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The Exchange-Rate Exposure of U.S. MultinationalsAuthor(s): Philippe JorionSource: The Journal of Business, Vol. 63, No. 3 (Jul., 1990), pp. 331-345Published by: The University of Chicago PressStable URL: http://www.jstor.org/stable/2353153 .

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Philippe JorionColumbiaUniversity

The Exchange-Rate Exposureof U.S. Multinationals*

It is widely believed that exchange rates affectthe value of the firm. Exchangeratesare a majorsource of uncertaintyfor multinationals, beingtypically four times as volatile as interest ratesand 10 times as volatile as inflation.1While therelationshipbetween inflation rates or interestrates and the value of the firm has been beenextensively analyzed,2it is astonishingthat theassociation between exchange rates and thevalue of the firm has not been subject to muchempiricalresearch.The purpose of this paper is to analyze theforeignexchange exposure of U.S. multination-als. Withoutpresuminganycausal link, exposurerepresentsthe sensitivity of the value of the firmto exchange rate randomness and can be mea-suredby the regression coefficient of the changein the value of the firm on the change in the ex-change rate.To date, a number of theoreticalpapershaveinvestigated the possible sources of exchange-

This articleexaminesthe exposureof U.S.multinationalso for-eign currencyrisk. Evi-dence is presented thatthe relationshipbe-tween stock returnsand exchangerates dif-fers systematicallyacross multinationals.Given these results, thestudy focuses on thedeterminants f ex-change-rateexposure.The comovementbe-tween stock returnsand the value of thedollar s found to bepositivelyrelated to thepercentageof foreignoperationsof U.S. mul-tinationals.

* Thanks are due to Michael Adler, Maurice Levi, RexThompson, Arthur Warga, and an anonymous referee forhelpful comments.1. Overthe period 1971-87, the annualized olatilityof thedollar/mark xchange-rate hange was 12%,againsta volatil-ity of 3% or the U.S. Treasurybill rate and 1.3% or the U.S.inflation.2. See, e.g., French, Ruback, and Schwert (1983), Flan-nery and James (1984), Bernard (1986), and Sweeney andWarga 1986).(Journal of Business, 1990, vol. 63, no. 3)? 1990by The University of Chicago.All rightsreserved.0021-9398/90/6303-0004$0150

331


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Exchange-Rate Exposure 333perfectly correlatedwith the exchange rate andan orthogonalcompo-nent does not imply a causal relationshipbetween exchange rates andstock prices. This is simply a statistical decompositioncomparable oothers used to studythe relationshipbetween the value of an asset andinflationrates, interest rates, and, for that matter,marketmovements.Clearly, the degree of association between endogenous variablessuch as stock prices and exchange rates depends on the nature of theshocks affecting the economy. Blanchardand Summers (1984), forexample, present a good summary of how various disturbancesarelikelyto affect these asset prices. Thus, exposure mayjust reveal, say,the simultaneousimpact of monetary factors on exchange rates andstock prices. To the extent that monetary shocks affect firmsdifferen-tially, cross-sectional variation could appear in the association be-tween stock prices and exchange rates, even for purely "domestic"firms. Some empirical evidence on this issue is presented in the nextsection.Foreign exchange exposure can generally be decomposed into theeffect of exchange-rate randomnesson (i) the value of net monetaryassets with fixed nominal payoffs6and on (ii) the value of real assetsheld by the firm. Abstracting from inflation uncertainty, short-termforeignmonetaryassets are, in general,fully exposedto exchange risk,whereas domestic monetary assets are not. This is usually called"translation xposure." Real assets, however, will be affectedin valueby exchange-rate movements, whatever their location. Thus purelydomestic firms,like utilities, may be affectedby exchange-ratemove-ments througheffects on aggregatedemand or on the cost of tradedinputs; domestic firms that sell goods competingwith importswill alsobe exposed to exchange-ratemovements. United Statesmultinationalsthat rely heavily on exports should see the value of their U.S. realassets unfavorablyaffectedby an appreciationof the U.S. dollar;con-versely, foreign real assets producing goods that are ultimatelyim-ported intothe United States shouldbenefitfrom anappreciation f thedollar. In addition, Dumas (1978) emphasized that exposure containsan "operational"element that accounts for the firm'sresponsivenessto exchange-rate changes. It could be argued, for instance, that theunique abilityof multinationalso shiftproduction romone countrytoanotheractually lessens their exchange-rateexposure. Finally, multi-nationalsmay actively adjust their transactionor balance sheet expo-sure by means of various covering instruments; hese hedgingactivi-ties, if known and impounded in stock prices, will reduce thecorrelationbetween stock prices and exchangerates.Whatemerges from the above is that the determinantsof exposureare quite complex, and that exposure may be difficult to identify. In

6. This class also includes contractual ash flows in the foreigncurrency.


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334 Journal of Business

spiteof this, U.S. multinationals xhibitsignificant ross-sectionaldif-ferences in their association with exchange rates, as will be shownbelow. This articlepresents a firstattemptat analyzingthe sources ofthese differencesin exposure. For example, one could analyze expo-sure due to monetaryassets withbalance sheet information oncerningforeign versus domestic nominal assets, as French, Ruback, andSchwert (1983) did when studyingexposureto inflationrisk. Unfortu-nately, such detailed accountingdata on internationaloperationsarenot readilyavailable, to my knowledge.Informationon foreignand domestic sales, however, is available ora numberof U.S. multinationals.These foreignsales figurescombineexports from the United States, both directand intragroup,and salesby foreign subsidiaries.To see how exposurecan be relatedto foreignoperations, consider, first, a monopolistic tradingfirm whose costsare incurred n dollarsbut whose sales receiptsaredeterminedby for-eignprices. All else equal,an unanticipatedoreigncurrencyapprecia-tion shouldincreaseprofitsand the value of the firm.7Moreprecisely,Levi (1983) shows that, with fixed marginalcosts, the change inexports dollarprofits af due to exchange rate changes can be writtenas dwrfIdS= -qwflS, where -q is the elasticity of foreign demand,whichmustbegreater hanone to ensurepositiveearnings.Assumenowthat the value of the firm V can be writtenas the discountedvalue of astream of constant total profits, which are the sum of foreign profitsand domestic profits rr= 1rrf + lrd. Focusing only on the exposure offoreign operations,the exchange-rateexposure of the firm is (dVIV)I(dSIS) = -qlTw/l. So, using the ratio of foreignsales to total sales as aproxy for the ratio of foreign profits to total profits, the exposureshould increase as the proportionof sales exportedincreases.

Consider next a foreign subsidiarywith revenues and costs princi-pallydenominated n the foreigncurrency.The dollarvalue of this sub-sidiaryshould(ceterisparibus) ncreaseas the foreigncurrencyappre-ciates because of a translation effect. Using the same notation asabove, the exchange-rateexposurecan be writtenas (dVIV)I(dSIS)=1flw. Again, this suggests a positive cross-sectionalrelationshipbe-tween currencyexposure and the degree of foreignoperations.

7. A caveat is in orderhere. Manyauthors,such as Shapiro 1975)and Cornell 1980),have suggested that exchange risk is really measured by deviationsfrom purchasingpowerparity.If thelaw of one priceholds, barring elativepricechanges,then exchange-rate movementsareexactly offset by pricemovements,and exchangeriskdisappears. nreality,however, largeand persistentdeviations rompurchasing owerparityhave beendocumented.The monthly volatilityof relativechanges in exchangerates is about 10times the volatilityin inflationrates, so that most of the movement n exchange ratescannotbe accounted or by inflation ates.Therefore, he correlation etween month-to-month changes in real exchange rates is extremely high, and similarresults will beobtainedusingnominalor real exchange rates.


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Exchange-Rate Exposure 335II. The Exposure of U.S. MultinationalsEstimates of the exposure coefficient can be obtained from the time-series regression,

Rit = hoi + PliRst + Eit, t = 1, ... ., T. 1whereRitis the rate of returnon the ith company's commonstock andRst s the rateof change n a trade-weighted xchange rate, measuredasthe dollarprice of the foreign currency.Thus a positive value for Rstindicatesa dollar depreciation.This specification s appropriate f changes in stock prices and ex-change rates are essentially unanticipated. If, for example, the ex-pected rate of return on the common stock and the expected rate ofchangein the exchange rate are constant over time, thenthe intercept13oiwill reflect these expected values, and the slope coefficient willcorrectly measure the effect of unanticipatedchanges in exchangerates on stock returns.Another possibility would be to take the for-ward premiumon the exchangerate as the expected rateof change inthe exchange rate. However, a growing numberof empiricalstudiesindicate that the forward rate is a biased predictor of the future spotrate and does not even outperformthe contemporaneousspot rate.8Furthermore,since the percentageof actualvariation n the spot rateexplained by the forwardpremium s quite small,about 5% n sample,it can safely be concludedthat most of the actual change in the spotrate is unanticipated.The trade-weightedexchange rate is derived from the weights inthe MultilateralExchange Rate Model (MERM) computed by theInternationalMonetary Fund. These weights are based on 1977trade flows and price elasticities and are reported in the Appendix.9End-of-periodexchange rates were constructedfrom MERM weightsandend-of-periodbilateralnominalrates. Collapsingall exchangeratesinto one multilateral xchange rate results in a parsimonious epresen-tation that is convenient to use. In addition,it avoids the problem ofmulticollinearity hat arises because many cross-exchange rates arefixed relative to each other, or nearly so.10Changes in the value of the firm,Rit, are measured by the rate ofreturnon the companies' common stocks as provided by the Univer-sity of Chicago Center for Research in Security Prices (CRSP)database. The sampleperiodstarts n January1971,which is the year whenexchange rates started to float, and ends in December 1987, which

8. See, e.g., Bilson (1981).9. Theprocedure or computing he MERMweights s detailed n Artus andMcGuirk(1981).10. For example, the correlation between movements in dollar/markand dollar/French francexchange rates was 0.88 from 1971to 1987.


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Exchange-Rate Exposure 337TABLE 1 Distribution of Exposure Coefficients 082of U.S. Multinationals

Rit= Ii + 02iRst + P3Rmt + nitPeriod (Monthly Returns)

1971-87 1971-'75 1976-80 1981-87Minimum - 1.45* - 2.93* - 1.83* - 1.94*(-3.10) (-2.07) (-2.59) (-2.63)First quartile -.27 -.61 -.38 -.25(-1.17) (-.7Q) (-.73) (-.93)Median -.07 -.17 .05 -.06(- .25) (.17) (- .18) (-.20)Third quartile .12 .22 .27 .13(.49) (.18) (.84) (.50)Maximum .56* 1.72* .52* 1.17*(1.99) (2.35) (3.02) (2.56)Cross-sectional mean -.093 -.234 - .079 -.078Cross-sectional SD .307 .712 .493 .353Significance, no. of firms with signifi-cant exposure at 5% level 15/287 5/287 16/287 15/287Stability, no. of firms with same signfor exposure:1971-75 and 1976-80 ... 190/287 190/287 ...1976-80 and 1981-87 ... ... 159/287 159/287All three subperiods ... 109/287 109/287 109/287Autocorrelation,no. of firmswith sig-nificant Durbin-Watson statisticat 5% level 0/287 2/287 5/287 0/287Value-weighted market exposure .158 .712* .084 .022(1.01) (1.98) (.30) (.10)Equal-weightedmarketexposure .058 .493 .081 -.101(.30) (.96) (.23) (-.43)

NOTE.-t-statisticsare in parentheses.The exposurecoefficient s computedby regressing hestockmonthly eturnsRi,on the rateof change na trade-weightedxchangerateRs,andonthe stockmarket eturnRing. Themarket xposure s derived roma univariate egression nRs,. Totalsampleconsists of 287 nonoilcompanies.* Significant at the 5% level.

for the cross-sectionaldistribution.Table 1providesa partialexplana-tion for the rarity of studies on the relation between the stock marketand the foreignexchangemarket. Most exposure coefficientsare smallrelative to their standarderror, except in a few cases. Of course, thisdoes not necessarily mean that the true exposure coefficients are allzero but ratherthat exposure is impreciselyestimated.The coefficients also appear to change over time. Only 190 firmshave anexposurewith the same sign inthe firstandsecondsubperiods,and the numberdrops to 159 when comparingthe second and thirdsubperiods.The bottom partof the table reportsthe exposure (PI)ofthe stock market. From one subperiod o another, the exposure of thevalue-weightedmarketchanges from0.71 to 0.08 to 0.02, with the firstcoefficient significant.This is consistent with the results of Obstfeld


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338 Journal of Business(1985), who finds evidence that monetary developmentshave domi-natedthe behavior of the dollar from 1975 to 1981,while goods-mar-ket developmentshave gained in importance since. Monetaryexpan-sion, for instance, raises the nominalprices of stocks and currenciessimultaneously, which translates into a positive exposure coeffi-cient.12But given the large standarderrors, tests of stabilitycannot rejectthe hypothesis of constant coefficients. These conclusions are rein-forced when standarderrorsare correctedfor heteroscedasticitysincethe correction tends to increase standarderrors.13 Otherwise theseregressions are well specified in terms of seriallyuncorrelatedresid-uals: a very smallproportionof the regressions yields significantDur-bin-Watsonstatistics.In view of the previous results, it seems important o test whetherthese exposure coefficients are all equal or even zero. Equal coef-ficientscould also reveal the endogenousnatureof the relationshipbe-tween stock prices and exchange rates, which, in this case, would beunrelated to foreign operations.To performsuch a test, equation (2)should be runjointly for all firms in the sample, accountingfor thecontemporaneouscorrelationsin the error terms. The model shouldthereforebe estimatedby generalized east squares (GLS). Since thisprocedurerequires hatthe numberof firmsbe smaller hanthe numberof monthly observations,40 firms were selected at a time.Thus, 40 multinationalswere chosen so as to maximize the disper-sion in the percentage of foreign operationsmeasure. The availablesampleof 287 firms was classifiedin orderof increasing oreign opera-tions, and40 firmswere chosen by samplingat regular ntervals. Table2 reports strong rejections of the hypotheses that the exposurecoefficients of these multinationalsare all equal or all zero. Theserejections can be traced to the use of a system of equations, whichyields morepowerfultests thanthe previousunivariateregressions, bypooling informationacross series. Additionally,the exposure coeffi-cients are also found to be significantlyunstable across the three sub-periods. To confirm these findings, the analysis is repeatedwith 40portfolios, sortedby foreign operations. Sorting nto portfoliosshouldyield less variablereturns,andthusmore precise parameter stimates.The drawbackof the sortingprocedure s that information s lost by av-eragingout the exposure coefficients withinportfolios. In any event,table 2 shows that similarresults are achieved with the portfoliosofmultinationals.Then, in order to distinguish he extent to which comovementsunre-

12. Huizingaand Mishkin 1986)also find markeddifferences n the behaviorof realinterestratesbefore and after 1980.13. For instance, the t-statisticfor the exposureof the value-weightedmarket n thefirst subperiodsdropsfrom 1.98 to 1.43 whencorrecting or heteroscedasticity.


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Exchange-Rate Exposure 339TABLE 2 Hypothesis Tests on Exposure Coefficients 082, January 1971-December1987

F-Test(P-Value)Average No. Significant HypothesisSample Exposure at 5% Level Equal 132 Zero 132 Stable 132

40 multinationalswithmost dispersion nforeign operations -.049 3/40 1.8599** 1.8997** 1.5892**(.0009) (.0005) (.0007)40 portfolioswithmost dispersion nforeign operations -.088 6/40 1.7834** 1.7454** 1.6254**(.002) (.003) (.0004)40 firmswith lowestpercentageof for-eign operations -.120 0/40 1.1816 1.2910 1.3086(.203) (.104) (.034)40 largestdomesticfirmswith no re-portedforeignop-erations - .151 2/40 1.2676 1.3286 1.2101(.123) (.081) (.099)

40 firmswith highestpercentageof for-eign operations .073 2/40 1.5787 1.7400** 1.2395(.012) (.003) (.073)14foreignfirms .563 9/14 2.7818** 5.6477** 1.6408(.0006) (.0001) (.018)

NOTE.-Systemestimatedby generalized east squares.The sampleconsists of 287 nonoilfirms,with foreign operationsreported n Value Line, except for the foreignfirms and the "domestic"firms,whicharethe largestFortune500firmswithno reported oreignoperations.The stability estjointlytests the equalityof exposurecoefficientsover the subperiods1971-75,1976-80,1981-87.** Significant t the 1% evel.

lated to exchange-rateexposure may give nonzero coefficients, thetests were repeated for firms with little or no foreign involvement.Forty companies were selected from the sample of 287with the lowestreportedforeignoperations,ranging rom0 to 6% of total sales. As isapparent from table 2, the cross-sectional variability in exposurecoefficients is much lower than before: the hypothesis of equalcoefficientsnow cannot be rejected at the 5% confidence evel. Giventhat multinationalsare among the largest U.S. firms, an alternativeexperiment was designed to control for firmsize. A sample was col-lected with the 40 largest companies among the Fortune 500 withoutany reportedforeignoperations. These domestic firmsbest match theValue Line sample of multinationals n terms of size and also covermany different industries. As explained above, differing exposurecoefficientsmay conceivably arise because of differingcross-sectional


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340 Journal of Businesseffects of economywide disturbances.But it appearsfrom table 2 thatthe dispersion in the exposure coefficients of domestic firms is quitelow, and that their exposure is not significantlydifferentfrom zero.Finally, table 2 reports tests on the exposure of the 40 firms in theValue Line samplewith the highest percentageof foreign operations,as well as 14foreignfirms isted on the New York Stock Exchange. Asexpected, these firms display a high and significantexposure to ex-change-ratemovements, with the results particularly trongfor foreignfirms. This section therefore has shown that cross-sectional variationsin exposure coefficients are identifiableandquite markedacross multi-nationalfirms, which indicates that an analysisof the determinantsofexchange-rateexposure is warranted.III. The Determinants f Exchange-RateExposureThe purpose of this section is to determine whether exchange-rateexposure is related to the degree of foreign involvement. The hy-pothesis can be cast in terms of the cross-sectional regression,

Eli = yo + yFi + ui, i = 1, ... ., Ng (3)whereFi is the ratio of foreign to total sales. The value of Yomay differfrom zero if the returnon the purelydomestic componentof the U.S.stock market s correlatedwith changes in exchangerates. Therefore,the constantincorporates he effect of the correlationbetween marketmovementsand the exchange rate.A major difficulty arises in this two-step estimation procedure ifthe errorsin (1) are correlatedacross companies,as is likely to be thecase. In thatsituation, ordinary east squares(OLS)estimationof (1) isfully efficient but the first-step estimates P'li are not independentacross equations. Generally,their covariancematrixcan be written asl[lt(Rst - Rs)2] 1, where fl is the covariance matrix of the contem-poraneouserrors t. As Thompson 1985)points out, theproblemarisesbecause all the betas are estimatedover the same sample period. Thiscorrelationacross betas impartsnonzero correlationsacross the errorterms in (3), which violates the classical OLS assumptions.The stan-darderrorof i' in (3) is then biasedandtests of significanceare difficultto interpret. To illustrate, figure 1 plots the exposure coefficientsagainstthe percentageof foreign operations or the sampleof multina-tionals. Whereas the slope coefficient is clearly positive, statisticalsignificance s difficult o assess. Thisproblem s too often overlookedin empiricalstudies.14

14. For instance, the high t-statistics oundby Agmonand Lessard (1977)and Fatemi(1984) are probablyseriously biased upward.These authorsregressthe estimatedsys-tematic risk coefficients against a degree of international perationsmeasurewithoutrecognizing hat the betas are correlatedacross firms.


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342 Journal of BusinessTABLE 3 Exchange Rate Exposure and Foreign Operations (40 Portfolios Sortedby Foreign Operations)

Rit = ri + r2iRst+ r3iRmt+ qits i = 1. 40,where 12i= Yo+ YiFiYo Y1

Estimation period,1971-87 -.105 .30*(- 1.86) (2.33)Subperiods:1971-75 -.213* .57*(-1.96) (2.22)1976-80 .014 - .01(.26) (-.48)1981-87 -.191** .41**(-4.65) (2.87)NOTE.-t-statistics romgeneralizedeast squaresestimationare in parentheses;R.,,R,,, Rmtaredefinedas the returnon portfolio , the rate of change n the exchangerate,andthe returnon themarket, espectively;Fi is the ratioof foreignsalesto total sales. The 40portfoliosaresorted norderof foreignoperations, rom a sampleof 287 nonoilfirms.* Significant t the 5% evel.** Significant t the 1% evel.

For reasonsnoted below, these portfoliosexcludeoil firms. With GLSestimation,the cross-sectionalstandarderrorsareasymptoticallycon-sistent, even if there remainssubstantialcorrelationacross portfoliosafter adjustingfor the market. The drawback of this method is thatgroupingwill reduce the variability in the independentvariable andthus lead to less powerful tests. In addition, since the matrix ft isunknown and has to be estimated, the improvementdepends on thetrade-offbetween estimation error and the departure rom the OLSassumption.Regression results for equation (5) are presented in table 3. Theestimated slope coefficient is positive and significant in two sub-periods, and for the whole period 1971-87. Thus, in spite of potentialmeasurementandinstabilityproblems, this evidence is consistent withthe hypothesis that exchange-rateexposure is positively related to theforeign sales variable.The previous resultswere achieved with 40 portfolios of 287 nonoilfirms.Oil companies were specificallyexcludedfrom the above analy-sis because it appeared that the multinationalswith the most foreignoperationsbelongedto the oil industry,where outputprices are com-monly set in dollars all over the world:foreign sales account for over53%of the sales of the U.S. oil industry, while the computer ndustryrankssecond, with a 41% oreignsales ratio. It is thereforereasonableto expect that U.S. oil companies are not so sensitive to fluctuations nthe value of the dollar, in which case the structuralrelationship(4)could yield differentcoefficients for oil and nonoil firms.


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Exchange-Rate Exposure 343TABLE 4 Exchange Rate Exposure and Foreign Operations: Oil versus NonoilFirms, January 1971-December 1987

Rit = 30i+ r2iRst + 3iRmt+ 1its =1. 58, where02i = _Ywy1N Fi for 40 nonoil portfolios, 2i = 'Y + 'y Fi for 18 oil firmsFirms Yo Y1i40 nonoil portfolios -.146** .33**(-3.11) (3.00)18 oil firms .082 .03(.70) (.21)

Joint test of equal coefficients:X2 = 5.99*P-value = .05

NOTE.-t-statistics from generalized least squares estimation are in parentheses. The parameters-Yo,Yiare different across the 40 nonoil portfolios and the 18 oil firms and are estimated jointly acrossthe 58 assets. The chi-square statistic tests the hypothesis that the coefficients (yo, -yl) are equal fornonoil portfolios and oil firms.* Significant at the 5% level.** Significant at the 1% level.

This hypothesis was tested by estimating (5) jointly for 40 nonoilportfolios and 18 oil firms, with results reported in table 4. The slopecoefficients are clearly different: 0.33 for nonoil portfolios, and 0.03 foroil firms, the latter not significant. This indicates that the exchange-rateexposure of oil firms is only weakly related to foreign operations. Inaddition, the joint hypothesis of equal coefficients (yo,yl) across oil andnonoil firms is rejected at the 5% level. These results justify excludingoil firms from the sample of U.S. multinationals for the analysis of thedeterminants of exchange-rate exposure.IV. ConclusionsThis article has identified significant cross-sectional differences in therelationship between the value of U.S. multinationals and the exchangerate. This association, called exposure, was found to be positively andreliably correlated with the degree of foreign involvement. Conversely,exposure without foreign operations does not appear to differ acrossdomestic firms.These results have direct implications for asset-pricing tests. Giventhat the value of the dollar appears to be one factor that differentiallyaffects U.S. stocks, exchange-rate exposure could theoretically bepriced in an arbitrage pricing theory framework. If so, firms couldaffect their cost of capital by currency hedging. However, there issome preliminary evidence, presented in Jorion (1988), that exchange-rate risk appears to be diversifiable.


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Exchange-Rate Exposure 345Flannery,Mark,andJames, Christopher. 984.The effect of interestrate changeson thecommon stock returns of financial nstitutions.Journal of Finance 39 (September):

1141-53.French, Kenneth; Ruback, Richard;and Schwert, William. 1983. Effect of nominalcontractingon stock returns.Journal of Political Economy91 (January): 0-96.Heckerman,Donald. 1972.The exchangerisk of foreignoperations.Journalof Business44 (January): 2-48.Hodder, James. 1982. Exposure to exchange rate movements.Journalof InternationalEconomics 13 (November): 375-86.Huizinga,John, and Mishkin, Frederick.1986. Monetarypolicy regimeshifts and theunusual behavior of real interest rates. Carnegie-Rochester Conference in Public Pol-icy 24 (Spring):231-74.Jacquillat, Bertrand, and Solnik, Bruno. 1978. Multinationalsare poor tools fordiversification. Journal of Portfolio Management 5 (Winter): 8-12.Jorion, Philippe. 1988. The pricingof exchangerate risk in the stock market.Workingpaper.New York: ColumbiaUniversity.Levi, Maurice. 1983. International Finance: Financial Management and the Interna-tional Economy, New York: McGraw-Hill.Obstfeld,Maurice. 1985.Floatingexchangerates:Experienceandprospects.BrookingsPaper on Economic Activity, no. 2, pp. 369-443.Senchak, Andrew,and Beedles, William:1980.Is indirect nternational iversificationdesirable? Journal of Portfolio Management 6 (Winter): 49-57.Shapiro,Alan. 1975.Exchangeratechanges, inflation,and the value of the multinationalcorporation.Journal of Finance 30 (May):485-502.Shapiro,Alan. 1977. Definingexchange risk.Journalof Business50 (January):37-39.Sweeney, Richard,andWarga,Arthur.1986.Thepricingof interest-rate isk: Evidence

fromthe stock market.Journal of Finance 51 (June):393-410.Thompson, Rex. 1985. Conditioningthe return-generating rocess on firm-specificevents: A discussion of events study method. Journal of Financial and QuantitativeAnalysis 20 (June): 151-68.Wihlborg,Clas. 1980.Currency xposure-taxonomy andtheory.In RichardM. LevichandClasG. Wihlborg eds.), ExchangeRisk and Exposure.Lexington,Mass.: Heath.

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