studying stock prices is informative since they represent

an aggregate measure of asset and liability risk and should also incorporate the effects financial risk

management. If derivatives are used for hedging purposes, firms with high asset and/or liability expo-

sure (gross exposure) should be more likely to use them and, consequently, might show lower post-

hedging (net) exposure. The next part of Panel A (Table 2) shows that derivatives users exhibit signifi-

cantly lower levels of net exposure.17This is true for all measures (Std.Dev., Std.Dev.*,Beta,Net-FX-

Exposure,Net-IR-Exposure, andNet-CP-Exposure). The magnitudes of the differences are substantial.

For example, median Std.Dev.* is 24.8% lower for derivatives users than for non-users. The difference

b di k b i 17 8% Si il diff i f


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Panel B of Table 2 repeats the analysis for the most of the firm-specific variables after each var-

iable has been adjusted for country and industry fixed-effects. The results are essentially unaffected.18

Overall, the results suggest that nonfinancial firms use derivatives in line with hedging motives. Given

the relatively modest leverage ratios of the sample firms, the incremental benefits accruing from addi-

tional risk of derivatives speculation may be small, given that the equity position as an option on the

assets of the firm is relatively deep in the money, as argued by Hentschel and Kothari (2001). The find-

ings are consistent with the results of previous studies. Bartram, Brown and Fehle (2005) find in multi-

variate logit regressions of a global sample of nonfinancial firms that corporations with more leverage,

foreign debt and Gross-FX-Exposureare more likely to use derivatives, which also supports the hedg-

ing argument.

4.2 Multivariate Tests

In order to test the robustness of these findings and to account for the interdependencies between the

different variables, multivariate regressions are estimated that explore the relationship between corpo-

rate risk measures and derivatives use while controlling for the level of gross exposure and other firm

characteristics. All regressions control for country and industry effects with dummy variables. Table 3

reports the results of these regressions. The results corroborate the prior finding that derivatives users

have significantly lower stock return volatility than non-users. In particular, the coefficient of the de-

rivatives variable in Panel A is large (-0.22) and highly significant (p-value


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0.01) and significant at the 0.04 level. Firms with small size and with low exchange rate exposures tend

to have high interest rate exposures. Finally, the last column of Table 3 presents results for commodity

price exposures and documents a significantly negative relationship between derivatives use and expo-

sure for the entire sample (derivatives coefficient of 0.01,p-value = 0.03).

These results confirm the univariate findings that derivatives users tend to have lower measures

of net financial risk even though they often have higher levels of gross exposure. The exception is FX

risk. In this case the results suggest that firms using FX derivatives (who typically have greater FX ex-

posure) reduce their FX risk to a level similar to firms not using derivatives. Altogether, the findings

presented in Table 3 are strongly supportive of the hedging hypothesis and counter to the speculation

hypothesis.

To examine the relationship between derivatives use and firm risk more carefully, we also con-

duct the analysis with our measures of individual derivative type (i.e., underlying asset) and country-

specific risk variables (instead of country dummy variables). This allows us to examine more directly

differences in type of exposure as well as country risk characteristics. Results are presented in Table 4.

Panel A shows that the negative relationship between general derivatives use and corporate risk

measures remains essentially unchanged when the regression includes country-specific variables. The

only exception is the coefficient for derivatives use in theNet-FX-Exposureequation becomes signifi-

cantly negative. As expected, firms in countries with higher interest rate risk (IR-Country) have higher

levels of overall risk includingNet-IR-Exposure. International trade (LogEXIM/GDP) as one of the ma-

j f h i i i l l d f i h b


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values of the other risk measures. This might be due to relatively low usage rates of CP derivatives

compared to other types of derivatives.

These findings provide consistent support for the hypothesis that nonfinancial firms use finan-

cial derivatives for hedging purposes even after controlling for pre-hedging exposure (e.g., Gross-FX-

Exposure,Leverage, industry, etc.), country risk factors, and other firm characteristics. None of the re-

sults suggest that derivative use is associated with higher risk. Because, financial risk management is

likely to be a decision based on the level of gross exposure, it is somewhat surprising that there are no

instances in which we find higher net risk for derivative users (though in some cases there are not sig-

nificant relationships). Overall, the evidence appears to cast considerable doubt on the notion that

firms would in any way use financial derivatives to increase levels of total risk, market risk, or other

financial risks.

5 Corporate Governance and Derivatives Market Access

Corporate governance (e.g. shareholder rights, ownership concentration, etc.) and the ease at which de-

rivatives are available may influence whether and to what extent nonfinancial corporations employ de-

rivatives for hedging or speculative purposes. In order to investigate this dimension of derivatives use,

we divide the sample into subsamples of firms with different characteristics. Specifically, we estimate

regressions separately for firms with weak and strong shareholder rights. The results, presented in Ta-

ble 5, suggest that firms use derivatives for hedging purposes in both countries with both weak and

strong shareholder rights.


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risk (but lower reductions in market betas and interest rate exposures). This may reflect the fact that

higher ownership concentration can have a different effect depending on the extent of insider or outsid-

er blockholdership, and it may be a proxy for investor rights on the country level. Overall, the results

further suggest that firms do indeed use derivatives in order to reduce and not increase their risk and

exposure. Yet, the reduction is somewhat less if shareholders are weak, which is consistent with small

speculative components of hedging (e.g., selective hedging as discussed by Stulz, 1996).

The strength of creditor rights and the quality of the legal system may also impact the relation-

ship between the use of derivatives and corporate risk measures. The results in Table 6 show that the

derivatives variable has a highly significant negative coefficient for samples with weak and strong

creditor rights and legal environments across the various proxies, again confirming that firms generally

use derivatives for hedging. Moreover, the evidence for the Creditor Rightsindex suggest that deriva-

tives users in countries with weak creditor rights have significantly larger reductions of their stock re-

turn volatility, market betas, interest rate exposures and commodity price exposures, while the decrease

in foreign exchange rate exposure is smaller. Similarly, the results for components of the creditor rights

index suggest (focusing on cases where the individual coefficients are significant) that users of deriva-

tives in an environment with strong creditor protection have significantly smaller reductions in their

stock return volatility, market betas as well as exposures to commodity prices. These findings are con-

sistent with anecdotal evidence suggesting lenders in countries with weak creditor rights often require

firms to commit to an effective risk management policy when granting a loan. There is also some evi-

dence that firms in an environment with good corporate law and effective enforcement have larger re-


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6 Robustness Tests and Alternative Specifications

We examine a variety of alternative specifications and undertake additional tests to check the robust-

ness of the empirical findings. First, we conduct the analysis individually for the six countries with the

most observations (as well as all other countries together). Table 8 reports the results for each of the

five risk measures we examine (Panels A through E). As would be expected with few observations, the

statistical significance of the results is lower but the vast majority of estimated coefficients for the de-

rivatives use variable are negative. Furthermore, there are no instances where derivative use is associ-

ated with significantly higher measures of financial risk.

Disclosure of derivatives use is not a regulatory requirement for all firms in the sample, which

could lead to a potential bias if the derivatives variables capture the reporting of derivatives use rather

than derivatives use per se. In order to address this issue, the sample is limited to firms in countries

with well-regarded accounting practices (the so-called G4+1 group consisting of U.S., U.K., Canada,

Australia, and New Zealand) as well as firms reporting according to international accounting standards

(IAS). For the resulting sample of 4,645 firms, disclosure of derivatives is mandatory. Table 9 docu-

ments that the results for this subsample are very similar to the findings for the whole sample. Most

importantly, the relationship between measures of firm risk and derivatives use is very robust to the

reporting requirement.

Another concern is the potential endogeneity of derivatives use.20 In particular, the observed

measures of firm risk are not (only) a function of derivatives use, but they are likely to determine the


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of derivatives, with firms that exhibit high net(after hedging) exposures being less likely to use deriva-

tives. The coefficients and significance levels of the other determinants of derivatives use are overall

consistent with those in the prior literature, especially with Bartram, Brown and Fehle (2005). The re-

sults of the simultaneous equations approach in Table 10 are robust to estimations with foreign ex-

change rate, interest rate or commodity price derivatives.21We also perform all analyses in the paper

using 3-year (or, alternatively, 5-year) averages of the accounting data, whenever data for several years

is available, or using accounting data at the beginning of the year for which derivatives usage infor-

mation is collected. The tenor of all previous results remains unchanged.

Another potential concern is that additional risk factors identified by the asset pricing literature

might be correlated with the financial risks we examine. For example, if the Fama-French (1993) or

momentum (Carhart, 1997) factors are correlated with interest rates or FX fluctuations, then our analy-

sis might be commenting on these factor loadings for individual firms instead of the financial risks we

seek to analyze. To examine this possibility, we estimate an augmented Carhart (1997) model with the

additional financial factors noted in Equation (1). We do this estimation only for U.S. stocks due to da-

ta availability. Utilizing the net risk measures from this estimation again results in consistently negative

values for the derivatives variables though they are on average slightly smaller in magnitude than those

reported for the U.S. in Table 8.

Finally, the robustness of the results is investigated by employing alternative variables or re-

gressors that reduce the sample size.22Consistent with monetary incentives to reduce managerial risk

i k i i i l i d i h h k l ili ll fi i l


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use derivatives to increase their risk to a level that is still below that of firms with high asset risk that

do not use derivatives. Similarly, measures of foreign sales, foreign income or foreign assets may be

related to asset risk as well. The fact that a negative relationship exists between derivatives use and

stock return volatility and financial exposures even after controlling for industry classification and the

level of gross exposure suggests that firms use derivatives indeed to reduce rather than increase risk.

By the same token, firms also have alternatives to the use of derivatives to hedge against financial risks

including foreign currency debt and operational hedges. Nevertheless, the negative relationship be-

tween derivatives use and measures of firm risk persist after controlling for these potential alternatives

to financial derivatives.

7 Conclusion

Derivatives are very versatile financial instruments that can be used equally well for hedging as well as

speculation. While surveys of corporate derivatives usage indicate that many corporations use deriva-

tives at least occasionally in order to take positions depending on their market view, most of the aca-

demic risk management literature assumes a hedging motive of corporate derivatives use. This paper

comprehensively analyzes the relationship between the use of financial derivatives at the firm level and

various corporate risk measures to assess whether the use of derivatives by nonfinancial firms is con-

sistent with hedging or speculative motives. For regulators, policy makers, shareholders and other cor-

porate stakeholders alike, it is important to be aware of the risk management practices of nonfinancial

firms and the concomitant effects on firm risk.


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rights, ownership concentration, creditor rights, legal environment, or access to derivatives. At the

same time, and in line with hedging motives of derivatives use, the reduction in risk and exposure is

larger for firms in countries where derivatives are readily available. On the other hand, the reductions

in stock return volatility and exposures are smaller for firms in countries with weak shareholder rights,

ineffective legal systems, and weak law enforcement. In contrast, derivatives users in countries with

weak creditor rights have significantly larger reductions of their stock return volatility, market betas,

interest rate exposures and commodity price exposures. These findings are consistent with lenders in

countries with weak creditor rights requiring firms to commit to an effective risk management policy

when granting a loan. This suggests that nonfinancial firms overall employ derivatives with the motive

and effect of risk reduction, despite the fact that according to questionnaires they occasionally take

positions with derivatives or adjust the size and timing of their derivatives position depending on their

market view. In line with Brown, Crabb and Haushalter (2006), these speculative aspects of derivatives

use appear overall minor relative to the dominant effect of reducing corporate exposures to financialrisks, which is good news for shareholders and regulators.


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Table 1: Summary Statistics of Derivatives Use of Sample Firms

The table shows summary statistics of derivatives use by country and industry. In particular, it presentsthe number of firms and the percentage of firms using derivatives, for general derivatives use, foreign

exchange rate derivatives, interest rate derivatives and commodity price derivatives. Firms are requiredto be outside the financial sector, to have an annual report on the Global Reports database, accountingdata on Thomson Analytics and at least 36 non-missing daily stock returns for the year of the annualreport on Datastream. Other countries are Bahamas, Bermuda, Cayman Islands, Egypt, Indonesia, Pe-ru, Portugal, Turkey, and Venezuela.

Firms General FX Derivatives IR Derivatives CP Derivatives

Argentina 10 70.0 70.0 60.0 40.0

Australia 301 66.4 52.2 42.2 14.3

Austria 41 56.1 56.1 22.0 7.3

Belgium 60 50.0 36.7 23.3 3.3

Brazil 16 81.3 56.3 18.8 18.8

Canada 537 60.3 46.2 27.2 17.7

Chile 13 100.0 84.6 53.8 15.4

China 32 12.5 6.3 3.1 3.1

Czech Republic 23 26.1 13.0 17.4 0.0

Denmark 80 87.5 80.0 26.3 5.0

Finland 100 64.0 58.0 37.0 8.0

France 159 66.0 52.8 44.7 3.8

Germany 395 47.1 39.0 24.1 4.8

Greece 19 21.1 21.1 10.5 5.3

Hong Kong 319 23.2 18.5 7.2 0.3

Hungary 15 40.0 33.3 13.3 13.3

India 40 70.0 62.5 12.5 5.0

Ireland 47 85.1 70.2 53.2 14.9

Israel 48 72.9 68.8 12.5 2.1

Italy 93 61.3 38.7 33.3 2.2

Japan 366 81.1 75.4 60.4 9.6

Korea, Republic of 24 70.8 54.2 25.0 8.3

Luxembourg 11 63.6 45.5 27.3 9.1

Malaysia 289 20.1 16.3 4.2 1.0

Mexico 35 60.0 34.3 37.1 14.3

Netherlands 131 56.5 48.1 33.6 4.6

New Zealand 39 94.9 79.5 76.9 17.9

Norway 85 67.1 56.5 29.4 8.2


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Table 2: Univariate Tests of Corporate Risk Measures and Derivatives Use

The table shows the number of observations (N), mean, median and standard deviation (Std.Dev.) of different risk characteristics forall firms, derivatives users and derivatives non-users. The last column presents p-values of Wilcoxon rank sum tests between deriva-tives users and non-users. Panel A shows results for unadjusted variables while in Panel B all firm-specific variables (other than dum-my variables) are adjusted for country (47), industry (44) and year effects. All variables are defined in Table A-1 in the appendix.

Panel A: Unadjusted Variables

_____________User______________ ______________Non-User______________ _Tests__

Variable N Mean Median Std.Dev. N Mean Median Std.Dev. Wilcoxon

Gross Exposure

Foreign Sales 3166 0.359 0.315 0.31 1648 0.270 0.141 0.32 0.000

Foreign Income (3y) 2423 0.235 0.056 0.50 1477 0.143 0.000 0.51 0.000

Foreign Assets 2349 0.182 0.099 0.22 1205 0.114 0.000 0.22 0.000

Gross-FX-Exposure 4172 0.621 1.000 0.49 2724 0.395 0.000 0.49 0.000

Foreign Debt 4172 0.882 1.000 0.32 2724 0.725 1.000 0.45 0.000

Leverage 4092 0.297 0.254 0.24 2644 0.189 0.081 0.24 0.000

Coverage (3y) 4116 3.852 3.657 4.62 2656 2.544 3.333 6.73 0.000

Quick Ratio 4053 1.380 0.913 1.57 2617 2.455 1.345 2.72 0.000

Gross-IR-Exposure 4092 0.601 1.000 0.49 2644 0.343 0.000 0.47 0.000

Gross-CP-Exposure 4172 0.157 0.000 0.36 2724 0.082 0.000 0.27 0.000Gross-Exposure 4172 0.864 1.000 0.34 2724 0.611 1.000 0.49 0.000

Country Risk

IR-Country 4166 1.099 0.844 0.59 2718 1.151 0.844 0.58 0.000

FX-Country 4166 0.042 0.049 0.02 2718 0.038 0.033 0.02 0.000

LogEXIM/GDP 4169 3.802 4.024 0.78 2722 4.152 4.130 0.94 0.000

ICR-Composite 4169 83.280 84.250 4.00 2723 82.281 84.250 4.37 0.000

ICR-Financial 4169 38.455 37.000 3.75 2723 38.914 37.000 3.46 0.000

ICR-Economic 4169 42.188 42.000 2.13 2723 42.149 42.000 2.04 0.000

ICR-Political 4169 85.917 90.000 7.37 2723 83.499 88.000 8.97 0.000

LogGDP 4171 28.009 27.978 1.68 2724 27.604 27.889 1.74 0.000

Net Risk/Exposure


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Table 2: Univariate Tests of Corporate Risk Measures and Derivatives Use (continued)

Panel B: Country and Industry Adjusted Variables

_____________User______________ ______________Non-User______________ _Tests__

Variable N Mean Median Std.Dev. N Mean Median Std.Dev. Wilcoxon

Gross Exposure

Foreign Sales 3166 0.025 -0.004 0.25 1648 -0.049 -0.094 0.26 0.000

Foreign Income (3y) 2423 0.032 -0.047 0.48 1477 -0.053 -0.130 0.49 0.000Foreign Assets 2349 0.017 -0.034 0.20 1205 -0.032 -0.063 0.18 0.000

Leverage 4092 0.029 -0.005 0.22 2644 -0.045 -0.089 0.21 0.000

Coverage (3y) 4116 0.255 0.040 4.53 2656 -0.395 0.129 6.38 0.058

Quick Ratio 4053 -0.278 -0.454 1.46 2617 0.431 -0.264 2.47 0.000

Net Risk/Exposure

Std.Dev. 4172 -0.022 -0.037 0.17 2724 0.034 0.020 0.20 0.000

Std.Dev.* 4172 -0.111 -0.178 0.87 2724 0.170 0.098 0.98 0.000

Beta 4042 0.009 -0.045 0.47 2620 -0.013 -0.081 0.50 0.003

Net-FX-Exposure 4042 0.571 0.394 0.58 2620 0.768 0.546 0.70 0.000

Net-IR-Exposure 4042 0.080 0.047 0.09 2620 0.099 0.055 0.12 0.000

Net-CP-Exposure 4042 0.116 0.085 0.11 2620 0.139 0.106 0.12 0.000

Other Firm Characteristics

Logsize 4092 0.436 0.324 1.65 2644 -0.674 -0.672 1.42 0.000

Logassets 4130 0.481 0.366 1.58 2683 -0.740 -0.712 1.40 0.000

NumIndSeg 4152 0.191 -0.052 1.74 2711 -0.293 -0.525 1.54 0.000

Book-to-Market 4080 -0.004 -0.129 0.64 2634 0.007 -0.131 0.75 0.235

BM*Leverage 4078 0.023 -0.070 0.46 2630 -0.035 -0.099 0.49 0.000R&D-to-Sales 2029 -0.051 -0.039 0.29 1023 0.102 -0.033 0.64 0.002

CapEx 4069 -0.018 -0.040 0.26 2555 0.029 -0.050 0.41 0.031

Tangible Assets 3882 -0.004 0.024 0.14 2554 0.007 0.030 0.15 0.000


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29

Table 3: Multivariate Regressions of Corporate Risk Measures on Derivatives Use

The table reports regression coefficients and their p-values (in brackets) from OLS regressions of derivatives use and control variables on corporate risk measures. Be-low the coefficients, information about the adjusted R2and the number of observations is reported. Std.Dev.* is the standardized standard deviation of local currencystock returns. Beta, Net-FX-Exposure, Net-IR-Exposure and Net-CP-Exposure are the coefficients of a regression of market index returns, exchange rate changes,short-term interest rate changes and the commodity price changes, respectively, on stock returns. Regressions with exchange rate, interest rate and commodity price ex-

posures use the absolute value of the coefficient as dependent variable. All regressions use country (47), industry (44) and year dummy variables. All variables are de-fined in Table A-1 in the appendix.

Std.Dev.* Beta Net-FX-Exposure Net-IR-Exposure Net-CP-Exposure

Variable Coef pvalue Coef pvalue Coef pvalue Coef pvalue Coef pvalue

Derivatives -0.128 [0.00] -0.060 [0.00] -0.014 [0.45] -0.001 [0.72] -0.006 [0.09]

Gross-FX-Exposure 0.024 [0.31] 0.025 [0.05] -0.008 [0.63] -0.003 [0.22] -0.001 [0.85]

Foreign Debt 0.092 [0.00] 0.027 [0.10] 0.042 [0.06] 0.001 [0.87] 0.007 [0.12]

Leverage -0.031 [0.53] -0.423 [0.00] 0.019 [0.60] -0.012 [0.03] 0.001 [0.88]Logsize -0.072 [0.00] 0.116 [0.00] -0.028 [0.00] -0.004 [0.00] -0.004 [0.00]

NumIndSeg -0.027 [0.00] -0.008 [0.03] -0.018 [0.00] -0.001 [0.18] -0.001 [0.13]

Book-to-Market 0.008 [0.60] 0.024 [0.01] -0.010 [0.41] 0.004 [0.04] -0.003 [0.18]

Dividend -0.885 [0.00] -0.349 [0.00] -0.221 [0.00] -0.028 [0.00] -0.042 [0.00]

Intercept 3.896 [0.00] 0.524 [0.00] 1.162 [0.00] 0.161 [0.00] 0.201 [0.00]

Adjusted R2 0.518 0.434 0.218 0.317 0.186

Observations 6708 6497 6497 6497 6497


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Table 4: Multivariate Regressions of Corporate Risk Measures on Derivatives Use and Country Risk

The table reports regression coefficients and their p-values (in brackets) from OLS regressions of deriva-tives use and control variables on corporate risk measures. Below the coefficients, information about the

adjusted R2and the number of observations is reported. Std.Dev.* is the standardized standard deviationof local currency stock returns. Beta, Net-FX-Exposure, Net-IR-Exposure and Net-CP-Exposure are thecoefficients of a regression of market index returns, exchange rate changes, short-term interest rate chang-es and the commodity price changes, respectively, on stock returns. Regressions with exchange rate, in-terest rate and commodity price exposures use the absolute value of the coefficient as dependent variable.All regressions use industry (44) and year dummy variables. Panel A refers to general derivatives use,Panel B refers to foreign exchange rate derivatives use, Panel C refers to interest rate derivatives use, andPanel D refers to commodity price derivatives use. All variables are defined in Table A-1 in the appendix.

Panel A: General Derivatives Use



Derivatives -0.112 [0.00] -0.072 [0.00] -0.072 [0.00] -0.001 [0.63] -0.010 [0.00]

Gross-FX-Exposure 0.021 [0.41] 0.013 [0.31] 0.024 [0.17] -0.009 [0.00] 0.001 [0.71]

Foreign Debt 0.098 [0.00] 0.010 [0.55] -0.009 [0.70] 0.001 [0.79] 0.002 [0.57]

Leverage 0.001 [0.99] -0.419 [0.00] 0.018 [0.62] -0.007 [0.23] 0.000 [0.98]

Logsize -0.094 [0.00] 0.114 [0.00] -0.006 [0.29] -0.003 [0.00] -0.002 [0.05]

NumIndSeg -0.012 [0.08] -0.001 [0.81] -0.012 [0.01] -0.002 [0.01] -0.001 [0.25]Book-to-Market -0.017 [0.33] 0.028 [0.00] 0.010 [0.38] 0.002 [0.21] -0.001 [0.68]

Dividend -0.906 [0.00] -0.356 [0.00] -0.274 [0.00] -0.038 [0.00] -0.049 [0.00]

LogEXIM/GDP -0.137 [0.00] -0.037 [0.00] 0.053 [0.00] -0.007 [0.00] -0.004 [0.06]

IR-Country -0.108 [0.00] -0.032 [0.01] 0.250 [0.00] 0.021 [0.00] 0.021 [0.00]

ICR-Political 0.004 [0.01] -0.012 [0.00] -0.008 [0.00] 0.001 [0.00] 0.000 [0.19]

Intercept 4.219 [0.00] 1.759 [0.00] 1.106 [0.00] 0.026 [0.25] 0.137 [0.00]

Adjusted R2 0.413 0.396 0.151 0.236 0.173

Observations 6703.00 6497.00 6497.00 6497.00 6497.00


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Table 4: Multivariate Regressions of Corporate Risk Measures on Derivatives Use and Country Risk

(continued)

Panel C: Interest Rate Derivatives Use



IR_Derivatives -0.135 [0.00] -0.116 [0.00] -0.030 [0.11] -0.003 [0.27] -0.010 [0.00]


Foreign Debt 0.081 [0.01] 0.002 [0.92] -0.023 [0.31] 0.001 [0.81] 0.001 [0.86]

Leverage 0.027 [0.62] -0.389 [0.00] 0.009 [0.81] -0.006 [0.31] 0.002 [0.82]

Logsize -0.092 [0.00] 0.117 [0.00] -0.008 [0.12] -0.003 [0.00] -0.002 [0.05]

NumIndSeg -0.010 [0.13] 0.000 [0.90] -0.011 [0.01] -0.002 [0.01] -0.001 [0.31]

Book-to-Market -0.018 [0.29] 0.027 [0.00] 0.010 [0.40] 0.002 [0.22] -0.001 [0.65]

Dividend -0.901 [0.00] -0.350 [0.00] -0.276 [0.00] -0.038 [0.00] -0.048 [0.00]

LogEXIM/GDP -0.140 [0.00] -0.040 [0.00] 0.055 [0.00] -0.007 [0.00] -0.004 [0.05]

IR-Country -0.107 [0.00] -0.033 [0.01] 0.253 [0.00] 0.021 [0.00] 0.021 [0.00]

ICR-Political 0.004 [0.01] -0.012 [0.00] -0.008 [0.00] 0.001 [0.00] 0.000 [0.21]Intercept 4.184 [0.00] 1.718 [0.00] 1.143 [0.00] 0.025 [0.28] 0.137 [0.00]

Adjusted R2 0.413 0.400 0.150 0.237 0.172

Observations 6703.00 6497.00 6497.00 6497.00 6497.00

Panel D: Commodity Price Derivatives Use




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32

Table 5: Derivatives Usage, Shareholder Rights and Ownership Concentration

The table reports regression coefficients and theirp-values (in brackets) from OLS regressions of derivatives use and control variables on corporate risk measures. Regressions distinguishbetween environments of weak or strong ownership concentration and shareholder rights. Panel A reports results for a specification based on Shareholder Rights. Panel B shows results forthe derivatives variable only where weak and strong ownership concentration and shareholder rights are distinguished based on alternative variables. Ownership concentration is strong forfirms where Closely Held (Ownership, Closely Held (Pct)) is above the sample median or where Widely Held is below the sample median. Shareholder rights are strong for firms whereShareholder Rights (Extra Meeting) is above the sample median or where One Share One Vote (Proxy Mail, Shares not Blocked, Cumulative Voting, Oppressed Minority, Preemptive

Rights) is equal to one. Below the coefficients, information about the adjusted R

2

and the number of observations is reported. *, **, and *** indicate that the coefficient of the derivativesvariable is significantly different for subsamples with strong and weak ownership concentration and shareholder rights at the 10%, 5% and 1% significance level, respectively. Std.Dev.*is the standardized standard deviation of local currency stock returns. Beta, Net-FX-Exposure, Net-IR-Exposure and Net-CP-Exposure are the coefficients of a regression of market indexreturns, exchange rate changes, short-term interest rate changes and the commodity price changes, respectively, on stock returns. Regressions with exchange rate, interest rate andcommodity price exposures use the absolute value of the coefficient as dependent variable. All variables are defined in Table A-1 in the appendix.


weak strong weak strong weak strong weak strong weak strong

Variable Coef pvalue Coef pvalue Coef pvalue Coef pvalue Coef pvalue Coef pvalue Coef pvalue Coef pvalue Coef pvalue Coef pvalue

Panel A: Results fo r Specification Based on Shareholder RightsDerivatives -0.01 [0.82]* -0.06 [0.05] -0.03 [0.17] -0.01 [0.42] -0.13 [0.00] -0.12 [0.00] -0.00 [0.25] 0.00 [0.89] -0.01 [0.01] -0.01 [0.07]

Gross-FX-Exposure 0.06 [0.05] 0.00 [0.99] 0.05 [0.00] -0.00 [0.89] 0.07 [0.00] 0.03 [0.28] 0.00 [0.98] -0.01 [0.00] 0.00 [0.39] -0.00 [0.94]

Foreign Debt 0.08 [0.15] 0.09 [0.01] 0.01 [0.69] 0.03 [0.08] 0.06 [0.09] 0.01 [0.68] 0.00 [0.83] -0.00 [0.55] -0.00 [0.92] 0.01 [0.06]

Leverage 0.05 [0.54] -0.06 [0.49] -0.30 [0.00] -0.52 [0.00] 0.01 [0.79] 0.03 [0.64] -0.02 [0.00] -0.01 [0.18] 0.01 [0.45] -0.02 [0.10]

Logsize -0.10 [0.00] -0.09 [0.00] 0.10 [0.00] 0.11 [0.00] -0.01 [0.17] -0.01 [0.08] 0.00 [0.85] -0.00 [0.08] -0.00 [0.01] -0.00 [0.06]

NumIndSeg -0.04 [0.00] -0.03 [0.00] -0.01 [0.04] -0.01 [0.01] -0.02 [0.00] -0.01 [0.07] -0.00 [0.11] 0.00 [0.05] -0.00 [0.27] 0.00 [0.88]

Dividend -0.70 [0.00] -0.64 [0.00] -0.28 [0.00] -0.26 [0.00] -0.28 [0.00] -0.33 [0.00] -0.05 [0.00] -0.05 [0.00] -0.05 [0.00] -0.06 [0.00]

Intercept 0.32 [0.00] 0.27 [0.00] 0.15 [0.00] 0.11 [0.00] 0.71 [0.00] 0.86 [0.00] 0.09 [0.00] 0.10 [0.00] 0.14 [0.00] 0.15 [0.00]

Adjusted R2 0.22 0.20 0.15 0.18 0.09 0.09 0.13 0.22 0.09 0.07

Observations 2908.0 3800.0 2710.0 3787.0 2710.0 3787.0 2710.0 3787.0 2710.0 3787.0

Panel B: Results for Alternative Measures of Shareholder Rights and Ownership Concentration (Derivatives Variable only)One Share One Vote -0.04 [0.14] 0.01 [0.82] -0.01 [0.30] -0.04 [0.22] -0.12 [0.00] -0.16 [0.00] -0.00 [0.14] -0.00 [0.00] -0.01 [0.01] -0.01 [0.02]

Proxy Mail 0.04 [0.27]*** -0.08 [0.01] -0.02 [0.48] -0.02 [0.22] -0.11 [0.00] -0.13 [0.00] -0.00 [0.36] -0.00 [0.64] -0.01 [0.02] -0.01 [0.03]

Shares not Blocked 0.15 [0.01]*** -0.08 [0.00] 0.02 [0.58]*** -0.03 [0.03] -0.03 [0.57]*** -0.13 [0.00] -0.02 [0.01]*** 0.00 [0.42] -0.01 [0.04]** -0.01 [0.03]Cumulative Voting 0.03 [0.36]*** -0.13 [0.00] -0.00 [0.98]** -0.04 [0.03] -0.19 [0.00]*** -0.06 [0.03] 0.00 [0.25]*** -0.01 [0.00] -0.01 [0.00] -0.01 [0.06]

Oppressed Minority 0.12 [0.02]*** -0.08 [0.00] 0.01 [0.72]*** -0.03 [0.04] -0.09 [0.02] -0.13 [0.00] -0.02 [0.00]*** 0.00 [0.15] -0.01 [0.04] -0.01 [0.04]

Preemptive Rights -0.11 [0.00]*** 0.06 [0.13] -0.04 [0.04]** 0.00 [0.85] -0.08 [0.00]*** -0.17 [0.00] -0.02 [0.00]*** 0.01 [0.04] -0.01 [0.01] -0.01 [0.01]

Extra Meeting -0.04 [0.12] -0.07 [0.15] -0.04 [0.01]* 0.01 [0.72] -0.10 [0.00] -0.13 [0.00] 0.00 [0.42]** -0.01 [0.04] -0.00 [0.16]** -0.02 [0.01]

Closely Held (Pct) -0.07 [0.03] -0.02 [0.54] -0.04 [0.03] -0.01 [0.56] -0.11 [0.00] -0.12 [0.00] -0.00 [0.36]** 0.00 [0.22] -0.01 [0.10] -0.01 [0.03]

Closely Held -0.05 [0.19] -0.02 [0.46] -0.03 [0.16] -0.01 [0.52] -0.03 [0.26]*** -0.18 [0.00] -0.01 [0.16]*** 0.00 [0.16] -0.01 [0.23]* -0.01 [0.00]

Ownership -0.02 [0.55] -0.05 [0.11] -0.02 [0.24] -0.02 [0.20] -0.02 [0.47]*** -0.17 [0.00] -0.00 [0.27]*** 0.01 [0.01] -0.01 [0.16] -0.01 [0.01]

Widely Held -0.02 [0.47] -0.05 [0.14] -0.02 [0.24] -0.02 [0.20] -0.02 [0.48]*** -0.17 [0.00] -0.00 [0.24]*** 0.01 [0.01] -0.01 [0.17] -0.01 [0.01]


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Table 6: Derivatives Usage, Creditor Rights and Legal Environment

The table reports regression coefficients and theirp-values (in brackets) from OLS regressions of derivatives use and control variables on corporate risk measures. Regressions distinguishbetween environments of weak or strong legal systems and creditor rights. Panel A reports results for a specification based on Creditor Rights. Panel B shows results for the derivativesvariable only where weak and strong legal environment and creditor rights are distinguished based on alternative variables. The legal environment is strong for firms where Rule of Law(Legality, KKZ-Rule of Law, Private Enforcement, Public Enforcement) is greater than the sample median. Creditor rights are strong for firms where Creditor Rights (English CL,Judicial Efficiency, Corruption, Expropriation Risk, Contract Repudiation, Legal Reserve) is greater than the sample median or where Restrict Reorganization (No Stay on Assets,Management not Stay) is equal to one. Below the coefficients, information about the adjusted R2and the number of observations is reported. *, **, and *** indicate that the coefficient ofthe derivatives variable is significantly different for subsamples with strong and weak legal environment and creditor rights at the 10%, 5% and 1% significance level, respectively.

Std.Dev.* is the standardized standard deviation of local currency stock returns. Beta, Net-FX-Exposure, Net-IR-Exposure and Net-CP-Exposure are the coefficients of a regression ofmarket index returns, exchange rate changes, short-term interest rate changes and the commodity price changes, respectively, on stock returns. Regressions with exchange rate, interestrate and commodity price exposures use the absolute value of the coefficient as dependent variable. All variables are defined in Table A-1 in the appendix.


weak strong weak strong weak strong weak strong weak strong


Panel A: Results for Specification Based on Creditor RightsDerivatives -0.16 [0.00]*** 0.09 [0.01] -0.06 [0.00]*** 0.02 [0.28] -0.06 [0.02]*** -0.20 [0.00] -0.01 [0.00]*** -0.00 [0.40] -0.01 [0.03] -0.01 [0.00]

Gross-FX-Exposure -0.03 [0.33] 0.07 [0.02] -0.01 [0.64] 0.05 [0.01] 0.07 [0.01] 0.04 [0.06] -0.01 [0.01] -0.01 [0.03] 0.00 [0.61] 0.00 [0.75]

Foreign Debt 0.13 [0.00] 0.09 [0.09] 0.05 [0.02] 0.01 [0.66] -0.06 [0.07] 0.15 [0.00] 0.01 [0.10] 0.01 [0.16] 0.01 [0.11] 0.01 [0.05]

Leverage -0.03 [0.73] 0.00 [0.99] -0.48 [0.00] -0.35 [0.00] 0.04 [0.49] -0.01 [0.86] -0.01 [0.52] -0.02 [0.01] -0.02 [0.11] 0.01 [0.52]

Logsize -0.15 [0.00] -0.04 [0.00] 0.10 [0.00] 0.11 [0.00] -0.03 [0.00] 0.00 [0.61] -0.00 [0.00] 0.00 [0.04] -0.00 [0.00] -0.00 [0.24]

NumIndSeg -0.03 [0.01] -0.05 [0.00] -0.01 [0.01] -0.01 [0.02] -0.01 [0.18] -0.02 [0.00] 0.00 [0.18] -0.00 [0.06] 0.00 [0.78] -0.00 [0.18]Dividend -0.69 [0.00] -0.65 [0.00] -0.28 [0.00] -0.24 [0.00] -0.34 [0.00] -0.28 [0.00] -0.05 [0.00] -0.04 [0.00] -0.05 [0.00] -0.05 [0.00]

Intercept 0.37 [0.00] 0.21 [0.00] 0.15 [0.00] 0.10 [0.00] 0.82 [0.00] 0.72 [0.00] 0.11 [0.00] 0.07 [0.00] 0.15 [0.00] 0.13 [0.00]

Adjusted R2 0.28 0.17 0.19 0.15 0.11 0.10 0.21 0.11 0.07 0.08

Observations 3321.0 3387.0 3258.0 3239.0 3258.0 3239.0 3258.0 3239.0 3258.0 3239.0

Panel B: Results for Alternative Measures of Creditor Rights and Legal Environment (Derivatives Variable only)English CL 0.13 [0.00]*** -0.10 [0.00] 0.02 [0.49]*** -0.04 [0.01] -0.11 [0.00] -0.12 [0.00] -0.03 [0.00]*** 0.01 [0.05] -0.01 [0.02] -0.01 [0.09]

Judicial Efficiency -0.11 [0.01]*** -0.01 [0.60] -0.05 [0.04]** -0.01 [0.36] -0.11 [0.00] -0.12 [0.00] 0.01 [0.06]*** -0.00 [0.54] -0.01 [0.05] -0.01 [0.06]

Corruption -0.03 [0.52] -0.02 [0.44] -0.02 [0.29] -0.01 [0.51] -0.23 [0.00]*** -0.06 [0.01] 0.01 [0.03]*** -0.01 [0.00] -0.01 [0.04] -0.01 [0.01]

Expropriation Risk -0.01 [0.65] -0.06 [0.13] -0.01 [0.70] -0.03 [0.13] -0.19 [0.00]*** -0.06 [0.06] 0.01 [0.02]*** -0.01 [0.00] -0.01 [0.00] -0.01 [0.09]

Contract Repudiation -0.16 [0.00]*** 0.17 [0.00] -0.06 [0.00]*** 0.04 [0.06] -0.13 [0.00] -0.10 [0.00] 0.01 [0.06]*** -0.02 [0.00] -0.01 [0.18]* -0.01 [0.00]

Legal Reserve -0.07 [0.01]*** 0.08 [0.09] -0.03 [0.02] 0.01 [0.77] -0.11 [0.00] -0.15 [0.00] 0.01 [0.05]*** -0.03 [0.00] -0.01 [0.10] -0.01 [0.02]

Restrict Reorganizat -0.13 [0.00]*** 0.07 [0.05] -0.05 [0.00]*** 0.01 [0.57] -0.06 [0.01]*** -0.19 [0.00] -0.01 [0.00]*** 0.00 [0.43] -0.01 [0.03] -0.01 [0.00]No Stay on Assets -0.09 [0.00]*** 0.05 [0.18] -0.04 [0.02]** 0.01 [0.74] -0.06 [0.01]*** -0.20 [0.00] -0.02 [0.00]*** 0.00 [0.52] -0.01 [0.03] -0.01 [0.00]

Management not Stay -0.08 [0.00]*** 0.08 [0.04] -0.04 [0.02]*** 0.02 [0.39] -0.08 [0.00]*** -0.24 [0.00] -0.01 [0.00]*** 0.00 [0.94] -0.01 [0.02] -0.01 [0.00]

Rule of Law 0.04 [0.16]*** -0.10 [0.00] 0.01 [0.72]** -0.04 [0.03] -0.20 [0.00]*** -0.07 [0.01] -0.00 [0.66]*** -0.02 [0.00] -0.01 [0.00] -0.01 [0.06]

Legality 0.02 [0.54]*** -0.08 [0.02] 0.00 [0.92]** -0.04 [0.05] -0.20 [0.00]*** -0.08 [0.00] 0.00 [0.64]*** -0.02 [0.00] -0.01 [0.00] -0.01 [0.05]

Private Enforcement 0.09 [0.01]*** -0.16 [0.00] 0.03 [0.19]*** -0.07 [0.00] -0.11 [0.00] -0.11 [0.00] -0.02 [0.00]*** 0.01 [0.07] -0.01 [0.01] -0.01 [0.25]

Public Enforcement 0.07 [0.03]*** -0.15 [0.00] 0.01 [0.61]*** -0.05 [0.01] -0.12 [0.00] -0.14 [0.00] -0.01 [0.03]* -0.00 [1.00] -0.01 [0.00] -0.01 [0.12]


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Table 7: Derivatives Usage and Derivative Market Access

The table reports regression coefficients and theirp-values (in brackets) from OLS regressions of derivatives use and control variables on corporate risk measures. Regressions distinguishbetween environments of easy and difficult market access to derivatives. Panel A reports results for a specification based on DerMktRank. Panel B shows results for the derivativesvariable only where easy and difficult derivatives market access is distinguished based on alternative variables. Access to derivatives is easy for firms where Derivatives Market Rank(GDP/Capita) is greater than the sample median or where the country of incorporation is in the OECD. Below the coefficients, information about the adjusted R2 and the number of

observations is reported. *, **, and *** indicate that the coefficient of the derivatives variable is significantly different for subsamples with easy and difficult access to derivatives at the10%, 5% and 1% significance level, respectively. Std.Dev.* is the standardized standard deviation of local currency stock returns. Beta, Net-FX-Exposure, Net-IR-Exposure and Net-CP-Exposure are the coefficients of a regression of market index returns, exchange rate changes, short-term interest rate changes and the commodity price changes, respectively, on stockreturns. Regressions with exchange rate, interest rate and commodity price exposures use the absolute value of the coefficient as dependent variable. All variables are defined in Table A-1in the appendix.


easy difficult easy difficult easy difficult easy difficult easy difficult


Panel A: Results for Specification Based on DerMktRankDerivatives -0.01 [0.73] -0.05 [0.15] -0.01 [0.48] -0.03 [0.13] -0.04 [0.13]*** -0.18 [0.00] -0.01 [0.04]*** 0.01 [0.00] -0.01 [0.05] -0.01 [0.03]

Gross-FX-Exposure -0.01 [0.69] 0.04 [0.18] -0.00 [0.96] 0.04 [0.03] 0.01 [0.74] 0.10 [0.00] -0.00 [0.45] -0.01 [0.00] 0.00 [0.40] -0.00 [0.95]

Foreign Debt 0.09 [0.01] 0.13 [0.01] 0.06 [0.01] 0.00 [0.95] -0.04 [0.13] 0.12 [0.00] -0.01 [0.05] -0.01 [0.17] 0.00 [0.48] 0.01 [0.25]

Leverage -0.22 [0.01] 0.21 [0.02] -0.48 [0.00] -0.32 [0.00] -0.09 [0.10] 0.12 [0.05] -0.03 [0.00] -0.01 [0.33] -0.02 [0.05] 0.01 [0.43]

Logsize -0.06 [0.00] -0.15 [0.00] 0.11 [0.00] 0.10 [0.00] -0.00 [0.70] -0.02 [0.01] 0.00 [0.13] -0.01 [0.00] -0.00 [0.50] -0.01 [0.00]

NumIndSeg -0.04 [0.00] -0.02 [0.01] -0.02 [0.00] 0.00 [0.81] -0.01 [0.07] -0.02 [0.01] 0.00 [0.28] 0.00 [0.80] -0.00 [0.66] 0.00 [0.89]

Dividend -0.61 [0.00] -0.64 [0.00] -0.28 [0.00] -0.23 [0.00] -0.40 [0.00] -0.23 [0.00] -0.06 [0.00] -0.05 [0.00] -0.06 [0.00] -0.05 [0.00]

Intercept 0.21 [0.00] 0.29 [0.00] 0.12 [0.00] 0.12 [0.00] 0.84 [0.00] 0.70 [0.00] 0.10 [0.00] 0.10 [0.00] 0.15 [0.00] 0.14 [0.00]

Adjusted R2 0.19 0.23 0.19 0.14 0.13 0.08 0.24 0.13 0.09 0.08

Observations 3644.0 3064.0 3644.0 2853.0 3644.0 2853.0 3644.0 2853.0 3644.0 2853.0

Panel B: Results for Alternative Measures of Derivatives Market Access (Derivatives Variable only)OECD -0.03 [0.26] -0.01 [0.86] -0.02 [0.29] -0.03 [0.28] -0.06 [0.00]*** -0.15 [0.00] -0.01 [0.00]** -0.00 [0.17] -0.01 [0.01] -0.01 [0.07]

GDP/Capita -0.09 [0.00]** -0.01 [0.79] -0.03 [0.09] -0.01 [0.49] -0.18 [0.00]*** -0.10 [0.00] -0.01 [0.08]*** 0.00 [0.21] -0.01 [0.02] -0.01 [0.05]


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Table 8: Multivariate Regressions of Corporate Risk Measures on Derivatives Use By Country

The table reports regression coefficients and their p-values (in brackets) from OLS regressions of derivatives use and control variables on corporate risk measures. Belowthe coefficients, information about the adjusted R2and the number of observations are reported. Panel A refers to the standardized standard deviation of local currencystock returns. Panel B, C, D and E refer to the coefficients of a regression of market index returns (market betas), exchange rate changes (net exchange rate exposures),short-term interest rate changes (net interest rate exposures) and the commodity price changes (net commodity price exposures), respectively, on stock returns. Regres-sions with exchange rate, interest rate and commodity price exposures use the absolute value of the coefficient as dependent variable. All regressions use industry (44) andyear dummy variables (and country dummies for the all other subsample). All variables are defined in Table A-1 in the appendix.

Panel A: Standard Deviations of Stock Return and Derivatives Use

United States United Kingdom Canada Germany Japan Australia All Other

Variable Coef pvalue Coef pvalue Coef pvalue Coef pvalue Coef pvalue Coef pvalue Coef pvalue

Derivatives -0.165 [0.00] 0.047 [0.55] -0.191 [0.05] 0.064 [0.49] 0.006 [0.92] -0.795 [0.00] -0.046 [0.21]

Gross-FX-Exposure -0.130 [0.00] 0.083 [0.25] -0.100 [0.26] 0.112 [0.22] -0.077 [0.20] 0.214 [0.16] 0.048 [0.17]

Foreign Debt 0.068 [0.14] 0.208 [0.04] 0.104 [0.41] -0.036 [0.75] 0.035 [0.69] 0.107 [0.61] 0.089 [0.12]

Leverage -0.101 [0.28] -0.099 [0.61] 0.711 [0.00] -0.670 [0.00] 0.036 [0.75] 0.095 [0.80] 0.237 [0.00]

Logsize -0.096 [0.00] 0.050 [0.02] -0.283 [0.00] 0.005 [0.87] -0.054 [0.01] -0.230 [0.00] -0.063 [0.00]

NumIndSeg -0.028 [0.02] -0.038 [0.08] 0.021 [0.46] -0.087 [0.00] -0.014 [0.33] 0.013 [0.75] -0.029 [0.00]

Book-to-Market 0.022 [0.46] 0.070 [0.25] -0.126 [0.04] 0.060 [0.38] -0.267 [0.00] 0.226 [0.06] -0.042 [0.05]

Dividend -0.787 [0.00] -0.875 [0.00] -0.760 [0.00] -0.936 [0.00] -0.518 [0.00] -1.774 [0.00] -0.763 [0.00]

Intercept 4.303 [0.00] 2.630 [0.00] 5.356 [0.00] 3.667 [0.00] 3.346 [0.00] 6.234 [0.00] 3.523 [0.00]

Adjusted R2 0.549 0.363 0.580 0.603 0.454 0.627 0.492

Observations 2032.0 852.00 499.00 394.00 366.00 274.00 2291.0

Panel B: Market Betas and Derivatives Use



Derivatives -0.073 [0.00] 0.002 [0.95] -0.007 [0.88] 0.048 [0.44] -0.066 [0.21] -0.201 [0.01] -0.063 [0.01]

Gross-FX-Exposure -0.082 [0.00] 0.038 [0.27] 0.011 [0.79] 0.119 [0.06] 0.028 [0.54] 0.076 [0.24] 0.042 [0.05]

Foreign Debt 0.055 [0.05] 0.041 [0.39] -0.026 [0.67] 0.085 [0.26] 0.112 [0.11] 0.056 [0.53] -0.000 [1.00]

Leverage -0.509 [0.00] -0.340 [0.00] -0.421 [0.00] -0.584 [0.00] -0.142 [0.10] -0.385 [0.02] -0.265 [0.00]Logsize 0.119 [0.00] 0.126 [0.00] 0.087 [0.00] 0.122 [0.00] 0.068 [0.00] 0.113 [0.00] 0.109 [0.00]

NumIndSeg -0.017 [0.02] -0.012 [0.25] 0.026 [0.06] -0.066 [0.00] -0.001 [0.95] 0.009 [0.63] 0.001 [0.88]

Book-to-Market 0.007 [0.69] 0.051 [0.08] 0.017 [0.55] 0.018 [0.70] -0.120 [0.01] -0.017 [0.73] 0.021 [0.11]

Dividend -0.379 [0.00] -0.234 [0.00] -0.311 [0.00] -0.477 [0.00] -0.108 [0.08] -0.409 [0.00] -0.303 [0.00]

Intercept 0.676 [0.00] 0.080 [0.20] 0.520 [0.00] 0.709 [0.00] 0.589 [0.00] 0.577 [0.00] 0.545 [0.00]

Adjusted R2 0.505 0.334 0.449 0.420 0.404 0.278 0.356

Observations 2032.0 852.00 499.00 394.00 366.00 274.00 2080.0

(continued)


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Table 8: Multivariate Regressions of Corporate Risk Measures on Derivatives Use By Country (continued)

Panel C: Net Foreign Exchange Rate Exposure and Derivatives Use



Derivatives -0.014 [0.71] -0.002 [0.93] -0.084 [0.16] -0.091 [0.29] 0.016 [0.69] -0.028 [0.52] 0.010 [0.77]

Gross-FX-Exposure -0.032 [0.43] -0.033 [0.23] -0.182 [0.00] -0.071 [0.40] 0.037 [0.30] 0.018 [0.61] 0.048 [0.12]

Foreign Debt 0.017 [0.68] 0.054 [0.16] 0.147 [0.06] 0.186 [0.07] 0.028 [0.60] 0.026 [0.60] 0.049 [0.35]

Leverage -0.064 [0.45] 0.028 [0.71] 0.340 [0.01] -0.226 [0.21] -0.062 [0.36] 0.191 [0.03] 0.046 [0.48]

Logsize -0.038 [0.00] 0.006 [0.49] -0.096 [0.00] -0.010 [0.70] -0.028 [0.03] -0.007 [0.58] -0.025 [0.02]

NumIndSeg -0.018 [0.08] -0.016 [0.06] -0.004 [0.81] -0.017 [0.45] -0.010 [0.25] -0.013 [0.21] -0.024 [0.00]

Book-to-Market -0.006 [0.82] -0.005 [0.84] -0.130 [0.00] 0.021 [0.73] -0.031 [0.37] -0.003 [0.90] -0.007 [0.71]

Dividend -0.230 [0.00] -0.145 [0.00] -0.104 [0.10] -0.304 [0.00] -0.086 [0.07] -0.157 [0.00] -0.248 [0.00]

Intercept 1.273 [0.00] 0.503 [0.00] 1.208 [0.00] 0.957 [0.00] 0.675 [0.00] 0.353 [0.00] 0.668 [0.00]

Adjusted R2 0.129 0.064 0.263 0.101 0.037 0.098 0.209

Observations 2032.0 852.00 499.00 394.00 366.00 274.00 2080.0

Panel D: Net Interest Rate Exposures and Derivatives Use



Derivatives -0.005 [0.45] 0.003 [0.43] 0.016 [0.24] 0.004 [0.78] 0.000 [0.48] -0.028 [0.06] -0.003 [0.33]

Gross-FX-Exposure -0.012 [0.06] -0.004 [0.21] -0.020 [0.11] 0.003 [0.85] 0.000 [0.89] 0.004 [0.72] 0.004 [0.19]

Foreign Debt -0.003 [0.71] 0.005 [0.27] 0.010 [0.59] 0.027 [0.12] -0.001 [0.23] 0.012 [0.49] -0.002 [0.71]

Leverage -0.020 [0.15] -0.001 [0.89] 0.016 [0.58] -0.038 [0.20] 0.001 [0.37] 0.034 [0.26] -0.001 [0.90]

Logsize -0.006 [0.00] 0.002 [0.05] -0.017 [0.00] 0.004 [0.41] -0.000 [0.15] -0.002 [0.73] -0.004 [0.00]

NumIndSeg 0.000 [0.88] -0.001 [0.18] 0.002 [0.62] -0.006 [0.09] -0.000 [0.05] -0.001 [0.72] -0.002 [0.06]

Book-to-Market -0.001 [0.78] 0.006 [0.02] 0.001 [0.91] 0.014 [0.18] 0.000 [0.63] 0.007 [0.49] -0.002 [0.25]

Dividend -0.028 [0.00] -0.018 [0.00] -0.030 [0.05] -0.036 [0.02] -0.003 [0.00] -0.075 [0.00] -0.016 [0.00]Intercept 0.166 [0.00] 0.039 [0.00] 0.248 [0.00] 0.133 [0.00] 0.013 [0.00] 0.150 [0.00] 0.086 [0.00]

Adjusted R2 0.302 0.100 0.178 0.127 0.131 0.209 0.353

Observations 2032.0 852.00 499.00 394.00 366.00 274.00 2080.0

(continued)


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Table 9: Multivariate Regressions for G4+1 Countries

The table reports regression coefficients and their p-values (in brackets) from OLS regressions of general deriva-tives use and control variables on corporate risk measures. Below the coefficients, information about the adjusted

R2and the number of observations is reported. Std.Dev.* is the standardized standard deviation of local currencystock returns. Beta, Net-FX-Exposure, Net-IR-Exposure and Net-CP-Exposure are the coefficients of a regressionof market index returns, exchange rate changes, short-term interest rate changes and the commodity price changes,respectively, on stock returns. Regressions with exchange rate, interest rate and commodity price exposures use theabsolute value of the coefficient as dependent variable. All regressions use industry (44) and year dummy varia-bles. The table is based on firms in G4+1 countries and those complying with IAS. All variables are defined in Ta-ble A-1 in the appendix.

Std.Dev.* Beta Net-FX-Exposure Net-IR-Exposure Net-CP-ExposureVariable Coef pvalue Coef pvalue Coef pvalue Coef pvalue Coef pvalue

Derivatives -0.139 [0.00] -0.071 [0.00] -0.061 [0.00] -0.002 [0.58] -0.010 [0.02]

Gross-FX-Exposure -0.024 [0.45] 0.003 [0.85] -0.014 [0.49] -0.011 [0.00] 0.000 [0.99]

Foreign Debt 0.139 [0.00] 0.030 [0.13] 0.022 [0.38] 0.005 [0.22] 0.005 [0.31]

Leverage 0.026 [0.72] -0.428 [0.00] 0.042 [0.35] -0.007 [0.38] -0.001 [0.91]

Logsize -0.113 [0.00] 0.110 [0.00] -0.014 [0.02] -0.004 [0.00] -0.001 [0.40]

NumIndSeg -0.005 [0.56] -0.001 [0.74] -0.007 [0.20] 0.000 [0.81] -0.002 [0.14]

Dividend -0.916 [0.00] -0.345 [0.00] -0.251 [0.00] -0.040 [0.00] -0.048 [0.00]

LogEXIM/GDP -0.094 [0.00] -0.060 [0.00] -0.010 [0.56] 0.001 [0.63] -0.005 [0.16]

IR-Country -0.121 [0.00] 0.036 [0.09] 0.386 [0.00] 0.057 [0.00] 0.036 [0.00]ICR-Political 0.007 [0.01] -0.017 [0.00] -0.014 [0.00] -0.000 [0.58] -0.001 [0.18]

Intercept 3.933 [0.00] 2.215 [0.00] 1.749 [0.00] 0.074 [0.04] 0.181 [0.00]

Adjusted R2 0.432 0.428 0.181 0.248 0.205

Observations 4644.00 4577.00 4577.00 4577.00 4577.00


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Table 10: Examination of Risk Measures and Derivatives Use in Simultaneous Equations

The table reports in Panel A coefficients and corresponding p-values (in brackets) of OLS regressions of general derivatives use and control varia-bles on corporate r isk measures. Below the coefficients, information about the adjusted R2(AdjRSq) and the number of observations is reported.Std.Dev.* is the standardized standard deviation of local currency stock returns. Beta, Net-FX-Exposure, Net-IR-Exposure and Net-CP-Exposureare the coefficients of a regression of market index returns, exchange rate changes, short-term interest rate changes and the commodity price chang-es, respectively, on stock returns. Regressions with exchange rate, interest rate and commodity price exposures use the absolute value of the coeffi-

cient as dependent variable. Panel B shows regression coefficients, their marginal effects and p-values (in brackets) from LOGIT regressions of therelation between the likelihood of general derivatives use, firm-specific and country-specific proxies of incentives for hedging, proxies of exposure,and control variables. Marginal effects (MarEff) are calculated as the change in the probability of using derivatives that comes from a change in theexogenous variable of interest from (mean - 0.5 StdDev.) to (mean + 0.5 StdDev.), where all other variables are evaluated at the mean. R-Square isthe generalized coefficient of determination proposed by Cox and Snell (1989, pp. 208 -209). The estimation is based on a simultaneous equationapproach.

Panel A: OLS Results



Derivatives -0.065 [0.01] -0.163 [0.00] -0.435 [0.00] -0.019 [0.00] -0.042 [0.00]


Foreign Debt 0.092 [0.00] 0.021 [0.20] -0.011 [0.63] 0.002 [0.57] 0.009 [0.03]

Leverage 0.084 [0.19] -0.238 [0.00] 0.421 [0.00] 0.006 [0.38] 0.037 [0.00]

Logsize -0.068 [0.00] 0.178 [0.00] 0.176 [0.00] 0.007 [0.00] 0.016 [0.00]

NumIndSeg -0.033 [0.00] -0.006 [0.08] -0.003 [0.53] 0.001 [0.35] 0.000 [0.54]

Dividend -0.634 [0.00] -0.186 [0.00] -0.047 [0.02] -0.034 [0.00] -0.027 [0.00]

LogEXIM/GDP -0.015 [0.28] -0.015 [0.06] 0.018 [0.05] -0.005 [0.00] -0.003 [0.05]

IR-Country -0.118 [0.00] -0.056 [0.00] 0.282 [0.00] 0.019 [0.00] 0.023 [0.00]

ICR-Political -0.004 [0.01] 0.002 [0.06] 0.006 [0.00] 0.002 [0.00] 0.002 [0.00]

Intercept 0.856 [0.00] 0.161 [0.11] 0.004 [0.97] -0.077 [0.00] 0.005 [0.80]

Adjusted R2 0.209 0.191 0.253 0.222 0.121

Observations 6213.000 6017.000 6017.000 6017.000 6017.000

(continued)


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40

Table 10: Examination of Risk Measures and Derivatives Use in Simultaneous Equations (continued)

Panel B: Derivatives Use (Logit) Results


Variable Coef MarEff pvalue Coef MarEff pvalue Coef MarEff pvalue Coef MarEff pvalue Coef MarEff pvalue

Std. Dev.* -1.619 -0.150 [0.00]

Beta -1.719 -0.077 [0.00]

Net-FX-Exposure -6.066 -0.334 [0.00]

Net-IR-Exposure -33.650 -0.343 [0.00]

Net-CP-Exposure -142.17 -0.807 [0.00]

Coverage (3y) -0.029 -0.034 [0.00] -0.015 -0.017 [0.02] -0.023 -0.027 [0.00] -0.020 -0.024 [0.00] -0.014 -0.016 [0.05]

Quick Ratio -0.090 -0.037 [0.00] -0.047 -0.019 [0.01] -0.089 -0.037 [0.00] -0.071 -0.029 [0.00] -0.089 -0.036 [0.00]

Logassets 0.323 0.116 [0.00] 0.629 0.224 [0.00] 0.397 0.142 [0.00] 0.394 0.141 [0.00] 0.076 0.027 [0.01]

Dividend -0.558 -0.062 [0.00] 0.082 0.009 [0.37] -1.424 -0.158 [0.00] -1.120 -0.125 [0.00] -7.076 -0.662 [0.00]

GrossProfitMargin (3 0.448 0.026 [0.00] 0.539 0.031 [0.00] 0.489 0.028 [0.00] 0.398 0.023 [0.00] 0.461 0.026 [0.00]

Income Tax Credit 0.554 0.020 [0.01] 0.585 0.021 [0.01] 0.670 0.024 [0.00] 0.736 0.026 [0.00] 0.782 0.027 [0.00]

MB*Leverage 0.121 0.019 [0.01] 0.087 0.014 [0.06] 0.131 0.021 [0.01] 0.063 0.010 [0.18] 0.019 0.003 [0.70]

MultShareClass 0.486 0.037 [0.00] 0.483 0.037 [0.00] 0.583 0.044 [0.00] 0.653 0.050 [0.00] 0.715 0.053 [0.00]

Stock Options 0.066 0.006 [0.40] 0.143 0.013 [0.07] 0.415 0.036 [0.00] 0.399 0.035 [0.00] 0.976 0.084 [0.00]

PctMktCap 2.352 0.062 [0

sb speculation blind 02102012

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