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Journal of Multinational Financial Management

10 (2000) 161–184

The choice of hedging techniques and thecharacteristics of UK industrial firms

Nathan Lael Joseph *Manchester School of Accounting and Finance, Uni6ersity of Manchester, Manchester M13 9PL, UK

Received 8 August 1998; accepted 15 April 1999

Abstract

This study presents the empirical results for the relationship between the use of hedgingtechniques and the characteristics of UK multinational enterprises (MNEs). All the firms inthe sample hedge foreign exchange (FX) exposure. The results indicate that UK firms focuson a very narrow set of hedging techniques. They make much greater use of derivatives thaninternal hedging techniques. The degree of utilisation of both internal and external tech-niques depends on the type of exposure that is hedged. Furthermore, the characteristics ofthe firms appear to explain the choice of hedging technique but the use of certain hedgingtechniques appears to be associated with increases in the variability of some accountingmeasures. This adverse impact of hedging has not been emphasised in the finance literature.The results imply that firms need to ensure that the appropriate techniques are used to hedgeexposures. © 2000 Elsevier Science B.V. All rights reserved.

JEL classification: F23; F30; G10

Keywords: Multinational enterprises; Foreign exchange exposure; Hedging techniques

www.elsevier.com/locate/econbase

1. Introduction

Most theoretical studies that seek to explain why industrial firms hedge exposurefocus on differences in the financial characteristics of users and non-users ofhedging techniques1. The empirical work which seeks to test the theoretical predic-

* Tel.: +44-161-2754029.E-mail address: [email protected] (N.L. Joseph)1 For a review of the literature see Levi and Sercu (1991), Nance et al. (1993) and Joseph and Hewins

(1997).

1042-444X/00/$ - see front matter © 2000 Elsevier Science B.V. All rights reserved.

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N.L. Joseph / J. of Multi. Fin. Manag. 10 (2000) 161–184162

tions takes a similar focus. However, the findings for certain hypothesised rela-tionships are often weak in both univariate and multivariate statistical tests (seeDolde, 1993; Nance et al., 1993). One possible explanation for the weak empiri-cal results of certain theoretical predictions relates to research design. For exam-ple, to identify US industrial firms as hedgers (users) and non-hedgers(non-users), both Nance et al. (1993) and Dolde (1995) used a questionnairesurvey which required respondents to indicate whether or not they use one (ormore) of four currency derivatives, i.e. forward, futures, swap and/or optioncontracts. In contrast, Berkman and Bradbury (1996) choose to categorise thefirms in their study in terms of the hedging information contained in theiraudited financial reports (see also Francis and Stephan, 1993; Geczy et al.,1997). Since firms are only required to disclose exposure information if suchinformation is material, this latter approach may not fully capture the hedgingactivities of firms. However, both approaches seem restrictive since firms use awide range of internal and external techniques (including derivatives) to hedgeforeign exchange (FX) and interest rate exposures (see Stanley and Block, 1980;Khoury and Chan, 1988). Furthermore, some firms may not hedge simply be-cause they have no exposure while others may not hedge or partially hedgedepending on their perception about FX rate behaviour and/or their confidencein using derivatives (see Dolde, 1993). These considerations therefore have im-portant implications for the empirical results of prior studies.

This study seeks to provide additional insights into the hedging behaviour ofUK firms by focusing on: (i) the degree of utilisation of a broad set of hedgingtechniques; (ii) the maturity structures of those hedging techniques; and (iii) thesources or types of exposures that are hedged. Those aspects are examinedbecause firms are known to make use of a wide range of techniques whenhedging exposure and to exercise substantial flexibility in hedging decisions (seeHakkarainen et al., 1998). Although newer financial innovations can reduce thedemand for traditional types of hedging techniques (see Tufano, 1995), empiricalevidence indicates that firms are not very receptive to the newer and morecomplex types of derivatives. This is because firms are concerned about thebanks’ commitment to those products and their ability to provide real solutionsto exposure problems (see Fairlamb, 1988; Glaum and Belk, 1992). Furthermore,managers can always adjust their hedging decisions to reflect their expectationsof changes in financial prices. Thus, if the forward rate is a biased predictor,managers can alter their hedging strategies to accommodate this effect. Here, apartial or no hedge or fully hedged strategy can be optimal for both transactionand economic exposures (see Berg and Moore, 1991; Schooley and White, 1995).Since firms tend to place more emphasis on transaction exposure than on eco-nomic and translation exposures (Khoury and Chan, 1988; Joseph and Hewins,1991), their use of hedging techniques may reflect the types of exposures theyhedge.

An examination of a broad set of hedging techniques is also warranted sincein certain situations, the use of some techniques can give rise to adverse

N.L. Joseph / J. of Multi. Fin. Manag. 10 (2000) 161–184 163

effects2. For example, the use of both forward and futures contracts to hedgetranslation exposure can give rise to economic (cash flow) gains/losses which arenot off-set by losses/gains from the underlying exposure. Giddy and Dufey (1995)(p. 51) also show that FX ‘‘…options are not ideal hedging instruments forcorporations’’ since the gains/losses which arise from their use are not linearlyrelated to changes in the value of the currency, thereby, increasing the variability ofthe firm’s real cash flow. But forward contracts can only hedge economic exposureoptimally if managerial decisions regarding inputs and outputs are fixed; otherwise,FX options may be more appropriate (see Ware and Winter, 1988). In the absenceof default, the use of forward contracts to hedge transaction exposure does notresult in any gain or loss. However, both (long-term) economic and translationexposures tend to have maturities which exceed those of FX forward, futures andoption contracts (see also Neuberger, 1996) such that a mis-match of the cash flowsfrom the derivatives and the gain/loss from the underlying exposures will arise.Further, because of basis risk, a one-to-one hedge ratio can increase the variabilityof the firm’s cash flow if short-dated futures contracts are used to hedge (see Melloand Parsons, 1995). Firms can also hedge with internal techniques, such as, leadsand lags which do not give rise to the maturity problems of external techniques. Inthis case, the impact on the financial measures would depend on the hedgingeffectiveness of the internal techniques that are used.

Finally, Glaum and Belk (1992) also examined the use of hedging techniques of17 UK firms but they did not link the degree of usage to the characteristics of theirfirms. This present study focuses on a much larger sample of UK firms across abroader set of hedging techniques. The degree of utilisation is also linked to thecharacteristics of the firms.

The remaining sections of this study are as follows: Section 2 describes thetheoretical framework and the research methodology. The empirical measures arealso described and the hypotheses are formulated in that section. Section 3 presentsthe empirical results. The results are summarised and their implications are evalu-ated in the Section 4.

2. Background

2.1. Theoretical framework for the use of hedging techniques

To construct the theoretical framework for this study, we rely on existing workwhich suggests that firms hedge to reduce: (i) the agency problem (Bessembinder,1991); (ii) effective corporate taxes (Smith and Stulz, 1985); (iii) risk aversion

2 The recent case of Metallgesellschaft (see Financial Times, 16th November 1994) arguable, illustratesthe inappropriate use of futures and swap contracts to hedge economic exposure and the associatedadverse effects of their use on leverage and liquidity. In theory, the FX futures price is a biased predictorof the realised spot price. Under risk neutrality, the amount of bias depends on the covariance betweenthe reinvestment rate premium and the realised spot rate. Under risk aversion, the amount of the biasdepends on three premia terms. (see Tucker, 1991, pp. 165–166).


among managers and other contracting parties (Stulz, 1984); (iv) the probability offinancial distress (Smith and Stulz, 1985), and (v) the adverse information contentof earnings (DeMarzo and Duffie, 1995). The theoretical explanations identifythose incentives for hedging which are likely to benefit contracting parties. How-ever, hedging might not benefit all parties equally and therefore the hedgingstrategies of firms will vary (see e.g. Tufano, 1996). In theory, shareholders canimplement terms of compensation which limit both the incentive to hedge and thechoice of hedging technique3.

2.2. Sources of data

To obtain measures of the degree of utilisation of internal and external hedgingtechniques, a questionnaire survey was mailed to either the finance director or thecorporate treasurer4 of UK (industrial) multinational enterprises (MNEs) duringOctober 1994. Two hundred and ten firms were targeted within the top 300category of The Times 1000: 1994 (hereafter The Times) companies. The MNEswere all quoted on the London International Stock Exchange. A total of 109responses were obtained, of which 75 were satisfactorily completed (11 are anony-mous). The response rate (35.71%) compares favourable with those of other relatedstudies (see Nance et al., 1993). The firms in our sample are typically large. Their5-year average sales value (sample size, N=64) to 1994 is £2 795 671 million(US$4 673 803 million). Also, 76.56% of the firms are quoted in The Times top 200category. On average, the firms hedged between 61 and 70% of their globalexposure (N=68) and they generated between 41 and 50% of their total sales(N=74) overseas. In addition to the firms’ total sales, other financial data wasobtained for the non-anonymous firms from the Datastream. This data set spansfive financial year-ends to 1994 for most of the firms.

2.2.1. Internationalisation measuresA firm’s degree of internationalisation can affect the extent to which it uses

hedging techniques (see Mathur, 1985). Since firms appear to initially use internaltechniques to hedge exposure (see Hakkarainen, et al., 1998), a positive relationshipis expected between the measures of internationalisation and the degree of utilisa-

3 Recent evidence indicates that institutional investors are attempting to monitor and control theoperations of firms. Gaved (1997) reports that UK institutional investors can instigate change when thefirm’s performance is not consistent with their expectations. Smith (1996) also provides evidence on thesuccess of US institutional investors — the California Public Employees’ Retirement System(CaLPERS) — who were able to ensure that targeted firms adopt specific performance-relatedresolutions.

4 The degree of utilisation was requested for each type of exposure. To save space, the hedgingtechniques and the types of exposures are not specifically defined here. McRae and Walker (1980)provide useful definitions of some of the techniques and how they can be used for hedging. Also, thisstudy adopts the standard definitions of exposures that are found in the finance literature (see McRaeand Walker, 1980). A copy of the questionnaire survey as well as the statistical results that are not fullypresented can be obtained from the author.


tion of internal techniques. In contrast, a negative relationship is expected betweenthe rate of utilisation of external techniques and the internationalisation measuressince the greater use of internal techniques implies less use of external techniques.To measure the degree of internationalisation,5 the following measures are used: (i)the number of foreign countries in which the group operates (NCOUNT); (ii) thenumber of foreign subsidiaries within the group (NSUBS); (iii) the percentage ofthe groups’ total sales that is generated overseas (PERSALE); and (iv) the percent-age of the groups’ global exposure that is hedged (PERHEDGE). These measuresalso proxy for the effects of the firm’s size and scale economies on the choice of thehedging technique used (see Shirreff, 1994).

2.2.2. Financial measuresSmith and Stulz (1985) suggest that hedging can reduce the potential for financial

distress by reducing the variability of certain financial measures. But the choice ofthe hedging instrument can increase the variability of the firms’ cash flow. Firmsthat make greater use of: (i) foreign currency borrowing/lending; (ii) cross-currencyinterest rate swaps; and (iii) foreign currency swaps are expected to exhibit greatervariability on cash flow, liquidity and leverage. The cash flow and liquiditymeasures are the coefficient of variation of: (i) gross cash flow to market value(GCASHMV); (ii) cash and marketable securities to market value (CASHMV); (iii)quick asset ratio (QAR); and (iv) working capital ratio (WCR). The leveragemeasures are the coefficient of variation of: (i) interest charges to operating andnon-operating income (IGEAR); (ii) preference capital and total borrowing to totalcapital employed (CGEAR); (iii) total borrowing to ordinary shareholders’ equityplus reserves (TLBOR), and (iv) long-term borrowing to market value (LT-BORMV). Since foreign currency borrowing can increase the probability of finan-cial distress, firms with greater variability in their leverage measures are expected tomake greater use of internal techniques.

Hedging can also mitigate the under-investment problem by reducing both thecost of external funds and the firm’s dependence on external finance (Froot et al.,1993). In the absence of hedging, the greater the growth opportunities of the firmthe more it will depend on external finance. Thus firms are more likely to hedge thegreater their growth options (Lessard, 1991). Since the returns from growth optionsare likely to have long leads, firms with more variability in their growth options areexpected to make greater use of internal hedging techniques thereby reducing theadverse cash flow impacts of derivatives and the associated default risk. This

5 The measures of internationalisation were provide by our respondents as part of their responses tothe same questionnaire survey. The aggregate index of the degree of internationalisation of Sullivan(1994) was not applied because there were insufficient variables to implement it (see Ramaswamy et al.,1996, for a critique). However, PERSALE and NSUBS which are used in the study are contained inSullivan’s index in one form or another. Also, no information was requested about operational hedgessuch as, currency sourcing of inputs/outputs and the relocation of operating facilities. Both anecdotalevidence (see Lewent and Kearney, 1990; Dolde, 1993) and current thinking (see Glaum, 1990) suggestthat the transaction costs that are associated with those hedging strategies are likely to outweigh thepotential benefits of the hedge.


relationship is tested by using the coefficient of variation of: (i) sales to market value(SALESMV); (ii) the firm’s book value to its market value (BOOKMV); and (iii)dividend yield. Here, a negative relationship between the degree of utilisation ofderivatives and our growth option measures is expected. Following DeMarzo andDuffie (1995), high quality managers are more likely to hedge. But the choice ofhedging technique and the type of exposure that is hedged can reflect managers’perceptions of the economic effects of hedging. Titman (1992) also shows that a firmthat has an optimistic outlook can use interest rate swaps to benefit from borrowingand the expected cost of financial distress will not increase. Thus a positiverelationship is predicted between the use of cross-currency interest rate swaps andvariability of the leverage measures.

The tax treatment of both the exposure and the hedging technique can haveimportant implications for the firm’s hedging strategy (see Kramer et al., 1993). UnderUK tax laws, the use of derivatives to hedge translation exposure may give rise tocash flow gains which are taxable and losses which are not tax allowable (see Buckley,1992). To avoid the adverse impacts of asymmetry in taxation, firms are likely to placemore emphasis on internal techniques when hedging translation exposure. The useof forward contracts to hedge the transaction exposure emanating from re6enuetransactions, results in taxable/tax allowable gains and losses in the UK. All thoseimpacts will in turn affect the level of profitability. Assuming that the tax credits canbe utilised, a lower degree of variability is expected on the tax measures for firmsthat use forward contracts to hedge transaction exposure. The tax and profitabilitymeasures are the coefficient of variation of: (i) tax charge on profit/loss to pre-taxprofit/loss (TAXRATIO); (ii) tax charge on profit /loss to market value (TAXMV);(iii) operating profit to sales (OPM); and (iv) trading profit to sales (TPM).

The terms of managers’ and employees’ compensation plans can also impact onthe choice of hedging technique (see Smith, 1993). Managers will use those derivatives,e.g. FX options, which increase the volatility of the firm’s stock price if a large partof their compensation is in the form of stock options. Following Smith and Stulz(1985) a positive relationship is expected between both managers’ and employees’wealth and the extent to which the firms use derivatives, particularly when hedgingeconomic and translation exposures. The measures of wealth are the coefficient ofvariation of: (i) directors’ remuneration to market value (DIRECMV); (ii) employees’remuneration to market value (EMPMV); and (iii) BOOKMV. The predictions arefurther summarised in Appendix A.

3. Empirical results

3.1. Some general results

Since the firms are large, one would expect them to make much greater use ofinternal hedging techniques than external techniques. Further, much greater use ofinternal techniques would be expected because of the transaction cost, biased pricing,default risk, etc. (see Riehl and Rodriguez, 1977) that are associated with

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Table 1Summary statistics for the extent to which hedging techniques are used by the firmsa

Hedging techniques Transaction exposure Economic exposure Translation exposure

Percentage rating Percentage ratingPercentage rating

Mean 1 3 N Mean 1 3NN Mean 1 3

Panel A. The degree of utilisation of internal hedging techniques by type of exposure6.9 63 1.13 87.3 0.0 67 1.06 94.0 0.01.49(a) Leads and lags 58.372

1.43 71.4 14.3(b) Matching inflows and outflows with respect to timing of settlement 6772 1.25 82.1 7.52.10 22.2 31.9 631.41 68.3 9.5 67 1.31 79.163 10.423.6 41.7(c) Inter-company netting of foreign receipts and payments 72 2.18

6273 1.40 69.4 9.7 66 1.14 89.4 3.02.11 24.7 35.6(d) Domestic currency invoicing1.31 79.0 9.7 66 1.03 98.5 1.5(e) Adjustment clause in sales contract 73 1.67 46.6 13.7 621.47 63.3 10.0 64 1.67 53.160 20.311.3(f) Asset/liability management 71 1.54 57.7

(g) Transfer pricing agreements 1.1370 88.3 1.7 65 1.03 96.9 0.01.41 61.4 2.9 60

Panel B. The degree of utilisation of external hedging techniques by type of exposure33.3 68 1.79 50.0 29.4 71 2.38 21.1 59.272(a) Foreign currency borrowing/lending 1.94 38.9

1.75 47.8 22.4 68 1.53 61.867 14.774(b) Forward exchange contracts 82.44.12.786974 1.33 73.9 7.2 69 1.22 81.2 2.91.84 35.1 18.9(c) Foreign exchange options

1.01 98.5 0.0 68 1.03 91.1(d) Foreign exchange futures 0.073 1.07 94.5 1.4 671.03 97.1 0.0 – – –68 –74(e) Factoring bills receivable 2.782.41.20

6974 1.42 69.6 11.6 70 1.46 68.6 14.31.34 75.7 9.5(f) Cross-currency interest rate swaps(g) Foreign currency swaps 1.4674 65.2 11.6 70 1.64 57.1 21.41.65 54.1 18.9 69

1.09 91.3 0.0 69 1.07 94.269 1.478.4 1.4(h) European currency unit 74 1.236974 1.01 98.6 0.0 69 1.00 100.0 0.01.01 98.6 0.0(i) Special drawing rights

(j) Other currency blocs 1.0774 94.2 1.4 69 1.04 95.7 0.01.20 85.1 5.4 691.17 88.4 5.8 69 1.10 92.8 2.969(k) Government exchange risk guarantee, e.g. ECGD 74 1.36 68.9 5.4

a The summary statistics relate to the scores obtained on a 3-point scale where 1 denotes not used; 2 denotes occasionally used; and 3 denotes frequently used.


external techniques. Table 1 shows that the degree of utilisation of internal andexternal hedging techniques varies with the type of exposure6. However, there ispreliminary evidence to suggest that the firms place more emphasis on certain externaltechniques — a finding which has been noted elsewhere (see McRae and Walker,1980, p. 101). In particular, Panel A shows that inter-company netting and domesticcurrency invoicing (in that order) are the most commonly used techniques whenhedging transaction exposure. Matching inflows/outflows and asset/liability manage-ment are respectively the most commonly used techniques when hedging economicand translation exposures. Evidence from Khoury and Chan (1988) shows thatmatching is the most popular internal technique used by US firms. Here, US firmsconsider matching to be the most flexible and ‘self-reliant’ way to hedge.

Panel B also shows that the firms use a limited set of external techniques to hedgethe exposures. The FX forward contract is the most commonly used hedgingtechnique. This finding is similar for US firms (see Phillips, 1995). Forward contractsare mainly used to hedge transaction exposure. While foreign currency borrowing/lending is the most commonly used technique when hedging both economic andtranslation exposures, it is the second most commonly used technique when hedgingtransaction exposure. The use of foreign currency borrowing/lending may reflect thedesire of the firms to reduce the amount of investment that is abroad (see Belk andGlaum, 1990), but the degree of usage is stronger for translation exposure than foreconomic exposure. Cross-currency interest rate swaps and foreign currency swapsare not commonly use by the firms. This is consistent with the findings of Glaumand Belk (1992). The utilisation rates of both FX options and futures are low forall types of exposures but FX options tend to be more widely used than FX futures(see also Glaum and Belk, 1992; Phillips, 1995). The low utilisation of FX futuresmay be due to the effects of daily resettlement which can adversely affect the liquidityof firms.

In general, external techniques appear to play a much more important role inhedging decisions then internal techniques. As the firms are large, scale economiesin the use of external techniques and the availability of skilled treasury personnel maycontribute to their greater use (see Geczy et al., 1997). However, the firms do notappear to be very selective in their use of the techniques when hedging different typesof exposures.

3.1.1. Hedging exposures with similar internal techniquesTo test for a link between the utilisation rates of internal techniques, a x2 test was

applied7. The test was applied to determine whether or not: (i) the firms are selective

6 The 3-point scale identified the degree of usage as: 1=not used; 2=occasionally used; and,3= frequently used. The occasional use of hedging techniques may be associated with partial hedgingand/or hedging strategies which reflect expected changes in the behaviour of the financial markets. Sincethe aim is to capture the degree of utilisation, it would appear that the use of a larger point scale wouldnot have altered the results (see Lehmann and Hulbert, 1972).

7 The results where the statistical test yields a value whose associated probability under the nullhypothesis is 5% or less (P-value50.05) are reported. This cut-off point is applied throughout this studyunless explicitly stated otherwise.


in their use of the hedging techniques; and (ii) certain techniques are perceived tohave special attributes such that they would only be used to hedge specificexposures. The null hypothesis that there is no difference in the utilisation rate ofmatching when the firms hedge transaction and economic exposures is rejected(x4

2=13.996; P-value=0.007). The contingency table suggests that the firms makegreater use of matching when hedging transaction exposure compared with eco-nomic exposure. For example, 32 of the 45 firms (71.11%) that do not use matchingto hedge economic exposure, also use matching (occasionally and frequently) tohedge transaction exposure. Using the Cramer test statistic, C (see Siegel andCastellan, 1988) the association appears to be moderate (C=0.333). The nullhypothesis of no difference in the degree of utilisation of matching when hedgingeconomic and translation exposures is also rejected (x4

2=33.668; C=0.521; P-value=0.000). Here, 50 of the firms do not use matching to hedge translationexposure and 90.00% of those firms do not hedge economic exposure with thistechnique either. However, the firms have a much stronger preference for inter-company netting when hedging transaction exposure compared with economicexposure (overallx4

2=13.910; C=0.332; P-value=0.008). While 43 of the firms donot use inter-company netting to hedge economic exposure, 72.10% of those firmshedge transaction exposure with inter-company netting. Similar inference can bemade for the use of asset/liability management and leads and lags across exposures,but in general, the firms appear to prefer to use those techniques to hedgetransaction exposure.

3.1.2. Hedging exposures with similar external techniquesExternal techniques such as currency swaps and foreign currency borrowing/lend-

ing, allow firms to borrow more cheaply than would otherwise have been possible.Those techniques also enable firms to reduce or eliminate the amount of theirforeign investments (see Glaum and Belk, 1992). Cross-currency interest rate swapsalso share those attributes. In general, if those techniques enable firms to reduce theamount of their foreign investment, one would expect their use to be more stronglyassociated with economic and translation exposures. The x2 test provided somesupport for this prediction. The null hypothesis of no difference in the degree ofutilisation of foreign currency borrowing/lending when hedging economic andtranslation exposures is rejected (overallx4

2=16.904; C=0.355; P-value=0.002).Of the 39 firms that hedge translation exposure with foreign currency borrowing/lending, 35.89% of them frequently hedge economic exposure with the sametechnique. However, more than half of those firms (21 out of 39) do not use foreigncurrency borrowing/lending to hedge economic exposure. Thus it seems that thefirms prefer to hedge translation exposure with foreign currency borrowing/lending.In contrast, the firms make much greater use of currency swaps when hedgingeconomic exposure compared with transaction exposure (overall x4

2=20.680; C=0.387; P-value=0.001) but most of the firms do not use cross-currency interest rateto hedge their exposures.

If managers believe that FX options provide a genuine hedge (but see, Giddy andDufey, 1995), they are more likely to use them to hedge economic and translation


exposures. The null hypothesis of no difference in the extent to which the firms useFX options to hedge economic and translation exposures cannot be rejected.However, the null hypothesis can be rejected for transaction and translationexposures (x4

2=10.224; C=0.272; P-value=0.037). Here, FX options are primar-ily used to hedge transaction exposure. Up to 37 of the 56 firms that do not use FXoptions to hedge translation exposure use the derivative to hedge transactionexposure.

3.1.3. Hedging transaction exposure with different techniquesSince it is more difficult to match the maturity of derivatives with those of the

underlying economic and translation exposures, firms would be expected to makemuch greater use of internal techniques. Although, the preliminary evidence sug-gests that the firms place a stronger emphasis on external techniques, the hypothe-sised relationships are directly tested here. The null hypothesis of no difference inthe extent to which the firms use foreign currency borrowing/lending and asset/li-ability management when hedging transaction exposure is easily rejected (x4

2=13.109; C of 0.308; P-value=0.011). Thirty-nine firms do not use asset/liabilitymanagement to hedge transaction exposure and more than half of those (56.41%)do not use foreign currency borrowing/lending either. Indeed, the contingency tablesuggests that there is a stronger preference for foreign currency borrowing/lending.The null hypothesis is also rejected for the extent to which forward contracts areused compared with matching and domestic currency invoicing8.

The results are similar for the extent to which the firms use FX options comparedwith other internal techniques9.

8 The test statistics for the extent to which FX contracts and the relevant internal hedging techniquesare used when hedging transaction exposure are as follows:

Use of FX forward contractsP-valueCx4

2Use of:12.361Matching 0.293 0.015

0.0350.26610.317Domestic currency invoicing

9 The test statistics for the extent to which FX options and the relevant internal hedging techniquesare used when hedging transaction exposure are as follows:

Use of FX optionsP-valueCUse of: x4

2

0.00614.488 0.317Leads and lags13.858Domestic currency invoicing 0.308 0.008

Transfer pricing arrangements 0.0020.35017.159


3.1.4. Hedging economic exposure with different techniquesSome significant results were also found for the degree of utilisation of certain

techniques when hedging economic exposure. For example, the null hypothesis forthe degree of utilisation of foreign currency borrowing/lending and asset/liabilitymanagement is rejected (x4

2=24.199; C=0.453; P-value=0.000). Most of the 29firms (86.21%) that do not use foreign currency borrowing/lending use asset/liabilitymanagement. The results are also significant for the relationship between the degreeof utilisation of: (i) FX options and certain internal techniques; and (ii) foreigncurrency swaps and certain internal techniques10.

The relationships are weak to moderate and reflect the stronger emphasis onexternal techniques.

3.1.5. Hedging translation exposure with different techniquesEvidence from Collier et al. (1990) indicates that some treasury managers of both

UK and US firms are concerned about the adverse impacts of translation risk onleverage, distributable reserves and the overall balance sheet value. One implicationof this finding is that managerial attitudes towards translation exposure would vary,particularly when firms are faced with hedging techniques which increase thevariability of those measures. The results indicate a moderate association betweenthe degree of utilisation of foreign currency borrowing/lending and asset/liabilitymanagement (x4

2=15.525; C=0.348, P-value=0.004). The firms generally makemuch greater use of foreign currency borrowing/lending to hedge translationexposure. For example, of the 34 non-users of asset/liability management, up to61.77% of them are occasional (17.65%) and frequent (44.12%) users of foreigncurrency borrowing/lending. Most firms that use forward contracts also use match-

10 The test statistics for the extent to which FX options and the relevant internal hedging techniquesare used when hedging economic exposure are as follows:

Use of FX optionsx4

2Use of: C P-value10.027 0.004Matching inflows/outflows 0.28221.674Inter-company netting 0.415 0.000

0.046Invoicing in domestic currency 0.2799.66711.695 0.312Transfer pricing arrangements 0.020

For economic exposure, the test statistics for the extent to which foreign currency swaps and the relevantinternal hedging techniques are used are as follows:

Use of foreign currency swapsx4

2 CUse of: P-value25.457Inter-company netting 0.449 0.000

Domestic currency invoicing 0.02511.186 0.30014.817 0.351 0.005Asset/liability management


ing, inter-company netting and domestic currency invoicing11 although the empha-sis on forward contracts is not strong. Similarly, the null hypothesis that there is nodifference in the degree of utilisation of foreign currency swaps and asset/liabilitymanagement is rejected (x4

2= 12.275; C=0.312; P-value=0.015). In general, thefirms place a much weaker emphasis on translation exposure.

3.2. Bi6ariate test of hedging techniques and firms’ characteristics

In this sub-section, the extent to which cross-sectional variation in the character-istics of the firms can explain the degree of utilisation of the hedging techniques isassessed. The data for the characteristics of the firms is not normally distributed.Therefore, the distribution-free Kruskal–Wallis statistic has been used. To illustratethe testing procedure, the test statistics associated with the use of FX options andthe characteristics of the 64 non-anonymous firms are shown for the case oftransaction exposure (see Table 2). If the degree of utilisation of FX options isassociated with the financial measures, one would expect to observe differences inthe variability of the financial measures. The table shows, for example, thatfrequent users of FX options exhibit less variability on dividend yield compared toboth occasional and non-users; the associated Kruskal–Wallis test statistic issignificant (P-value=0.015). Thus the null hypothesis that the k samples are fromidentical populations with the similar medians can be rejected and it can be inferredthat the degree of usage is associated with differences in the variability of themeasure.

3.2.1. Internal hedging techniques and firms’ characteristicsIn most cases, the degree of utilisation of internal techniques is positively related

with the measures of internationalisation. In the case of transaction exposure, theKruskal–Wallis statistic indicated that both occasional and frequent users ofmatching, domestic currency invoicing and transfer pricing tend to be larger interms of both NCOUNT and NSUBS. As expected, a higher degree of internation-alisation appears to be associated with an increase in the use of internal techniques.Similarly, firms that use inter-company netting are larger in terms of both measures,but in addition, the magnitude of PERSALE is also larger. As expected, firms thatuse asset/liability management to hedge transaction exposure exhibit less variabilityon QAR. However, PERHEDGE and the leverage measures were not found to be

11 The test statistics for the extent to FX forward contracts and the relevant internal hedgingtechniques are used when hedging translation exposure are as

Use of FX forward contractsP-valueCx4

2Use of:0.29711.267 0.024Matching inflows/outflows

14.980Inter-company netting 0.342 0.005Domestic currency invoicing 0.0250.29711.106

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Table 2The characteristics of the firms conditioned on the degree of utilisation of foreign exchange (FX) options when hedging transaction exposurea

Test statistic Combined sampleFX options not used FX options occasionally used FX options frequently used

S.D. N Mean S.D. K–W P-value N MeanMean S.D.N Mean S.D. N

1. Coefficient of 6ariation of financial measures20 30.703 20.340 13 44.244 25.781 5.827 0.054 61 32.304 20.35826.784 12.952SALESMV 28

20.888 13 35.646 24.416 2.493 0.287 6130.095 28.97220 19.165BOOKMV 28.9.70823.06029.11722. 13.894 20 27.199 16.017 8.416 0.015 58 29.567 19.62132.047 25.750 16Dividend

21 20.200 13.720 13 35.271 24.773 4.508 0.105 63 23.016 18.96819.317 18.977OPM 2914.517 13 21.059 15.109 2.603 0.272 6314.497 16.76918.226 15.90129TPM 21 17.250

28.80220 16.696 28 27.078 11.845 0.565 0.754 61 26.939 13.61724.242 9.384 28GCASHMV18.280 13 39.969 21.817 1.671 0.434 61CASHMV 45.31420 22.68251.367 28.036 28 43.47210.322 13 14.865 11.833 0.991 0.609 6316.583 16.28021 10.428QAR 2910.11216.739

13.14821 9.447 13 11.733 9.026 1.478 0.477 63 13.046 8.83413.720 8.154 29WCR17.561 13 39.226CGEAR 41.90721 2.760 0.252 63 25.334 25.62224.529 19.517 29 19.90619.565 13 47.102 39.092 0.867 0.647 6334.537 39.15829 26.108IGEAR 21 40.627 24.20833.631 13 56.070 43.403 2.268 0.322 61LTBORMV 44.72920 33.46144.282 24.786 28 39.78433.872 13 50.682 46.518 3.346 0.188 6329.034 38.421TLBOR 48.0022963.10743.79221

9.56221 8.234 13 −42.116 197.284 1.089 0.580 63 −0.961 89.8959.986 14.704 29TAXRATIO24.001 13 44.005 25.503 9.302 0.010 6139.953 35.85020. 22.237TAXMV 2811.54724.803

30.26721 17.575 13 41.375 28.508 4.022 0.134 62 30.836 20.89425.072 17.869 28.DIRECMV28 31.666 21.041 13 40.627 19.813 4.073 0.131 61 32.396 18.860EMPMV 28.05820 13.386

2. Internationalisation measures117.719 14 63.286 87.848 2.36845.400 0.306NSUBS 73 56.178 101.19525 85.444 34 61.176

34 20.147 16.500 14 36.000 27.016 8.188 0.017 73 22.164 20.72517.160NCOUNT 19.3752526.982PERSALE 1426 46.429 33.479 5.423 0.066 73 42.671 30.55131.731 31.239 33 49.96726.549 13 62.692 25.545 1.440 0.487 6755.690 60.07529 25.768PERHEDGE 25 63.800 25.219

a The summary statistics are conditioned on the degree of usage of foreign exchange options and are also given for the firms combined. The variable representing firmcharacteristics are described in the appendix. S.D. is the standard deviation. K–W is the Kruskal–Wallis test statistic which tests the null hypothesis that the characteristics of thefirms conditioned on the degree of usage have the same median. The P-values50.05 are show in bold. For both PERSALE and PERHEDGE, respondents were asked to tickone percentage value or range of values from [0], [1–10], [11–20]…[91–100%]. None of the firms recorded a score of 0%. The statistics reported are based on the mid-point of thoseranges. This table is for illustrative purposes only.


significantly associated with any hedging technique. The results for translation andeconomic exposure are insignificant and reflect the low priorities the firms give tothose exposures.

3.2.2. External hedging techniques and firms’ characteristicsThe Kruskal–Wallis test statistic also indicated that the use of external tech-

niques varies with the characteristics of the firms. One interesting result is thatoccasional users of currency lending/borrowing tend to hedge a much largerpercentage of PERHEDGE than frequent users, when transaction exposure ishedged. If firms partially hedge on the expectation of benefiting from FX trading(see Hakkarainen et al., 1998), it is possible that the percentage of exposure that ishedged as well as the degree of utilisation of certain techniques will vary. Firms thatfrequently use FX forwards to hedge transaction exposure tend to exhibit muchlower variability on CASHMV compared to occasional users. This result isexpected since the mis-match of the cash flows from the instrument and theunderlying exposure would not occur, in the absence of default. The degree ofutilisation of FX forwards is also positively related to NCOUNT. Furthermore, thedegree of utilisation of FX options is positively related to dividend yield, TAXMVand NCOUNT as well as the length of time since the firms had established theirformal corporate hedging policies. Thus it appears that greater experience inexposure management (see also Dolde, 1993) increases the firms’ confidence inusing more complex techniques. Firms that are occasional and frequent users offactoring tend to hedge a larger percentage of PERSALE. They are also larger interms of NSUBS. All those considerations apply to transaction exposure.

The long-term nature of economic exposure presents special problems for firmssuch that those hedging techniques which reduce the amount of foreign investmentsare likely to be preferred. Furthermore, the economic exposure arising from thelong leads of growth options is likely to re-enforce the incentive to partially hedge.In general, the results indicate that both occasional and frequent users of foreigncurrency borrowing/lending exhibit lower variability on certain growth optionmeasures, i.e. BOOKMV and SALESMV. The degree of variability on thosemeasures is lowest for frequent users. Further, the degree of utilisation is positivelyrelated to PERSALE. It should be noted that firms that hedge more than 81% oftheir global exposure exhibit greater variability on SALESMV, BOOKMV anddividend yield while firms that hedge less than 40% of global exposure exhibit theleast variability on those measures. But the statistical results are not significant(P-values]0.060). However, there is the potential for the degree of utilisation toimpact on the percentage of exposure that is hedged. Frequent users of FX optionstend to exhibit less variability on the growth option measures as well asGCASHMV, DIRECMV, EMPMV, while occasional users exhibit the highest levelof variability on those measures. Extending Smith’s (1993) argument, it had beensuggested that the terms of managerial compensation would provide an incentivefor using FX options, forwards and futures particularly when hedging economicand translation exposures. The results suggest that the incentive to increase thefirms’ volatility is greater only for occasional users of FX options.


Finally, the results indicate that firms that use foreign currency borrowing/lend-ing to hedge translation exposure exhibit less variability on OPM, IGEAR, andLTBORMV. The lower variability of the leverage measures is unexpected. How-ever, firms that hedge less than 40% of their global exposure exhibit less variabilityon both CGEAR and IGEAR while those that hedge between 41 and 80% of theirglobal exposure exhibit more variability on those measures (P-value50.025). Thusit appears that the extent to which exposure is hedged impacts on the hypothesisedrelationship. The use of foreign currency borrowing/lending when hedging transla-tion exposure is also positively related with NSUBS and PERSALE. While occa-sional users of foreign currency swaps exhibit greater variability on both OPM andTAXMV, frequent users exhibit less variability on OPM. These contrasting resultsmay be due to the inflexibility inherent in the use of foreign currency swapagreements.

3.3. Multi6ariate test of hedging techniques and firms’ characteristics

Bivariate tests tend to be weak since they do not allow for interactions among theexplanatory variables. To further assess the choice of hedging techniques, a logisticregression was applied. The dependent variable of the logistic regression is deter-mined by using the ratings that represent the degree of usage. Here, the score of 1(not used) is coded as 0 and, the scores of 2 and 3 (occasionally and frequentlyused) are coded as 1. The existence of missing explanatory variables and theanonymous responses result in an overall sample size of 54 firms. To minimise thepotential problems of small sample size, we present the results for the modelswhere: (i) at least 20% of the firms can be allocated to either group 0 or 1, a priori;(ii) each empirical model outperforms a naive proportional chance model (see Joyand Tollefson, 1975); and (iii) each model’s xn

2 statistic is significant at the 50.05level. No evidence was found that suspiciously large regression residuals had anadverse effect on the estimated coefficients.

3.3.1. Internal hedging techniquesPanel A of Table 3 shows that the explanatory variables exhibit some discrimina-

tory power for the degree of utilisation of internal hedging techniques. Only thecoefficients associated with transaction exposure are significant. As expected, theuse of internal techniques is positively related with measures of internationalisation.The use of leads and lags is positively related with the coefficients of bothSALESMV and NCOUNT but those coefficients are marginally significant. Thecoefficient value of 0.138 for SALESMV means that as its variability increases, allelse held constant, the likelihood that the firm will use leads and lags to hedgingtransaction exposure increases. In this case, each unit increase in the variability ofSALESMV increases the log odds by a factor of 1.148; that is, e0.138. EMPMVmakes the greatest contribution to the explanatory power of the model and thecoefficient of PERHEDGE is always positive. Both EMPMV and DIRECMV havenegative coefficients for leads and lags, and transfer pricing, respectively (P-value50.05).

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Table 3Logistic regression for the use of internal and external hedging techniques and the characteristics of the firmsa

Transaction exposure

Domestic cur-Coeff Coeff RLeads and lags R Transfer pricing Coeff Rrency invoicing

Panel A: Internal hedging techniquesCASHMV −0.182 SALESMV −0.065**−0.186−0.148** −0.251−0.038*EMPMV

(0.020)(0.070) (0.027)LTBORMV 0.042***SALESMV 0.377 TAXMV 0.106***0.152 0.2980.138*

(0.018) (0.014) (0.040)−0.055** −0.249 PERHEDGE 0.024*DIRECMV0.120 0.1220.027*NCOUNT(0.025) (0.014)(0.015)

NCOUNT 0.071***Constant 0.400 Constant −1.254−0.402(1.182)(0.023)(0.754)

0.382PERHEDGE 0.050***(0.019)−4.179***Constant(1.516)

Diagnostics StatisticsDiagnostics Statistics Diagnostics Statistics

Model’s x32 12.909***Model’s x5

2 24.552***10.348**Model’s x32

% classified 88.980***% classified 70.370*** % classified 75.930***S. Residuals 88.890***−0.022S. ResidualsS. Residuals −0.051N1, N2 −0.015N1, N2 30, 24 N1, N2 32, 22

12.42

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Table 3 (Continued)

Transaction exposure

Coeff Foreign***Currency Cross-currencyCoeff R Factoring Coeff RR Coeff Rexchangeborrowing/ interest rate

swapsoptionslending

Panel B: External hedging techniques−0.187** −0.244 DIRECMV −0.120**GCASHMV −0.308−0.321 TLBORTPM −0.039**−0.480*** −0.223(0.076) (0.017)(0.053)(0.163)

TAXMV 0.181***OPM 0.307 EMPMV 0.127***0.210*** 0.388 IGEAR 0.049**0.268 0.200(0.024)(0.048)(0.051) (0.062)

CASHMV −0.200 NSUBS 0.013***−0.256−0.096*** 0.413CASHMV NCOUNT −0.035*−0.047** −0.137(0.020)(0.022)(0.016) (0.005)

BOOKMV 0.095** 0.118 PERSALE −0.036** −0.234CASH 0.084*** 0.176(0.042) (0.055) (0.016)

SALES 0.187*** 0.266(0.071)

Constant −3.389***PERHEDGE 0.2270.068**(0.029) (1.038)

ConstantConstant −1.242 (0.934)1.246 Constant −0.163 (1.245)(1.106)

Diagnostic Statistics DiagnosticDiagnostic StatisticsStatisticsStatisticsDiagnostic

Model’s x32 19.075***Model’s x6

2 33.527*** Model’s x42 12.344**Model’sx4

2 25.314***% classified 87.040*** % classified 79.630**79.63***% classified 87.040*** % classifiedS. Residuals 0.007 S. Residuals −0.099S. Residuals −0.121 S. Residuals 0.003N1, N2 43, 11 N1, N2 41, 13N1, N2 18, 36 18, 36N1, N2

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Table 3 (Continued)

Economic exposure Translation exposure

Coeff R Currency bor-Coeff Coeff RCurrency bor- Foreign cur-Foreign ex-R Coeff Rrowing/lending rowing/lendingchange options rency swaps

0.254 0.188 OPM −0.092**0.118**GCASHMV −0.363OPM TPM 0.338***0.046** 0.339(0.047) (0.125)0.023) (0.035)

SALESMV 0.049**Dividend yield 0.251 CGEAR −0.041**−0.093 −0.382 OPM −0.340***−0.061 −0.374(0.018) (0.117)(0.021)(0.038)

IGEAR −0.249 TAXMV 0.059**−0.120−0.065** 0.282EMPMV TAXRATIO 0.179**−0.053** 0.305(0.038) (0.023) (0.027) (0.072)

Constant −1.601**Constant PERSALE 0.026* 0.149 NSUBS 0.151**1.049 0.219(0.015) (0.007)(0.714)(0.862)

PERHEDGE 0.038** 0.225 Constant −0.447(0.019) (0.619)

Constant −0.470(1.357)

Diagnostics StatisticsDiagnostics DiagnosticsStatistics StatisticsDiagnostics Statistics

Model’s x52 20.915*** Model’s x4

213.597*** 28.689***Model’s x326.108bModel’s x3

2

% classified 85.190***% classified 72.220a % classified 72.220***% classified 75.930***S. Residuals −0.016 S. Residuals −0.0550.047S. Residuals −0.017 S. ResidualsN1, N2 13, 41 N1, N2 28, 26N1, N2 23, 31 N1, N2 37, 17

a The explanatory variables are entered into/removed from the logistic regression using a stepwise procedure. The likelihood-ratio test is used for both entering (cut-off P-value50.05) and removing (cut-offP-value]0.10) the explanatory variables into/from the model. For this reason some coefficients are significant at the 10% level, which is considered to be marginal. The Wald statistic is used to test the nullhypothesis that each coefficient of the model is zero. The standard errors of the coefficients are in parentheses. R is the partial correlation between the dependent and independent variables. S. Residuals isthe average of the standardised residuals of the logistic regression model. For the ith case its residual is divided bypi(1−pi) where pi is the predicted value. The chi-square xn

2 statistic tests the null hypothesisthat all coefficients in the model (except the constant) are simultaneously zero against the alternative that at least one coefficient is non-zero. The percentage correctly classified is a measure of the classificatoryefficiency of the model. The level of significance indicates that the classificatory efficiency of the empirical model is superior to that of a naive proportional chance model (see, Joy and Tollefson, 1975). N1

indicates the number of firms in the sample that do not use the hedging techniques while N2 indicates the total number of occasional and frequent users. The results are presented where: (i) it was possibleto allocate at least 20% of the firms to group 0 or 1 a priori; (ii) the percentage correctly classified by the empirical model outperforms a proportional chance naive model (P-valueB0.05; one tailed); and(iii) each model’s xn

2 statistic is significant at the 5% level or less.* The test statistic is significant at ]5% but 510% level.** The test statistic is significant at ]1% but 55%.*** The test statistic is significant at 51% level.


3.3.2. External hedging techniquesThe results for the degree of utilisation of external hedging techniques are shown

in Panel B of Table 3. Here, the degree of utilisation of foreign currency borrowing/lending is associated with each type of exposure. The cash flow and profitabilitymeasures appear to explain the degree of utilisation, and in most cases, theircoefficients carry the expected sign. Notice that the coefficient for TAXMV ispositive implying that the use of FX options for hedging transaction exposure willincrease as its variability increases. For transaction exposure, PERSALE carries anunexpected negative sign for cross-currency interest rate swap, and is marginallysignificant (but positive) in the case of translation exposure. In general, thecharacteristics of the firms can explain the choice of hedging technique but theexplanatory power of the logistic regression is much stronger for the use of externaltechniques.

4. Summary and conclusions

This empirical study is concerned with the use of both internal and externalhedging techniques by large UK MNEs and the extent to which cross-sectionalvariation in the characteristics of those firms can explain the degree of usage.

The empirical results show that UK firms utilise a narrow set of techniques tohedge exposure. The firms place much more emphasis on currency derivatives thanon internal hedging techniques. This emphasis is not consistent with the approachthat is suggested in the academic literature (see McRae and Walker, 1980) and theimplications of prior empirical work (see Hakkarainen et al., 1998, p. 44). Also, thefirms place more emphasis on transaction exposure and economic exposure andmuch less on translation exposure. Those findings are informative since they showthat not all the traditional hedging techniques are utilised by the firms despite theproliferation of financial innovations in recent years (see Remolona, 1992–93). Oneimportant implication of the model of Breeden and Viswanathan (1990) is that likefinancial institutions, industrial firms are likely to make much greater use ofderivatives (than internal techniques) in order to indirectly communicate theirmanagerial ability to operate in the derivatives market.

The characteristics of the firms also have strong predictive power. In general, theempirical results indicate that the explanatory power of the characteristics of thefirms is stronger for the degree of utilisation of external techniques. It would appearthat previous empirical studies which focus on the usual set of derivatives to identifyhedgers and non-hedgers can capture some of the effects they seek to measure.However, an important feature of the results of this study is the finding of strongcross-sectional variation in the characteristics of firms that hedge. Indeed, it isshown that the degree of usage of certain techniques is associated with an increasein the variability of certain financial measures. Thus contrary to the general viewfound in the finance literature, hedging does not always decrease the variability ofthe firm’s value. To the author’s knowledge, apart from the implications forleverage in hedging decisions and the concerns raised by Giddy and Dufey (1995),


the issues which have been raised have not been explicitly addressed in theoreticaland empirical work. As the firms do not hedge fully, it is possible that part of theobserved variability reflects the effects of partial hedging. However, the maturitymis-match of exposures and derivatives will normally give rise to some degree ofvariability in financial measures.

Acknowledgements

The author would like to thank an anonymous referee of this Journal for his/herhelpful comments on a earlier version of this manuscript.

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Appendix A. The predicted signs and the characteristics of firms

Variable name Variable description Generalisation of the predicted signs by type of exposure

Internal techniques External techniques

Economic TranslationTransaction Economic Translation Transaction

1. Coefficient of 6ariation of financial measures−Total sales to market value. The market value of the ? − + ?−SALESMV

firm is the closing ordinary share price times the totalshares outstanding at the firm’s financial year-end

− + +−BOOKMV −Total assets less total liabilities less preference stock −outstanding at the year end to market valueDividend paid per share to price per share at the − − + +−Dividend yield −financial year end

− − + ?−OPM −Operating profit margin: operating profit to total sales+ +−−TPM −−Trading profit margin: trading profit to total sales

Gross cash flow to market value − + +− −GCASHMV −− + +−CASHMV −Cash, cash equivalents and marketable securities to −

market value−Quick asset ratio: total current assets less stock and − + +− −QAR

work-in-progress to total current liabilities−Working capital ratio: total current assets to total cur- − + +− −WCR

rent liabilities− + +− −−CGEAR Preference capital and total borrowing to total capital

employed− +IGEAR +Total interest charges to the sum of operating and − − −

non-operating income+ +−−Long term borrowing to market value − −LTBORMV

−Total borrowing to ordinary shareholders’ equity and − + +− −TLBORreservesTax charge on profit and loss to pre-tax profit ? ? +− −TAXRATIO −

? +?−TAXMV −−Tax charge on profit and loss to market value

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Appendix A. (continued)

Generalisation of the predicted signs by type of exposureVariable descriptionVariable name

External techniquesInternal techniques

Translation Transaction Economic TranslationTransaction Economic

− + +−DIRECMV −−Total of directors’ remuneration and pension fundcontributions to market valueTotal employees’ remuneration to market value − + +− −EMPMV −

Bsp=1/2\2. Internationalisation measures

− −+ ++Number of foreign subsidiaries within the groupNSUBS −− − −NCOUNT Number of foreign countries in which the subsidiaries + + +

of the group operate− −++ −+Percentage of group’s total sales generated overseasPERSALE

+ + − − −Percentage of the group’s global exposure that isPERHEDGE +hedged

The analysis is performed on the coefficient of variation of each financial measure. The coefficient of variation is an ideal (unit-free) measure since the useof certain hedging techniques can either increase or decrease the variability of financial measures. The coefficient of variation is computed for thenon-anonymous firms for 5 years to 1994 in most cases. The financial variables were obtained from Datastream while the internationalisation measures wereobtained from the questionnaire survey. The predicted signs for firms that use more of a technique can depend on the specific hedging technique. Thus thepredicted signs are generalised expectations only. Since one expects firms to initially use internal techniques to hedge, a positive relation is expected betweeninternationalisation measures and the use of internal techniques. The relation is expected to be negative for external techniques. The Kruskal–Wallis testis typically performed for the 64 non-anonymous firms. The presence of missing explanatory values for the non-anonymous firms restricts the total samplesize in the logistic regression to 54 firms.


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