! ! ! ! ! University!of!Amsterdam! Amsterdam!Business!School! ! ! Master!in!International!Finance! ! ! Master!Thesis! ! ! Exchange!rate!exposure!and!derivatives!use!of!firms!in!financial!distress! ! ! (Michèle)!Chantal!Hage! ! ! 10415203! ! ! September!2014! ! ! Dr.!Jeroen!Ligterink! ! ! !
Table&of&Contents&
! 1.! Introduction!...!2! 2.! Literature!review!...!4! 3.! Research!methodology!...!10! 4.! Data!and!descriptive!statistics!...!13! 5.! Results!...!20! 6.! Robustness!checks!...!31! 7.! Conclusion!...!35! 8.! Appendix!...!38! 9.! References!...!40! ! ! !&
1. Introduction&
!This! thesis! combines! three! main! topics,! being! financial! distress,! exchange! rate! exposure!and!riskWshifting!theory.!Financial!distress!is!the!state!a!firm!is!in!before!it! goes!into!bankruptcy.!Not!all!firms!in!financial!distress!end!up!filing!for!bankruptcy,! but!a!firm!in!financial!distress!is!more!likely!to!do!so.!In!general,!a!firm!in!financial! distress! has! difficulty! paying! its! liabilities.! It! becomes! increasingly! difficult! to! gain! access! to! loans! and! customers! will! prefer! to! choose! a! different! supplier! (Wruck,! 1990),!causing!further!financial!problems.!This!thesis!does!not!take!financial!distress! in!itself!into!account,!but!the!likelihood!a!firm!will!go!into!financial!distress.!Proven! models,! such! as! the! ZWscore! model! by! Altman! (1968),! will! be! used! to! predict! the! probability!of!financial!distress!for!the!firms!under!study.! ! The!second!topic!to!be!addressed!is!exchange!rate!exposure.!Exchange!rate!exposure! is!the!level!of!risk!firms!face!when!exchange!rates!fluctuate.!This!exposure!generally! arises!when!(part!of)!a!product’s!costs!and/or!revenues!are!in!a!different!currency! than!the!main!currency!of!the!company.!Exposures!can!be!hedged!in!various!ways,! with!derivatives!being!the!most!frequently!used!(Bartram,!Brown!and!Minton!2010).! Foreign! exchange! derivatives! come! in! the! forms! of! forwards,! options! and! swaps,! with!forwards!being!the!most!widely!used.!Forwards!are!contracts!that!convey!the! right!to!purchase!or!sell!a!certain!amount!of!foreign!currency!for!a!specified!price!on! a!specified!future!date!(Jarrow!and!Oldfield,!1981).!They!are!used!to!hedge!foreign! exchange!exposures!as!they!eliminate!the!risk!that!the!exchange!rate!will!fluctuate!in! an!unfavorable!way.!However,!derivatives!are!not!always!used!in!a!perfect!manner! and!or!sometimes!used!to!speculate!(Allayannis!and!Ofek!2001).!This!thesis!uses!the! terms!exchange!rate!exposure!and!exposure!to!exchange!rate!risk!interchangeably.! !
The! final! topic! is! riskWshifting! theory.! This! topic! is! relatively! new,! and! not! much! research! has! been! done! to! date.! The! main! research! has! been! done! by! Eisdorfer! (2008,!2009,!2010)!and!covers!empirical!evidence!of!riskWshifting!theory!for!firms!in! financial!distress.!RiskWshifting!theory!states!that!firms!in!financial!distress,!where!the! incentives!of!managers!and!shareholders!are!aligned,!tend!to!take!on!more!risk.!The!
reasoning! is! that! the! shareholders! will! benefit! if! the! risk! pays! off,! whereas! the! debtholders! will! pay! if! the! extra! risk! causes! further! financial! distress! (Jensen! and! Meckling,!1976).!!
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Putting!these!topics!together!leads!to!the!hypothesis!for!this!thesis.!If!riskWshifting! theory! is! true,! than! firms! in! financial! distress! would! have! higher! foreign! exchange! exposures,! as! they! use! derivatives! imperfectly! and! thus! increase! their! risk.! The! research! question! addressed! in! this! thesis! is:! Does! exchange! rate! exposure! (after! using!derivatives)!increase!for!firms!with!a!high!probability!of!financial!distress?!The! main! contribution! of! this! thesis! will! be! in! the! field! of! riskWshifting! theory! and! specifically! to! gather! evidence! to! support! this! theory.! Taking! it! a! step! further,! no! research!has!been!done!to!date!on!foreign!exchange!exposure!risk!in!combination! with!the!riskWshifting!theory.!Additional!research!is!also!done!for!a!subsample!on!the! types!of!derivatives!used!by!the!firms!in!the!sample!and!the!notional!values!of!these! derivatives!for!firms!with!high!versus!low!probabilities!of!financial!distress.!! ! Data!is!collected!for!U.S.!firms!over!the!time!period!2004!to!2013.!First,!the!relevant! data! is! used! to! compute! ZWscores,! which! are! a! measure! for! probability! of! financial! distress.! Next! the! foreign! exchange! exposures! are! determined! for! each! firm! on! a! yearly!basis.!Finally,!a!regression!is!run!with!the!exposure!as!dependent!variable!and! the!ZWscore,!derivative!usage!and!others!as!independent!variables.!Variations!of!this! regression!are!run!to!determine!differences!based!on!ZWscores!and!exposures.!
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This! thesis! is! divided! into! six! sections.! The! first! section! introduces! the! topic! by! examining! previous! literature! and! combining! this! into! the! hypothesis! under! study.! The! second! part! describes! the! methodology! used! and! the! variables! needed! to! complete!the!research!process.!The!third!section!describes!the!data!that!has!been! collected!from!various!databases!and!shows!mean!values!and!correlations!between! the!variables.!The!fourth!section!shows!the!results!of!the!regressions!performed.!The! fifth!section!adds!robustness!checks!and!additional!analyses!to!the!results.!The!sixth!
2. Literature&review&
!During!the!1970s,!the!fixed!exchange!rate!system!of!Bretton!Woods!came!to!its!end.! This! led! to! an! increase! in! exchange! rate! volatility! and! in! turn! to! an! increase! of! exchange!rate!exposure!for!many!firms!(Bartram,!Dufey!and!Frenkel,!2005).!Over!the! last!decades!this!exposure!has!grown!exponentially,!due!to!increased!globalization!of! firms!(Bartram,!Brown!and!Minton!2010)!and!markets!opening!up!through!extensive! trade!policies!and!reduced!transportation!costs!(Bartram,!Dufey!and!Frenkel,!2005).! Empirical!studies!have!shown!significant!effects!of!exchange!rate!exposure!on!sales! and! cash! flows! (Hung,! 1992;! Williamson,! 2001),! though! the! effect! on! firms’! stock! prices!appears!to!be!weak!or!nonWexistent!(Griffin!and!Stulz,!2001;!Dominguez!and! Tesar,!2006).!! ! Firms!try!to!mitigate!their!foreign!exchange!rate!exposure!by!implementing!one!or! several!measures.!These!measures!are!hedging!strategies!and!come!in!three!general! forms.!First!is!an!operational!hedge,!which!includes!transferring!production!from!one! country!to!another!(Dumas,!1978).!By!producing!in!the!country!where!the!products! are!sold,!the!costs!of!the!product!and!its!revenues!can!for!a!large!part!be!matched!in! the!same!currency.!However,!this!is!not!always!a!viable!option.!Second!is!passingW through! part! or! all! of! the! currency! fluctuations! to! the! client! (Bodnar,! Dumas! and! Marston! 2002).! Many! studies! have! been! done! on! the! effects! of! passingWthrough! exchange!rate!fluctuations!and!these!studies!generally!show!that!it!is!not!possible!to! completely!reduce!a!firm’s!exposure!to!exchange!rate!risks!(Menon,!1995).!The!main! reduction!stems!from!financial!hedging,!in!which!foreign!debt!and!foreign!exchange! derivatives! are! used! (Bartram,! Brown! and! Minton! 2010).! Derivatives! are! means! to! create! a! hedging! position! that! offsets! an! exposure! (Bartram,! Dufey! and! Frenkel,! 2005).!Purnanandam!(2008)!has!studied!the!effect!for!derivative!usage!by!firms!in! financial! distress.! His! study! shows! that! financially! distressed! firms,! especially! in! concentrated!industries,!have!more!incentive!to!hedge!exposures!and!in!turn!make! more! use! of! derivatives.! Forms! of! derivative! hedging! to! offset! foreign! exchange! exposures! include! forward! contracts,! options! contracts! and! swaps.! One! of! the!
downsides! of! using! derivatives! is! that! employees! may! be! tempted! to! speculate! which! direction! the! market! will! take! and! adapt! their! hedging! strategy! accordingly.! Studies! have! been! performed! to! uncover! whether! derivatives! are! often! used! to! speculate!with,!but!research!has!thus!far!shown!that!derivatives!are!used!to!hedge! against!exposures!to!risks.!Allayannis!and!Ofek!(2001)!have!shown!that!in!a!sample! of! nonfinancial! firms,! derivatives! usage! significantly! decreases! exposure! to! foreign! exchange!risks!and!are!thus!not!used!as!speculation!tools.!However,!the!stories!on! Procter!&!Gamble!and!Metallgesellschaft!in!the!nineties!and!various!(financial)!firms! during!the!most!recent!financial!crisis,!show!that!firms!sometimes!do!use!derivatives! to!speculate!with!and!also!show!the!importance!of!studying!why!this!happens.!This! speculation! with! derivatives! often! increases! the! foreign! exchange! risk,! instead! of! decreasing!it!(Bodnar!and!Marston,!1996).!Firms!in!financial!distress!are!especially! prone! to! this! increase! in! risk,! as! explained! in! the! riskWshifting! theory! proposed! by! Jensen!and!Meckling!(1976).!
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Previous!studies!show!that!firms!with!certain!characteristics,!such!as!greater!default! probabilities! (i.e.! financial! distress),! growth! opportunities! and! product! uniqueness,! have! a! higher! exposure! to! exchange! rate! fluctuations! (Wei! and! Starks,! 2013).! The! theory!that!firms!in!financial!distress!have!higher!exposure!is!that!these!firms!have! limited! ability! to! hedge! against! exchange! rate! exposures,! due! to! higher! costs! of! capital!and!lower!credit!worthiness.!Firms!in!financial!distress!are!confronted!with! both! direct! and! indirect! costs! (Opler! and! Titman,! 1994).! The! direct! costs! mainly! consist! of! advisory! fees! and! legal! and! administrative! costs! associated! with! bankruptcy!(Wruck,!1990).!Weiss!(1990)!finds!that!the!direct!costs!only!make!up!a! small!part!of!the!financial!distress!costs,!approximately!3.1%!of!the!market!value.!A! larger! part! stems! from! the! indirect! costs,! which! consist! of! three! parts.! First,! an! inability!to!conduct!the!usual!business!as!the!firm!no!longer!has!the!right!to!make! specific! decisions! without! approval.! Second,! most! firms! see! a! decrease! in! demand! and! an! increase! in! production! costs.! Third,! management! has! to! spend! a! large! amount!of!time!on!resolving!the!financial!distress!(Wruck,!1990).!The!indirect!costs! are! difficult! to! measure,! but! research! done! to! date! shows! that! these! costs! are!
between! 9%! and! 15%! of! market! value! (Cutler! and! Summers,! 1988! and! Altman,! 1984).!! ! In!addition,!firms!in!financial!distress!are!prone!to!increase!their!risk!by!undertaking! riskier!investments!if!the!interests!of!the!shareholders!and!the!managers!are!aligned.! The!reasoning!is!that!the!shareholders!will!receive!the!benefits!if!all!goes!well!and! the! debtholders! will! pay! the! costs! if! the! investment! goes! badly! (Eisdorfer,! 2008).! Jensen! and! Meckling! (1976)! were! among! the! first! to! define! agency! costs! and! the! resulting!riskWshifting!problem.!Agency!costs!are!defined!as!“a!contract!under!which! one!or!more!persons!(the!principals)!engage!another!person!(the!agent)!to!perform! some! service! on! their! behalf! which! involves! delegating! some! decision! making! authority!to!the!agent.!If!both!parties!to!the!relationship!are!utility!maximizers!there! is!good!reason!to!believe!that!the!agent!will!not!always!act!in!the!best!interests!of! the! principal”! (Jensen! and! Meckling,! 1976).! Thus,! in! the! case! of! a! firm! in! financial! distress,! the! shareholders! (the! agents)! have! the! incentive! to! take! on! highWreturn! projects!at!the!cost!of!increased!risk!for!the!debtholders!(the!principals).!This!holds! true! especially! for! firms! with! a! shortWtime! horizon,! such! as! for! firms! in! financial! distress!(Kuersten!and!Linde,!2011).!This!concept!is!known!as!riskWshifting!(Eisdorfer,! 2008).!
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RiskWshifting! is! a! relatively! new! field,! with! minimal! studies! being! performed! in! this! area!to!date.!Even!though!Jensen!and!Meckling!(1976)!defined!their!agency!theory! several!decades!ago,!riskWshifting!itself!has!only!recently!gained!attention!(Eisdorfer,! 2008,! 2009,! 2010).! The! main! empirical! research! stems! from! Eisdorfer! (2008),! who! finds!conclusive!evidence!of!riskWshifting!behavior!for!firms!in!financial!distress.!His! study!shows!that!during!periods!of!high!volatility,!firms!in!financial!distress!realize! less! value! from! their! investments.! The! riskWshifting! theory! supporting! this! is! that! firms!in!financial!distress!take!on!riskier!investments!and!in!turn!have!higher!risk!of! losing!on!their!investment!(Eisdorfer,!2008).!The!main!determinants!of!the!level!of! riskWshifting! have! been! found! to! include! size! of! debt! issues,! earnings! volatility! and! the!interest!rate!(Danielova,!Sarkar!and!Hong,!2013).!In!addition,!a!tradeWoff!occurs! between! riskWshifting! and! corporate! hedging! (Purnanandam,! 2008).! Firms! use!
derivatives! to! hedge! against! risks,! but! use! them! in! an! imperfect! manner! that! increases!risk!for!some!other!firms!(Bodnar!and!Marston,!1996).!Eisdorfer’s!(2008)! study!measures!risk!by!comparing!stock!volatility!of!firms!in!financial!distress!to!the! market! volatility.! Other! studies! have! used! earnings! volatility! as! their! measure! of! operating!risk!(Danielova,!Sarkar!and!Hong,!2013).!However,!no!research!has!been! done! to! date! on! the! specific! risk! of! foreign! exchange! fluctuations! a! firm! can! be! exposed!to.!!
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A! similar! study! by! Starks! and! Wei! (2013)! has! focused! on! the! foreign! exchange! exposure!elasticity!for!manufacturing!firms!in!financial!distress.!The!theory!in!their! paper! is! that! firms! in! financial! distress! are! more! affected! by! exchange! rate! fluctuations!as!they!have!less!access!to!external!capital!markets!and!have!difficulties! conducting! financial! and! operational! hedges.! They! find! a! direct! link! between! financial! distress! and! the! exposure! to! exchange! rate! risks.! That! is,! as! firms’! probabilities!of!financial!distress!increase,!their!foreign!exchange!exposure!increases! as!well.!This!thesis!adds!to!the!study!by!Starks!and!Wei!(2013)!by!adding!derivatives! usage! as! an! explanatory! factor! for! foreign! exchange! exposure! and! building! on! the! riskWshifting!theory.!!
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Another!study!by!Alliyannis!and!Ofek!(2001)!has!explored!the!effect!of!derivatives!on! exchange!rate!exposure!for!US!firms.!The!basis!of!their!paper!was!to!explore!the!role! that! derivatives! play! in! firms,! as! this! became! a! major! concern! to! investors! and! regulators! after! the! derivative! speculation! scandals! surrounding! Procter! &! Gamble! and!Metallgesellschaft.!They!studied!whether!firms!use!derivatives!to!hedge!(and!in! turn!decrease!their!foreign!exchange!exposure)!or!to!speculate!(and!in!turn!increase! their!foreign!exchange!exposure).!Their!findings!show!that!firms!use!derivatives!to! hedge,! as! they! are! successful! in! decreasing! their! foreign! exchange! exposure.! However,!they!do!not!examine!differences!based!on!financial!distress!probabilities,! which!will!be!the!main!contribution!of!this!thesis.!
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Not! much! (empirical)! research! has! been! done! on! riskWshifting! to! date.! The! main! research! stems! from! Eisdorfer! (2008,! 2009,! 2010).! His! evidence! shows! that! shareholders!have!an!incentive!to!show!riskWshifting!behavior!when!the!firm!is!in!a! state! of! financial! distress.! This! behavior! is! affected! by! various! factors,! mainly! stemming!from!the!shareholders’!ability!and!incentive!to!shift!additional!firm!risk!to! debtholders! (Eisdorfer! 2008).! This! thesis! will! contribute! to! the! field! of! riskWshifting! theory!and!try!to!link!this!theory!to!foreign!exchange!exposure!for!firms!in!financial! distress.! This! thesis! will! also! go! inWdepth! into! the! types! of! foreign! exchange! derivatives! that! firms! use! and! whether! the! values! and! types! differ! for! firms! with! higher!probabilities!of!financial!distress.!
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The! recent! financial! crisis! has! shown! the! importance! of! studying! firms! in! financial! distress.!The!riskWshifting!problem!gives!even!more!weight!to!this!topic,!as!taking!on! too!much!risk!was!one!of!the!issues!at!the!start!of!this!crisis.!In!addition,!the!bail!out! of! several! large! firms! on! the! edge! of! bankruptcy! may! increase! the! riskWshifting! incentive!for!these!firms’!shareholders,!as!the!downside!potential!is!decreased!for! these!firms.!
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In! summary,! exposures! to! exchange! rate! risks! are! a! serious! concern! to! many! companies.!This!risk!becomes!even!more!apparent!for!firms!in!financial!distress,!as! riskWshifting!theory!suggests!that!these!firms!will!increase!their!risk!even!further!if! there! is! a! chance! of! a! positive! payoff.! They! may! decide! not! to! use! derivatives! to! hedge! against! these! risks,! but! instead! start! to! speculate! with! these! derivatives! on! which! direction! the! market! will! take! (Bodnar! and! Marston,! 1996).! If! riskWshifting! occurs,!the!theory!suggests!that!firms!in!financial!distress!will!increase!their!foreign! exchange!exposures.!
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Therefore,! this! thesis! will! examine! the! theory! that! firms! in! financial! distress! have! higher! foreign! exchange! exposures! after! using! derivatives! due! to! riskWshifting! behavior.!That!is,!if!riskWshifting!theory!is!correct,!firms!in!financial!distress!will!use! derivatives! for! speculative! purposes! and! in! turn! increase! their! risk.! The! main! hypothesis! to! be! addressed! will! thus! be:! Does! exchange! rate! exposure! after! using!
derivatives! increase! for! firms! with! a! high! probability! of! financial! distress?! Further! analysis!will!also!be!done!on!the!types!of!derivatives!hedging!and!the!probability!of! financial!distress.!!In!summary,!the!hypothesis!is!as!follows:! ! H1:!Exchange!rate!exposure!will!increase!for!firms!with!a!high!probability!of!financial! distress!after!using!derivatives.! !
The! next! sections! will! explore! the! methodology! and! data! that! will! be! used! in! this! study!and!the!results!from!the!regression!analyses.!
3. Research&methodology&&
!In! order! to! test! the! hypotheses,! I! need! a! proxy! for! financial! distress.! The! level! of! financial!distress!in!my!analysis!will!be!measured!using!the!ZWscore!model!by!Altman! (1968).!The!ZWscore!model!is!widely!used!to!predict!financial!distress!and!uses!five! variables! to! obtain! a! ZWscore! (Altman,! 2000).! This! model! is! effective! in! classifying! financial!distress!one!year!before!the!bankruptcy!date!in!up!to!94%!in!earlier!sample! studies!(Altman,!2000).!The!scores!are!categorized!in!three!groups,!a!‘safety!zone’! (scores!of!3.0!or!more),!a!‘grey!area’!(scores!between!1.81!and!2.99)!and!a!‘danger! zone’!(scores!below!1.81).!!! ! The!variables!needed!to!classify!financial!distress!are:! • “X1!=!working!capital!/!total!assets! • X2!=!retained!earnings!/!total!assets! • X3!=!ebit!/!total!assets! • X4!=!market!value!of!equity!/!book!value!of!total!liabilities! • X5!=!sales!/!total!assets”!(Altman!et!al.,!1968)! ! The!function!putting!these!variables!together!is:! ! "! = 0.012!!+ 0.014!!+ 0.033!!+ 0.006!!+ 0.999!!"!(Altman, 1968)! !
The! data! for! these! variables! can! be! found! in! the! Compustat! database.! The! methodology!will!be!used!as!described!by!Altman!(1968).!
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The! level! of! foreign! exchange! exposure! will! be! measured! according! to! the! methodology! described! in! Choi! and! Prasad! (1995).! This! timeWseries! regression! is! derived!from!the!methodology!introduced!by!Jorion!(1990).!The!main!adaptation!is! that!Jorion’s!(1990)!model!also!uses!the!foreign!to!total!sales!ratio,!which!will!instead! be!incorporated!in!equation!(3).!This!method!includes!both!the!index!return!and!the! real!interest!rate!in!a!twoWfactor!model:! ! (1)!
! "!!,! = !!+ !!!!!" + !!!"#!$!+ !!!"#$%$&#!+ !!,!!!for$j$=$1…N! ! • !!,!!is!the!stock!return!for!firm!j!in!month!t! • !!!"!is!the!percentage!change!in!the!exchange!rate!index!for!month!t! • !"#!$!!is!the!equally!weighted!CRSP!index!return!for!month!t! • !"#$%$&#!!is!the!real!interest!rate!for!month!t! • !!!is!the!regression!coefficient!of!interest,!interpreted!as!the!elasticity!of!firm! j’s!equity!valuation!to!exchange!rate!risk”!(Starks!and!Wei,!2013)! !
An! equally! weighted! CRSP! index! return! is! used! to! remove! the! bias! that! large! multinational! firms! (with! high! foreign! exchange! rate! exposures)! dominate! valueW weighted!market!index!returns!(Bodnar!and!Wong,!2003).!The!exchange!rate!index! used!is!the!tradeWweighted!US!dollar!index!against!major!currencies.!This!variable!is! extracted!from!the!Federal!Reserve!database,!the!other!variables!mentioned!can!be! found!in!the!Compustat!database!and!the!CRSP!database.!
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The! final! stage! includes! testing! the! specific! hypothesis.! The! beta! needs! to! be! regressed! on! various! proxies,! including! the! level! of! financial! distress.! Previous! studies! have! shown! that! growth! opportunities! (Starks! and! Wei,! 2013),! specialized! products!(Titman!and!Wessels,!1988),!foreign!sales!(Doidge,!Griffin!and!Williamson,! 2006),! leverage,! salesWtoWmarket! value,! size! and! industry! (Starks! and! Wei,! 2013)! contribute! to! enhancing! exchange! rate! sensitivity.! Thus,! these! proxies! need! to! be! included! in! the! regression.! In! addition,! as! this! thesis! focuses! on! exchange! rate! exposure!of!firms!in!financial!distress!after!using!derivatives,!a!proxy!will!be!included! for!derivatives!use.!Thus,!the!regression!will!be!as!follows:! ! "!"#(!"#) = ! + !!! + !!!"!"+ !!!"#$%!"+ !!!"!" + !!!"#$%!"+ !!!"#!"+ !!!"!"+ !!!"#$!"+ !!!"#!"+!!!"!"#$%!""! (adapted!from!Starks!and!Wei,!2013)! (2)! (3)!
• abs(exp)!is!the!absolute!value!of!the!exposure!derived!from!equation!(2),!the! absolute!value!of!!!.! • Z!is!the!level!of!financial!distress!as!measured!by!Altman’s!ZWscore!in!equation! (1).! • PB!is!the!marketWtoWbook!value,!a!measure!of!growth!opportunities.!Ratio!of!a! firm’s!market!capitalization!divided!by!its!book!value.! • CapEx!is!the!firm’s!capital!expenditures,!a!measure!of!growth!opportunities.! Ratio!of!a!firm’s!capital!expenditures!divided!by!net!PPE.!
• RD! is! the! level! of! research! and! development! expenditures,! a! measure! of! product!specialization.!Ratio!of!R&D!expenses!to!total!assets.!
• ForTS!is!the!level!of!Foreign!Sales,!measured!by!foreign!sales!divided!by!total! sales.!
• Lev! is! the! leverage,! a! measure! of! capital! structure.! Ratio! of! book! value! of! debt!divided!by!total!assets.!
• SM! is! the! salesWtoWmarket! value,! measured! by! annual! sales! divided! by! the! market!value!of!equity.!
• Size!is!measured!by!the!log!of!the!firm’s!market!capitalization.!
• Industry! is! a! combination! of! 10! dummy! variables! for! the! general! industries! the!companies!are!in.!
• Deriv!is!the!measure!of!hedging.!A!dummy!variable!that!indicates!whether!a! company! uses! derivatives! (1)! or! not! (0).! As! this! information! is! not! readily! available,! data! is! gathered! on! whether! each! firm! had! (unrealized! and! realized)! gains! and! losses! on! derivatives.! If! this! is! the! case,! a! value! of! 1! is! given!to!that!company!for!the!year!and!a!0!if!they!do!not!report!gains!and! losses!on!derivatives.! ! The!data!on!the!variables!mentioned!can!be!found!in!the!Compustat!database!and! the!Datastream!database.!! ! !
&
4. Data&and&descriptive&statistics&
!The! data! used! will! be! from! the! last! decade,! from! 2004! till! 2013.! This! time! period! includes!a!severe!financial!crisis,!which!ensures!sufficient!data!on!firms!in!financial! distress.!In!addition,!as!the!globalization!trend!continues,!more!and!more!firms!are! expected!to!be!exposed!to!exchange!rate!risks!(Bartram,!Brown!and!Minton!2010).! By!using!recent!data,!the!relevance!of!the!study!is!ensured.! ! The!data!stems!from!companies!that!were!listed!on!the!New!York!Stock!Exchange! (NYSE)!and!NASDAQ,!including!companies!that!went!inactive!during!this!time!period.! Inactivity!does!not!necessarily!mean!these!companies!went!bankrupt,!companies!can! also!become!inactive!when!they!leave!the!exchange!they!are!trading!on.!The!main! currency! used! by! these! companies! is! the! dollar,! with! currency! exposures! varying! from!firm!to!firm.!The!data!collection!started!off!with!the!total!pool!of!all!companies! trading! on! these! markets! in! the! time! period! of! interest.! The! observations! were! reduced!by!adding!several!restrictions,!such!as!data!availability,!positive!total!assets! and!data!on!derivative!usage.!!
!
In!total,!there!are!1948!companies!that!fit!these!criteria.!Of!these!companies,!195! became! inactive! during! the! time! period! of! interest! and! 1753! stayed! active.! In! general,! out! of! all! observations! over! the! time! period! 2004! to! 2013,! 91.84%! was! active.! As! reported! in! column! B! of! table! 1,! 34.02%! of! these! companies! used! derivatives.!This!finding!is!lower!than!that!of!previous!studies,!such!as!Bodnar!and! Gebhardt! (1998),! who! find! that! 57%! of! nonWfinancial! US! firms! use! derivatives! to! hedge! and! Bartram,! Brown! and! Fehle! (2009),! who! show! that! 64.9%! of! US! nonW financial!firms!use!derivatives!to!hedge!and!37.7%!use!foreign!exchange!derivatives.! This! difference! can! be! explained! by! the! proxy! used! to! examine! derivatives! usage.! This! study! uses! (unrealized)! gains! and! losses! on! derivatives! as! a! measure! whether! the!firms!use!derivatives!or!not.!The!studies!mentioned!above!have!retrieved!their! data!from!direct!surveys!to!the!firms!in!their!study!and!thus!do!not!need!a!proxy.!
Several!descriptive!statistics!have!been!added!in!tables!1!to!3.!The!first!table!shows! descriptive!statistics!of!all!the!variables!in!the!study,!as!shown!in!equations!(1),!(2)! and!(3).!Two!of!these!variables!are!dummy!variables!(activity!and!derivative!usage).! The! industry! variable! has! been! omitted,! as! it! has! no! mean! value.! The! firms! under! study!come!from!10!different!industries,!with!the!manufacturing!industry!being!the! largest!contributor.!
!
Table! 2! shows! the! correlations! between! the! variables,! subdivided! by! each! of! the! equations! mentioned! in! the! research! methodology! section.! Many! of! the! variables! are!significantly!correlated.!However,!as!the!methodology!used!has!been!proven!in! many! previous! studies,! this! should! not! be! cause! for! concern.! Many! of! the! correlations!can!also!be!explained!by!financial!theory.!One!such!example!is!the!high! correlation! between! the! real! interest! rate! and! the! percentage! change! in! the! exchange! rate! index! (Table! 2! Panel! B),! which! are! directly! linked! in! the! theory! of! interest!rate!parity.!The!most!interesting!correlations!are!shown!in!Table!2!Panel!C,! as!these!are!these!are!the!variables!in!the!main!regression.!Although!many!of!the! correlations! are! significant,! the! values! are! relatively! low.! Major! concern! are! the! correlations! between! the! independent! variables! as! this! may! lead! to! problems! of! multicollinearity,!which!is!tested!in!the!robustness!section!and!does!not!prove!to!be! an!issue.!The!highest!(positive)!correlations!can!be!seen!between!derivatives!use!and! foreign!sales!levels,!leverage!and!size.!Larger!companies!have!higher!levels!of!foreign! sales!then!smaller!companies!and!hence!have!more!incentive!to!hedge!exposures!to! exchange! rate! fluctuations.! In! addition,! hedging! is! often! combined! with! taking! on! extra!leverage!(Bodnar!and!Marston,!1996),!which!explains!the!high!correlations!of! these!variables!with!leverage.!
!
Table! 3! shows! the! descriptive! statistics! for! the! ZWscore.! We! see! that! in! any! given! year,!most!companies!have!ZWscores!in!the!safety!zone.!The!effects!of!the!financial! crisis! that! started! in! 2008! are! also! clear! from! this! table.! A! significant! drop! in! the! average! ZWscore! can! be! seen! in! that! year,! with! only! slightly! more! than! half! of! the! companies! having! ZWscores! in! the! safety! zone.! Overall,! the! ZWscores! over! the! years! have! an! average! value! of! around! 5.0,! with! 62%! having! ZWscores! showing! low!
probabilities! of! financial! distress.! These! values! are! in! line! with! previous! studies,! in! which!average!ZWscores!are!around!3.0!for!crisis!years!(such!as!during!the!‘80s)!and! 6.0! and! higher! during! boom! years! (such! as! the! late! ‘90s)! (Altman,! 2000).! Similar! studies!focusing!on!the!effects!of!financial!distress!on!exchange!rate!exposure,!such! as! Starks! and! Wei! (2013),! incorporate! significantly! lower! financial! distress! probabilities!into!their!studies.!The!difference!can!be!explained!in!two!ways.!Firstly,! the!study!by!Starks!and!Wei!(2013)!uses!Merton’s!default!probability!model!(Merton,! 1974)!as!the!measure!of!financial!distress.!Second,!they!restrict!their!sample!by!using! only! firms! with! assets! over! $50! million,! and! in! result! eliminate! smaller! firms! with! higher! default! probabilities! from! their! sample! (Vassalou! and! Xing,! 2004).! The! monthly!default!probability!used!in!their!study!is!2.09%!with!a!standard!deviation!of! 7.56%!(Starks!and!Wei,!2013).!
Table&1&–&Summary&statistics&of&firm&exposure&to&foreign&exchange&risk&
This!table!shows!the!descriptive!statistics!of!the!variables!in!this!study.!In!total!there! are! 1948! companies! that! fit! the! criteria! in! the! time! period! from! 2004! to! 2013,! totaling!12.342!observations.!The!mean,!median,!standard!deviation,!minimum!and! maximum! are! given.! The! variables! for! exchange! rate! exposure! (Stock! return,! Exchange!rate!change,!EWRET!and!Interest)!are!based!on!monthly!values,!the!others! on! yearly! values.! The! variables! Active! and! Derivative! are! dummy! variables.! The! industry! variable! has! been! omitted,! as! it! has! no! mean! value.! Most! notable! is! that! only!34.02%!of!companies!use!financial!derivatives.!!
!
! Mean! Median! Std!Dev.! Min! Max!
Work.Cap./TA! 0.3308! 0.3050! 0.2263! W0.5915! 0.9616! RE/TA! W0.5066! 0.1300! 2.5466! W87.6696! 2.6616! EBIT/TA! 0.0378! 0.0741! 0.1929! W3.6189! 1.6467! MV!Eq./TL! 7.0034! 3.3020! 12.2012! 0.0022! 333.2375! Sales/TA! 1.0400! 0.8744! 0.7271! 0.0022! 8.6069! Stock!Return!! W0.0062! 0.0058! 0.3013! W10.9546! 8.6304! Exch.!Rate!change!! 0.0003! 0.0018! 0.0114! W0.04111! 0.0602! EWRET! 0.0184! 0.0144! 0.0453! W0.2052! 0.1928! INTEREST! W0.0030! W0.0034! 0.0021! W0.0096! 0.0198! Abs(exposure)! 20.1402! 7.5043! 97.1792! 0.0000! 6172.1250! Z! 5.0535! 3.7565! 8.1444! W116.4592! 202.0437! PB! 4.4814! 2.3496! 30.5878! 0.0083! 1575.7040! CapEx! 0.2885! 0.2217! 0.5166! 0.0000! 43.1465! R&D! 0.0762! 0.0362! 0.1168! 0.0000! 1.9785! ForTS! 31.8190! 26.8000! 29.8598! 0.0000! 100.0000! Lev! 0.3595! 0.0834! 0.1581! 0.0000! 0.8881! SM! 1.4247! 0.6835! 5.6275! 0.0011! 444.1147! Size! 6.5106! 6.4280! 2.0529! 0.9233! 13.3480! Active! 0.9184! 1.0000! 0.2737! 0.0000! 1.0000! Derivative! 0.3402! 0.0000! 0.4738! 0.0000! 1.0000!
Table&2&–&Correlations&for&all&variables&affecting&foreign&exchange&exposure& This%table%is%divided%into%three%panels,%one%for%each%of%the%regressions.%Panel%A%shows%the%correlations%for%the%variables%used%to%compute%the%Z< score.%We%see%a%relatively%high%correlation%between%variables%Retained%Earnings%to%Total%Assets%(RE/TA)%and%EBIT%to%Total%Assets%(EBIT/TA),% which%can%be%explained%by%the%relation%between%EBIT%and%retained%earnings.%As%this%is%a%proven%method%of%computing%default%probabilities,%this% high%correlation%is%no%cause%for%concern.%Panel%B%shows%the%correlations%for%the%variables%used%to%compute%the%foreign%exchange%exposure%as% given%in%equation%(2).%Once%again,%we%see%a%relatively%high%correlation%between%the%exchange%rate%fluctuation%and%the%real%interest%rate,%which% is%explained%by%interest%rate%parity%theory.%Panel%C%shows%the%correlations%between%the%variables%in%the%main%hypothesis.%Most%notable%is%a% negative%correlation%between%R&D%and%derivatives%use,%while%a%(strong)%positive%relation%can%be%seen%between%derivatives%use%and%Foreign% Sales%levels,%leverage%and%size.%% % Panel%A%
% WC/TA% RE/TA% EBIT/TA% Eq/TL% Sale/TA%
WC/TA% 1.0000% % % % % RE/TA% <0.1396*% 1.0000% % % % EBIT/TA% <0.1976*% 0.5429*% 1.0000% % % Eq/TL% 0.3861*% <0.0638*% <0.0147% 1.0000% % Sale/TA% <0.1498% 0.1115*% 0.2579*% <0.1814*% 1.0000% % % Panel%B%
% Stock%ret.% FX%ret.% EWRET% INTEREST%
Stock%ret.% 1.0000% % % %
FX%ret.% <0.0631*% 1.0000% % %
EWRET% 0.2033*% <0.3106*% 1.0000% %
Panel%C%
% Abs(exp)% Z% PB% CapEx% R&D% ForTS% Lev% SM% Size% Deriv%
Abs(exp)% 1.0000% % % % % % % % % % Z% <0.0380*% 1.0000% % % % % % % % % PB% <0.0022% <0.0100% 1.0000% % % % % % % % CapEx% 0.0307*% 0.0654*% 0.0096% 1.0000% % % % % % % R&D% 0.0288*% <0.1436*% 0.0851*% 0.0725*% 1.0000% % % % % % ForTS% <0.0125% <0.0109*% <0.0179*% <0.0188*% 0.0105% 1.0000% % % % % Lev% <0.0032% <0.2654*% 0.0815*% <0.0839*% <0.1893*% <0.0144% 1.0000% % % % SM% 0.0182*% <0.0549*% <0.0164% <0.0311*% <0.0845*% <0.0522*% 0.0877*% 1.0000% % % Size% <0.1123*% 0.1270*% 0.0441*% <0.0490*% <0.2215*% 0.2232*% 0.2148*% <0.1139*% 1.0000% % Derivative% <0.0504*% <0.0805*% <0.0012% <0.0958*% <0.2224*% 0.2053*% 0.3074*% 0.0385*% 0.4305*% 1.0000% % *%Significant%at%the%0.05%level% ! ! !
Table&3&–&Distribution&of&Z3scores&per&year& This%table%shows%the%distribution%of%the%Z3score%per%year.%The%average%Z3scores%per% year%are%shown,%as%well%as%the%percentages%of%companies%having%a%Z3score%in%one%of% the%three%zones%(Danger%Zone%–%Z3scores%below%1.81,%Grey%Area%–%Z3scores%between% 1.81%and%2.99%and%the%Safety%Zone%–%Z3scores%above%3.00).%% %
Fiscal%Year% Average%Z3score% Danger%Zone% Grey%Area% Safety%Zone%
2004% 7.1642% 11.93%% 17.40%% 70.68%% 2005% 6.3535% 13.02%% 16.32%% 70.66%% 2006% 6.2125% 12.70%% 15.70%% 71.60%% 2007% 5.9243% 15.72%% 18.07%% 66.21%% 2008% 3.6055% 26.84%% 21.64%% 51.51%% 2009% 4.1537% 21.95%% 21.04%% 57.00%% 2010% 4.6053% 19.71%% 18.97%% 61.32%% 2011% 4.2495% 22.35%% 19.45%% 58.21%% 2012% 4.1999% 20.85%% 20.48%% 58.67%% 2013% 5.2591% 15.57%% 19.12%% 65.31%% Overall% 5.0535% 18.57%% 18.96%% 62.47%% % % %
5. Results&
% After%collecting%all%the%data%on%the%firms%in%the%study,%the%regressions%described%in%the% methodology%section%were%performed.%First%was%calculating%all%the%Z3scores%for%the% firms%for%each%separate%year%using%equation%(1).%Next,%a%time3series%regression%was% run%using%equation%(2)%to%estimate%coefficients%for%the%foreign%exchange%exposures% for%each%firm%on%an%annual%basis.%The%data%used%for%the%exposures%was%on%a%monthly% basis% and% then% combined% for% each% twelve3month% period% to% retrieve% the% annual% exposure%value%for%each%firm%(Starks%and%Wei,%2013).%The%final%step%was%to%run%the% regression% from% equation% (3),% in% various% forms.% Some% data% on% the% estimates% of% foreign%exchange%exposure%has%been%shown%in%appendix%A.%%%
Firstly,%the%regression%was%run%based%on%all%the%variables%and%performed%as%described% in%the%methodology%section.%The%absolute%values%of%the%estimated%exposures%were% regressed% on% the% firms’% Z3scores,% market3to3book% value,% capital% expenditures,% R&D% expenses,%foreign%sales,%leverage,%sales%to%market%capitalization,%firm%size,%derivative% usage%and%10%industry%dummies.%The%regression%has%been%performed%in%two%ways,% one%based%on%simple%linear%regression,%the%other%based%on%a%panel%data%set%with%firm% and%year%fixed%effects.%By%setting%the%data%for%fixed%effects,%we%can%observe%whether% differences%exist%on%a%firm3level%and%a%yearly%basis.%The%results%are%shown%in%table%4.%% % In%the%simple%linear%regression%Z3scores,%Capital%expenditures,%leverage%and%size%are% significant%at%the%5%%level%and%the%derivative%usage%is%significant%at%the%10%%level.%In% the%panel%data%set,%most%variables%loose%their%significance,%only%the%Z3score%remains% significant% at% the% 5%% level.% We% see% that% by% setting% the% data% for% fixed% effects,% the% explanatory% power% (shown% by% R3squared)% becomes% much% larger% at% 0.3378.% This% indicates%that%the%fixed%effects%model%is%better%at%incorporating%the%variables%in%the% study% to% explaining% the% variance% in% the% foreign% exchange% exposure.% The% intra3class% correlation% (given% by% rho)% indicates% that% nearly% 65%% of% the% variance% is% due% to% differences%between%the%panel%sets%(Brooks,%2008).%
The% two% most% important% variables% in% this% study% are% the% Z3score% and% the% use% of% derivatives.%The%Z3score%is%significant%and%has%a%small%negative%coefficient.%This%means% that% for% firms% with% higher% Z3scores,% the% absolute% exposure% goes% down% slightly.% For% firms%that%increase%their%Z3score%by%1,%the%exposure%to%exchange%rate%risk%goes%down% by%0.2097%(0.3614%according%to%the%panel%data%set%regression).%This%is%in%line%with%the% results% reported% by% Starks% and% Wei% (2013),% that% firms% with% higher% probabilities% of% financial%distress%are%more%exposed%to%exchange%rate%risks.%The%intuition%is%that%firms% in%financial%distress%are%more%affected%by%exchange%rate%fluctuations%as%they%have%less% access% to% external% capital% markets% and% have% difficulties% conducting% financial% and% operational%hedges%(Starks%and%Wei,%2013).%The%derivatives%use%variable%is%significant% in% the% simple% linear% regression% and% has% a% coefficient% that% is% clearly% negative.% This% means% that% firms% that% make% use% of% derivatives,% decrease% their% exposure% to% foreign% exchange%rate%risks%by%2.1355%(not%significant%in%the%panel%data%set%regression).%This% result%is%to%be%expected,%as%firms%in%general%use%derivatives%to%hedge%and%decrease% exposures%to%risks%(Bartram,%Dufey%and%Frenkel,%2005).%It%is%also%in%line%with%previous% studies,%such%as%Allayannis%and%Ofek%(2001),%which%find%that%firms%that%use%(currency)% derivatives%significantly%reduce%their%exchange%rate%exposure.%This%means%that%firms% generally%use%derivatives%to%hedge%exposures,%not%to%speculate%with%them%(Allayannis% and% Ofek,% 2001).% The% next% step% is% to% uncover% whether% derivatives% usage% changes% exposures% for% firms% with% high% probabilities% of% financial% distress,% as% stated% in% the%
Table&4&–&Regression&results&for&exchange&rate&exposure&&
This%table%shows%the%overall%regression%results%for%equation%(3).%The%first%step%is%to% determine%the%Z3scores%using%equation%(1).%Next,%each%firms’%exposure%is%regressed% according% to% equation% (2).% Finally,% the% estimated% exposures% are% regressed% on% the% firms’% Z3scores,% market3to3book% value,% capital% expenditures,% R&D% expenses,% foreign% sales,% leverage,% sales% to% market% capitalization,% firm% size,% derivative% usage% and% 10% industry% dummies.% The% first% column% shows% the% regression% results% based% on% simple% linear%regression,%the%second%column%shows%the%same%regression%with%the%panel%data% set% to% firm% and% year% fixed% effects.% In% the% panel% data% set% regression,% the% industry% dummies%have%been%omitted%due%to%multicollinearity.%The%table%includes%observation% size% and% R3squared% in% the% bottom% rows,% as% well% as% rho% for% the% panel% data% set% regression.%
%
Abs(exp)% Simple%linear%regression% Panel%data%set%regression%
Constant% 142.1136% (0.94)% 52.5904% (2.04)***% Z% 30.2097% (32.89)***% 30.3614% (32.40)***% PB% 0.0036% (0.34)% 0.0039% (0.35)% CapEx% 4.7906% (2.78)***% 1.9305% (1.09)% R&D% 2.2389% (0.33)% 317.9272% (31.25)% ForTS% 0.0662% (1.57)% 0.0001% (0.00)% Lev% 13.9558% (2.03)***% 12.6541% (0.96)% SM% 0.0292% (0.16)% 0.0035% (0.03)% % % %
Table%4%continued% Size% 35.2972% (36.12)***% 34.7330% (31.22)% Derivative% 32.1355% (31.93)**% 32.2431% (30.42)%
Industry% Yes% Omitted%
N% 12,342% 12,342% R2% 0.0563% 0.3378% Rho% % 0.6478% **%significant%at%the%0.1%level% ***%significant%at%the%0.05%level% % %
Since%for%the%relationship%between%Z%and%exposure%it%only%matters%whether%a%firm%is% close% to% financial% distress% and% not% so% much% on% the% level% of% Z,% the% regression% has% additionally%been%run%differentiating%on%the%basis%of%groups%of%Z3scores.%Two%dummy% variables%were%created,%one%for%Z3scores%under%3.0%(Z3scores%in%the%danger%zone%and% the% grey% area)% and% one% for% Z3scores% under% 1.81% (Z3scores% in% the% danger% zone).% The% estimated% exposures% are% regressed% on% these% dummy% variables,% market3to3book% value,%capital%expenditures,%R&D%expenses,%foreign%sales,%leverage,%sales%to%market% capitalization,%firm%size,%derivative%usage%10%industry%dummies.%In%addition,%a%cross3 term%has%been%added%for%Z3scores%and%derivative%usage,%in%order%to%make%inferences% on%the%interaction%between%these%variables.%The%results%of%this%regression%have%been% reported%in%table%5.%% % Again%we%see%that%Z3scores,%capital%expenditures,%leverage,%size%and%derivatives%usage% are% statistically% significant% when% we% use% the% Z3score.% The% size% variable% and% use% of% derivative%variable%show%a%decrease%in%the%exposure%to%exchange%rate%risks,%but%the% other% significant% variables% increase% exposure% as% the% value% of% the% variable% becomes% larger.% Additionally,% the% cross3term% for% Z3scores% and% derivative% usage% is% significant% and%positive%for%the%continuous%variable,%but%increasingly%negative%for%firms%with%high% probabilities% of% financial% distress.% This% would% indicate% that% lower% Z3scores% and% derivatives%usage%have%negative%effects%on%the%exposure%to%exchange%rate%risk.%The% exposure% to% exchange% rate% risks% is% decreased% by% 7.8711% when% firms% with% financial% distress%probabilities%in%the%grey%area%and%danger%zone%are%taken%into%account.%This% exposure%is%decreased%even%more,%by%8.9709,%when%only%firms%with%financial%distress% probabilities%in%the%danger%zone%are%taken%into%account.%That%is,%as%firms%have%higher% probabilities% of% financial% distress,% using% derivatives% decreases% their% exchange% rate% exposure.% This% result% is% not% in% line% with% the% hypothesis% formulated% earlier,% as% the% expectancy%of%risk3shifting%theory%would%predict%the%opposite%to%happen.%Allayannis% and% Ofek% (2001)% have% shown% in% their% study% that% using% derivatives% decreases% the% exposure%to%exchange%rate%risk,%and%this%result%does%not%appear%to%be%different%for% firms%with%high%probabilities%of%financial%distress.%
In%this%regression%we%see%that,%compared%to%the%original%regression%reported%in%table% 4,%the%sign%of%Z3score%coefficient%changes%and%becomes%larger%for%firms%with%Z3scores% in%the%grey%area%and%danger%zones.%This%means%that%that%exposure%becomes%larger%for% firms%with%high%probabilities%of%financial%distress.%A%similar%pattern%can%be%seen%when% we%look%only%at%derivative%usage,%although%this%variable%is%not%significant%when%the% regression% incorporates% the% dummy% variables% for% the% Z3score.% We% see% that% the% coefficient%becomes%positive%when%comparing%Z3scores%above%and%below%3.0%and%less% negative%when%comparing%Z3scores%above%and%below%1.81.%This%would%indicate%that% firms%with%high%probabilities%of%financial%distress%that%use%derivatives%decrease%their% foreign%exchange%exposures,%but%not%significantly%so.%% % Overall,%the%results%presented%in%tables%4%and%5%indicate%that%the%hypothesis%stated% previously% does% not% hold.% It% appears% that% firms% with% high% probabilities% of% financial% distress% use% derivatives% to% hedge% and% in% turn% decrease% their% exposure% to% foreign% exchange% rate% risk.% If% risk3shifting% theory% were% proved% in% this% study,% we% would% see% that%firms%use%derivatives%to%speculate%and%in%turn%increase%their%foreign%exchange% exposures.% Allayannis% and% Ofek% (2001)% have% shown% in% their% study% that% firms% use% derivatives% to% hedge% and% decrease% their% exposures% instead% of% speculating% with% derivatives%and%increasing%exposure.%This%result%does%not%appear%different%for%firms% with%high%probabilities%of%financial%distress.% %
Table&5&–&Regression&results&for&foreign&exchange&exposure&based&on&Z3scores&
The% table% below% shows% the% regression% results% from% equation% (3),% subdivided% by% Z3 score.%The%first%step%is%to%determine%the%Z3scores%using%equation%(1).%Next,%each%firms’% exposure%is%regressed%according%to%equation%(2).%Finally,%the%estimated%exposures%are% regressed% on% the% firms’% Z3scores,% market3to3book% value,% capital% expenditures,% R&D% expenses,%foreign%sales,%leverage,%sales%to%market%capitalization,%firm%size,%derivative% usage%10%industry%dummies%and%a%cross3term%for%Z3score%and%derivative%usage.%The% first%column%(Continuous%variable)%shows%the%results%based%on%the%Z3score,%without%a% dummy% variable% for% comparison% reasons.% The% second% column% (Dummy% below% 3.0)% shows%the%results%for%companies%based%on%a%dummy%variable%for%Z3scores%below%3.0,% i.e.,% companies% with% probabilities% of% financial% distress% in% the% danger% zone% and% grey% area.% The% third% column% (Dummy% below% 1.81)% shows% regression% results% based% on% a% dummy%variable%for%firms%with%Z3scores%below%1.81,%i.e.%high%probabilities%of%financial% distress% in% the% danger% zone.% The% coefficients% are% given% as% well% as% the% t3statistics% in% parentheses.% Additionally,% the% number% of% observations% and% R3squared% are% given% at% the%bottom%of%the%table.% % Abs(exp)% Continuous% variable% Dummy%% below%3.0% Dummy%% below%1.81% Constant% 142.3056% (1.41)% 138.5986% (1.36)% 141.1150% (1.40)% Z(dummy)% 30.2374% (33.15)***% 7.5001% (2.24)***% 7.7226% (2.18)***% PB% 0.0031% (0.31)% 0.0042% (0.42)% 0.0030% (0.31)% CapEx% 4.7606% (3.62)***% 4.8449% (3.73)***% 4.7926% (3.54)***% R&D% 1.6135% (0.23)% 30.9112% (30.13)% 32.2735% (30.32)% ForTS% 0.0655% (1.56)% 0.0638% (1.57)% 0.0664% (1.56)% % % % %
Table%5%continued% Abs(exp)% Continuous% variable% Dummy%% below%3.0% Dummy%% below%1.81% Lev% 15.3546% (2.13)***% 10.9134% (1.51)% 13.1734% (2.25)***% SM% 0.0329% (0.19)% 0.0249% (0.14)% 0.0372% (0.22)% Size% 35.3408% (36.14)***% 35.1602% (36.12)***% 35.2016% (35.75)***% Derivative% 34.3110% (32.54)***% 0.8624% (0.62)% 30.4228% (30.36)% Z(dummy)% x% derivative% 0.4923% (2.38)***% 37.8711% (32.67)***% 38.9709% (32.06)***%
Industry% Yes% Yes% Yes%
N% 12,342% 12,342% 12,342%
R2% 0.0159% 0.0163% 0.0162%
***%significant%at%the%0.01%level% **%significant%at%the%0.05%level%
A% final% regression% has% been% performed% where% the% exposures% are% divided% based% on% whether% the% exposure% is% positive% or% negative.% The% results% based% on% absolute% exposures%are%also%given%for%comparative%purposes.%The%results%are%further%divided%in% two% sections,% based% on% whether% the% companies% use% derivatives% or% not.% This% will% enable%us%to%make%inferences%about%exposures%based%on%derivatives%usage.%Positive% exposures% indicate% net% exporters,% whereas% negative% exposures% indicate% net% importers%(Cho%and%Song,%2011).%The%results%are%given%in%table%6.%
%
The%results%show%that%each%of%the%variables%is%significant%in%at%least%one%setting,%but% only%size%is%significant%in%all%samples.%When%looking%at%the%Z3scores,%we%see%that%for% both% samples% (with% firms% that% do% use% derivatives% and% those% that% do% not),% negative% exposures% (net% importers)% have% slightly% less% negative% Z3score% coefficients,% while% positive%exposures%(net%exporters)%have%slightly%more%negative%Z3score%coefficients.% This%would%indicate%that%net%exporters%with%higher%probabilities%of%financial%distress% (i.e.,%lower%Z3scores)%are%less%exposed%to%exchange%rate%risk%than%net%exporters%with% higher%Z3scores,%whereas%net%importers%with%higher%likelihoods%of%financial%distress% experience%more%exchange%rate%exposure%than%net%importers%with%higher%Z3scores.%% % Using%derivatives%has%an%effect%on%foreign%exchange%exposures,%although%not%always% significantly.%We%see%that%as%firms’%Z3scores%increase,%those%that%do%use%derivatives% decrease%their%exposures%to%foreign%exchange%rate%risk%more%than%firms%that%do%not% use% derivatives.% That% is,% as% the% probability% of% financial% distress% decreases,% using% derivatives%will%decrease%the%exposure%to%foreign%exchange%rate%risks.%%
%
Interesting% to% see% is% that% the% variables% in% the% regression% have% higher% explanatory% value%for%the%exposure%levels%for%firms%that%do%use%derivatives%than%for%those%that%do% not.%This%can%be%seen%by%comparing%the%R3squared%statistics%of%the%two%groups.%% %
Table&6&–&Regression&results&for&foreign&exchange&exposure&based&derivative&usage&and&exposure&
This%table%shows%the%results%of%the%regression%as%noted%in%equation%(3).%The%first%step%is%to%determine%the%Z;scores%using%equation%(1).%Next,%each% firms’%exposure%is%regressed%according%to%equation%(2).%Finally,%the%estimated%exposures%are%regressed%on%the%firms’%Z;scores,%market;to;book% value,%capital%expenditures,%R&D%expenses,%foreign%sales,%leverage,%sales%to%market%capitalization,%firm%size,%derivative%usage%and%10%industry% dummies.% The% table% is% divided% into% six% parts,% based% on% the% exposure% measurement.% The% first% three% columns% show% only% companies% that% use% derivatives.% For% the% last% three% columns,% only% companies% that% do% no% use% derivatives% are% taken% into% account.% The% first% and% fourth% columns% represent%the%statistics%with%the%dependent%variable%as%absolute%exposure%of%the%companies.%The%second%and%fifth%columns%show%the%same% regression%with%the%dependent%variable%restricted%to%negative%values%and%the%third%and%sixth%columns%show%the%regression%with%the%dependent% variable% restricted% to% positive% exposures.% The% coefficients% are% shown,% including% the% t;statistics% in% parentheses.% In% addition,% the% number% of% observations%and%R;squared%are%mentioned%below%each%column.%
%
% Use%derivatives% Do%not%use%derivatives%%
% Absolute%exposure% Negative%exposure% Positive%exposure% Absolute%exposure% Negative%exposure% Positive%exposure%
Constant% 26.0158% (3.59)***% 24.2064% (2.82)***% 12.8576% (2.65)***% 149.1236% (1.47)% 73.2593% (5.98)***% 140.0852% (1.39)% Z% ;0.2538% (;1.99)***% ;0.2318% (;1.89)**% ;0.3157% (;1.57)% ;0.1098% (;1.39)% ;0.0286% (;0.19)% ;0.1702% (;2.20)***% PB% 0.0046% (0.32)% ;0.0062% (;4.33)***% 0.0233% (0.61)% 0.0044% (0.31)% 0.0153% (0.53)% ;0.0088% (;0.95)% % % %
Table%6%continued%
% Use%derivatives%% Do%not%use%derivatives%%
% Absolute%exposure% Negative%exposure% Positive%exposure% Absolute%exposure% Negative%exposure% Positive%exposure%
CapEx% 11.9124% (3.20)***% 7.8744% (1.31)% 16.7202% (3.95)***% 4.5985% (3.52)***% 4.6602% (1.04)% 4.8579% (4.25)***% R&D% ;0.1406% (;0.03)% ;1.7487% (;0.15)% 3.8903% (0.33)% 1.1105% (0.15)% ;20.5230% (;1.55)% 20.2250% (2.79)***% ForTS% 0.0327% (2.05)***% ;0.0054% (;0.25)% 0.0621% (2.71)***% 0.0833% (1.39)% 0.0373% (0.84)% 0.1370% (1.27)% Lev% 4.0762% (1.43)% 0.6159% (0.17)% 5.4665% (1.31)% 24.8897% (2.18)***% 46.3218% (1.93)**% 6.2246% (1.45)% SM% ;0.0016% (;0.05)% 0.2508% (1.16)% ;0.0264% (;1.83)**% 0.1914% (0.34)% 0.6094% (0.55)% ;0.3382% (;1.05)% Size% ;1.8492% (;4.16)***% ;1.8381% (;2.12)***% ;1.7537% (;6.76)***% ;7.6255% (;5.41)***% ;11.6409% (;5.27)***% ;4.1568% (;2.23)***%
Industry% Yes% Yes% Yes% Yes% Yes% Yes%
N% 4,201% 1,908% 2,293% 8,141% 3,937% 4,204%
R2% 0.0225% 0.0306% 0.0361% 0.0164% 0.0218% 0.0214%
**%significant%at%the%0.1%level% ***%significant%at%the%0.05%level%
6. Robustness+checks+
!For!the!regressions!run!in!the!results!section,!several!robustness!checks!have!been! performed.!First!is!the!test!for!heteroscedasticity,!using!the!White!standard!errors! test.! With! a! chi;squared! value! of! 396.79! for! the! original! regression,! the! null! hypothesis! of! constant! variance! is! rejected.! Thus,! there! is! significant! evidence! of! heteroscedasticity.! The! heteroscedasticity! tests! for! the! subsample! regressions! also! reject!the!null!hypothesis!of!constant!variance!and!thus!show!significant!evidence!of! heteroscedasticity.! The! regressions! have! been! redone! by! using! robust! standard! errors! and! these! are! the! results! presented! in! the! tables.! The! coefficients! of! the! variables!have!not!changed,!but!using!robust!standard!errors!changes!the!t;statistics! and!in!result!several!variables!have!become!significant!or!lost!their!significance!by! using! this! method! (Brooks,! 2008).! The! most! important! variables! in! this! study,! Z; score,! derivatives! usage! and! the! interaction! effect! between! these! two! variables,! have!increased!their!significance!by!using!robust!standard!errors!(though!in!the!case! of!derivatives!usage,!not!always!to!a!significant!value).!Using!robust!standard!errors! has!not!changed!the!results!and!interpretation.!
!
Also! tested! is! the! level! of! multicollinearity,! which! appeared! to! be! an! issue! when! looking!at!table!2.!The!correlations!presented!in!this!table!showed!high!correlations! for! various! independent! variables.! Multicollinearity! has! been! tested! using! the! variance!inflation!factors!(VIF)!for!the!independent!variables!test.!The!results!show! that!the!independent!variables!all!have!VIF!scores!between!1.02!and!1.42,!which!is! generally!considered!a!sign!that!multicollinearity!is!not!present!(O’Brien,!2007).!This! result! shows! that! the! variables! in! the! regression! are! not! correlated! in! a! way! that! would!cause!problems!to!the!regression!and!its!results.!
!
Taking! the! analysis! a! step! further,! this! study! also! compares! the! use! of! foreign! exchange! derivatives! between! firms! that! have! low! Z;scores! (i.e.,! firms! with! high! probability!of!financial!distress)!and!firms!that!have!high!Z;scores!(i.e.,!firms!with!low!
been!found!by!examining!the!annual!reports!of!the!firms!in!the!sample.!As!it!would! be!too!time;consuming!to!go!through!the!annual!reports!of!all!the!firms!in!the!study,! a!sample!of!84!firms!has!been!selected.!43!Of!these!firms!have!Z;scores!below!2.0! (i.e.,! these! firms! are! in! the! danger! zone! or! grey! area)! and! 41! firms! have! Z;scores! above!3.0!(i.e.,!these!firms!are!in!the!safety!zone).!In!order!to!ensure!comparability,! the!sample!has!been!taken!from!firms!in!the!same!general!industry!(manufacturing)! and! data! has! been! used! from! the! year! 2012! only.! Quantitative! data! on! notional! amounts! of! foreign! exchange! derivative! use! has! been! collected! as! well! as! information!on!the!types!of!derivatives!used.!!
!
A! two;sample! t;test! has! been! performed,! with! the! groups! being! determined! by! Z; scores.! The! results! comparing! the! two! samples! have! been! reported! in! table! 7! (column! 1).! The! two! samples! show! to! be! similar! in! terms! of! (absolute)! exposure,! market!to!book!value,!R&D!value,!level!of!foreign!sales!to!total!sales!and!value!of! foreign!exchange!derivatives.!This!means!that,!in!this!subsample,!firms!with!a!high! possibility! of! financial! distress! on! average! use! the! same! value! of! foreign! currency! derivatives! as! firms! with! low! probabilities! of! financial! distress.! ! This! enforces! the! results! presented! in! the! results! section,! that! derivatives! usage! decreases! foreign! exchange! exposure.! This! result! does! not! support! the! hypothesis! that! derivatives! usage!by!firms!in!financial!distress!increases!exposure!to!foreign!exchange!rate!risks.! !
However,! the! data! itself! is! more! interesting.! Of! the! sample! of! firms! with! Z;scores! under! 2.0,! over! 70%! used! foreign! currency! derivatives! to! hedge! foreign! exchange! exposures!in!2012!(as!reported!in!the!annual!reports).!In!the!other!sample!with!Z; scores!over!3.0,!only!42%!used!foreign!currency!derivatives!to!hedge.!This!difference! in! the! use! of! foreign! currency! derivatives! is! significant,! as! indicated! in! table! 7! (column! 1).! A! previous! study! by! Purnanandam! (2008)! has! studied! this! effect! for! derivative! usage! by! firms! in! financial! distress.! His! study! shows! that! financially! distressed!firms,!especially!in!concentrated!industries,!have!more!incentive!to!hedge! exposures!and!in!turn!make!more!use!of!derivatives.!!
The! two! subsamples! have! also! been! compared! using! only! those! that! use! foreign! currency!derivatives!(table!7,!column!2).!We!see!even!clearer!that!the!two!groups!do! not! differ! in! the! value! of! the! foreign! currency! derivatives! they! use,! although! the! difference! in! exposures! is! slightly! higher! (but! not! significantly! so).! From! the! data! collected! we! see! that! all! companies! that! hedge! foreign! currency! derivatives! used! foreign!exchange!forward!contracts!to!accomplish!this!and!several!additionally!used!
Table+7+–+Comparison+of+foreign+exchange+derivatives+use+in+subsample+
This!table!shows!the!results!of!the!Two;sample!t;test!with!equal!variances!for!the! comparison! of! foreign! exchange! derivative! use! between! firms! with! Z;scores! indicating! a! probability! of! financial! distress! (Z;score! <! 2.0)! and! firms! with! Z;scores! not!indicating!a!probability!of!financial!distress!(Z;score!>!3.0).!The!means!have!been! compared!for!the!variables!used!in!this!thesis,!and!additionally!also!on!the!value!of! foreign!currency!derivatives!used!as!stated!in!the!firms’!annual!reports!of!2012.!The! null! hypothesis! has! been! defined! as! the! difference! between! the! two! means! being! equal!to!zero,!with!the!alternative!hypothesis!that!the!means!are!not!equal!to!zero.! The! first! column! (Subsample)! shows! the! t;statistics! for! the! entire! subsample! (84! firms),!whereas!the!second!column!shows!the!t;statistics!for!only!those!firms!in!the! subsample!that!use!foreign!exchange!derivatives.! ! ! Subsample! Subsample!only!FX!derivatives! Abs(exposure)! ;1.3619! ;1.6525! PB! ;0.9455! ;0.7280! CapEx! 2.6842***! 1.2714! R&D! ;0.7326! 0.3593! ForTS! ;0.8746! 0.9969! Lev! ;7.1710***! ;4.0299***! SM! ;4.4126***! ;3.2287***! Size! 3.4654***! 4.0544***! FXforward(value)! ;1.1039! ;0.4388! FXforward(usage)! ;2.7512***! ! ! ***!significant!at!the!0.05!level! ! ! ! ! ! !
7. Conclusion+
!This! thesis! has! studied! whether! firms! with! high! probabilities! of! financial! distress! increase! their! foreign! exchange! exposure,! while! using! derivatives.! Data! has! been! collected! from! U.S.! firms! trading! on! the! NYSE! and! NASDAQ! in! the! period! 2004! to! 2013.! This! data! was! first! used! to! construct! Z;scores,! indicating! the! probability! of! financial!distress,!for!each!firm!in!each!year.!Next,!the!exchange!rate!exposure!was! determined! based! on! a! model! including! index! returns! and! interest! rates.! The! absolute!value!of!this!exposure!was!then!used!as!the!dependent!variable!in!the!final! regression.! This! regression! included! the! variables! Z;score,! market;to;book! value,! capital! expenditures,! R&D! expenses,! foreign! sales,! leverage,! sales! to! market! capitalization,!firm!size,!derivative!usage!and!10!industry!dummies.!! ! When!looking!at!the!Z;scores,!we!see!that!exposure!to!exchange!rate!risk!becomes! larger!as!the!probability!of!financial!distress!becomes!more!prominent.!This!is!in!line! with!the!results!in!a!previous!study!by!Starks!and!Wei!(2013).!The!results!show!that! in!the!overall!sample!of!firms,!derivative!usage!decreases!exchange!rate!exposure.! This! is! to! be! expected,! as! derivatives! are! generally! used! to! hedge! these! types! of! exposure.!Previous!studies!have!shown!that!firms!use!foreign!currency!derivatives!to! hedge!their!exposures!to!exchange!rate!risks,!not!to!speculate!with!these!derivatives! (Allayannis! and! Ofek,! 2001).! When! the! analysis! went! more! in;depth! to! derivatives! use!by!firms!with!high!probabilities!of!financial!distress,!the!result!was!significant!but! not! in! the! direction! expected! by! risk;shifting! theory.! The! hypothesis! formulated! in! this! thesis! was! that! derivatives! usage! by! firms! in! financial! distress! would! increase! their! foreign! exchange! exposure! due! to! risk;shifting.! The! results! show! that! the! opposite! happens;! firms! with! high! probabilities! of! financial! distress! are! able! to! reduce! their! exposures! to! foreign! exchange! risk! with! the! use! of! derivatives.! This! indicates! that! these! firms! do! not! use! derivatives! to! speculate! and! in! turn! do! not! increase!their!risk.!Thus,!the!results!from!the!study!by!Allayannis!and!Ofek!(2001)!are! valid! in! this! thesis! as! well.! We! can! conclude! that! firms! in! financial! distress! do! not! change!their!hedging!strategy!to!speculate!on!derivatives,!but!instead!use!them!to!
!
However,!there!appears!to!be!a!large!difference!in!foreign!exchange!derivative!usage! between!firms!with!low!and!high!Z;scores.!Firms!with!high!probabilities!of!financial! distress! make! more! use! of! foreign! exchange! derivatives! than! firms! with! low! probabilities! of! financial! distress.! This! is! apparent! in! an! in;depth! analysis! of! a! subsample! of! the! firms! in! the! study.! In! this! subsample,! approximately! half! had! Z; scores! in! 2012! below! 2.0,! while! the! other! half! had! Z;scores! above! 3.0.! The! two! samples! were! taken! from! the! same! general! industry! (manufacturing)! and! were! similar!in!terms!of!exposure!and!market;to;book!value.!Here!we!concluded!that!70%! of! the! firms! with! high! probabilities! of! financial! distress! used! derivatives! to! hedge! against!foreign!exchange!exposures,!while!the!same!held!true!for!only!42%!of!the! firms!with!low!probabilities!of!financial!distress.!However,!the!notional!values!of!the! foreign!exchange!derivatives!used!on!average!did!not!significantly!differ!between!the! two! groups.! The! results! have! shown! that! these! foreign! exchange! derivatives! were! used! to! decrease! exposure! to! foreign! exchange! rate! risk,! even! for! firms! with! high! probabilities!of!financial!distress.!This!is!in!line!with!previous!results!from!a!study!by! Alliyannis! and! Ofek! (2001),! who! find! that! firms! use! derivatives! to! hedge! against! foreign!exchange!exposure.!Increasing!risk,!as!stated!in!the!hypothesis,!would!have! implied!speculation!with!derivatives,!which!is!not!supported!by!the!results.!
!
Analysis! was! also! done! by! comparing! positive! and! negative! exposures.! Assuming! positive! exposures! indicate! net! exporters! and! negative! exposures! indicate! net! importers,! the! results! indicate! that! net! exporters! with! higher! probabilities! of! financial!distress!(i.e.,!lower!Z;scores)!are!less!exposed!to!exchange!rate!risk!than!net! exporters! with! higher! Z;scores,! whereas! net! importers! with! higher! likelihoods! of! financial!distress!experience!more!exchange!rate!exposure!than!net!importers!with! higher!Z;scores.!The!use!of!derivatives!by!either!net!importers!or!net!exporters!does! not!significantly!influence!this!result.! ! Overall,!the!results!do!not!support!the!theory!that!firms!with!high!probabilities!of! financial!distress!that!use!derivatives!are!more!exposed!to!foreign!exchange!rate!risk! than!firms!in!similar!situations!that!do!not!use!derivatives.!In!fact,!derivative!usage!
significantly!reduces!exposure!levels!when!taking!financial!distress!probabilities!into! account.!The!risk;shifting!theory!on!which!the!hypothesis!was!based!has!not!been! proven!in!this!study.!!
!
Limitations! of! this! research! include! that! in! the! main! regressions,! many! of! the! variables!did!not!significantly!affect!exposure!levels.!In!addition,!data!on!the!use!of! foreign!exchange!derivatives!use!is!not!readily!available.!It!was!only!possible!for!a! subsample!of!firms!to!go!through!the!annual!reports!to!find!which!derivatives!were! used!and!for!which!amounts.!Future!research!should!focus!in!this!area,!as!primitive! analysis! on! this! subsample! already! showed! some! interesting! results.! This! research! should!focus!on!the!difference!in!types!of!derivatives!used,!as!the!small!subsample! showed!that!firms!with!high!probabilities!of!financial!distress!use!a!larger!variety!of! derivatives! hedging! than! firms! with! low! probabilities! of! financial! distress.! Additionally,! studies! with! larger! samples! should! also! look! into! why! financially! distressed! firms! seem! to! make! more! use! of! derivatives! to! hedge! against! foreign! exchange!exposures!than!healthy!firms.!
8. Appendix+
!The!exposure!to!exchange!rate!risk!has!been!determined!by!using!the!methodology! described! by! Choi! and! Prasad! (1995)! and! shown! in! the! methodology! section! with! equation!(2).!Individual!firms’!exposure!to!foreign!exchange!rates!are!determined!by! regressing!stock!returns!on!a!monthly!basis!on!the!change!in!the!US!dollar!exchange! rate!index!against!major!currencies,!the!return!on!the!equally!weighted!return!of!the! CRSP!index!and!the!real!interest!rate!(Starks!and!Wei,!2013).!The!real!interest!rate!is! determined!by!subtracting!the!monthly!inflation!rate!from!the!one;month!T;bill.!This! gives!us!the!coefficient!of!interest,!the!exposure!to!foreign!exchange!rates,!on!a!firm! and!yearly!basis.! ! Some!general!statistics!on!the!estimates!of!foreign!exposure!are!given!in!table!8.!This! table! shows! frequency! and! means! for! all! firms! based! on! real! exposures,! absolute! exposures,! negative! exposures! and! positive! exposures,! and! also! subdivided! on! the! basis!of!Z;scores.!From!this!table!it!is!clear!to!see!why!absolute!exposures!are!used!in! the! regression,! as! positive! and! negative! exposures! would! cancel! each! other! out! if! true!values!were!used.!We!see!that!the!value!of!absolute!exposures!increases!as!we! look! at! firms! with! high! probabilities! of! financial! distress! (Z;scores! under! 3.0! and! under!1.81).!Negative!exposures!decrease!with!higher!probability!of!financial!distress! (i.e.,!less!exposure!to!exchange!rate!risk)!if!only!negative!exposures!are!taken!into! account,!but!positive!exposures!increase!with!higher!probability!of!financial!distress! (i.e.,!more!exposure!to!exchange!rate!risk)!if!only!positive!exposures!are!taken!into! account.!! ! ! !
Table+8+–+Exposure+values+of+firms+in+study+
This! table! shows! the! exposure! values! for! the! firms! in! this! thesis.! Individual! firms’! exposure!to!foreign!exchange!rates!are!determined!by!regressing!stock!returns!on!a! monthly! basis! on! the! change! in! the! US! dollar! exchange! rate! index! against! major! currencies,!the!return!on!the!equally!weighted!return!of!the!CRSP!index!and!the!real! interest!rate!(Starks!and!Wei,!2013).!The!first!column!(Nominal!exposures)!gives!the! frequency!and!means!of!the!nominal!exposure!values,!the!second!column!(Absolute! exposures)!gives!the!frequency!and!mean!of!absolute!values!of!the!exposures!and!in! column!3!(Negative!exposures)!and!column!4!(Positive!exposures)!only!negative!and! positive!exposures!are!taken!into!account,!respectively.!A!further!subdivision!is!made! based! on! the! Z;scores.! Z;scores! under! 3.0! indicate! firms! with! probabilities! of! financial! distress! in! the! grey! area! and! danger! zone,! whereas! Z;scores! under! 1.81! indicate!firms!with!high!probabilities!of!financial!distress!in!the!danger!zone.! ! ! ! Nominal! exposures! Absolute! exposures! Negative! exposures! Positive! exposures! All!firms! Freq.! 12,348! 12,348! 5,847! 6,501! Mean! ;0.8961! 20.1402! ;22.2128! 18.2762! ! ! ! ! ! ! Z;score! under!3.0! Freq.! 4,634! 4,634! 2,209! 2,425! Mean! ;0.7339! 25.5590! ;27.5783! 23.7195! ! ! ! ! ! ! Z;score! over!3.0! Freq.! 7,714! 7,714! 3,638! 4,076! Mean! ;0.9935! 16.8850! ;18.9548! 15.0377! ! ! ! ! ! ! Z;score! under!1.81! Freq.! 2,293! 2,293! 1,094! 1,199! Mean! ;2.8078! 30.7578! ;35.1764! 26.7262! ! ! ! ! ! ! Z;score! over!1.81! Freq.! 10,055! 10,055! 4,753! 5,302! Mean! ;0.4601! 17.7189! ;19.2290! 16.3652!
9. References+
! Allayannis,!G.,!&!Ofek,!E.!(2001).!Exchange!rate!exposure,!hedging,!and!the!use!of! foreign!currency!derivatives.!Journal(of(international(money(and(finance,!20(2),!273; 296.! !Altman,! E.! I.! (1968).! Financial! ratios,! discriminant! analysis! and! the! prediction! of! corporate!bankruptcy.!The(journal(of(finance,!23(4),!589;609.!
!
Altman,! E.! I.,! Haldeman,! R.! G.,! and! Narayanan,! P.! (1977).! ZETA™! analysis! A! new! model!to!identify!bankruptcy!risk!of!corporations.!Journal(of(Banking(&(Finance,!1(1),! 29;54.!!
!
Altman,! E.! I.! (1984).! A! further! empirical! investigation! of! the! bankruptcy! cost! question.!The(Journal(of(Finance,!39(4),!1067;1089.!
!
Altman,!E.!I.!(2000).!Predicting!financial!distress!of!companies:!revisiting!the!Z;score! and!ZETA!models.!Stern(School(of(Business,(New(York(University,!9;12.!!
!
Bartram,! S.! M.,! Dufey,! G.,! and! Frenkel,! M.! R.! (2005).! A! primer! on! the! exposure! of! non;financial! corporations! to! foreign! exchange! rate! risk.! Journal( of( Multinational(
Financial(Management,!15(4),!394;413.!!
!
Bartram,! S.! M.,! Brown,! G.! W.,! &! Fehle,! F.! R.! (2009).! International! evidence! on! financial!derivatives!usage.!Financial(management,!38(1),!185;206.!
!
Bartram,! S.! M.,! Brown,! G.! W.,! and! Minton,! B.! A.! (2010).! Resolving! the! exposure! puzzle:!The!many!facets!of!exchange!rate!exposure.!Journal(of(Financial(Economics,!
95(2),!148;173.!
! !
Bodnar,!G.!M.,!and!Marston,!R.!(1996).!1995!Survey!of!derivatives!usage!by!US!non; financial! firms.! George( Weiss( Center( for( International( Financial( Research,( Wharton(
School,(University(of(Pennsylvania.! ! Bodnar,!G.!M.,!and!Gebhardt,!G.!(1999).!Derivatives!Usage!in!Risk!Management!by! US!and!German!Non;Financial!Firms:!A!Comparative!Survey.!Journal(of(International( Financial(Management(&(Accounting,!10(3),!153;187.! ! Bodnar,!G.!M.,!Dumas,!B.,!and!Marston,!R.!C.!(2002).!Pass;through!and!Exposure.!The( Journal(of(Finance,!57(1),!199;231.!! ! Bodnar,!G.!M.,!and!Wong,!M.!F.!(2003).!Estimating!exchange!rate!exposures:!issues! in!model!structure.!Financial(Management,!35;67.! ! Brooks,!C.!(2008).!Introductory(econometrics(for(finance.!Second!Edition.!Cambridge! university!press.! ! Cho,!S.,!and!Song,!M.!K.!(2011).!Foreign!Exchange!Exposures!of!Korean!Firms.!Journal( of(East(Asian(Economic(Integration,!15(1),!55;86.! ! Choi,!J.!J.,!and!Prasad,!A.!M.!(1995).!Exchange!risk!sensitivity!and!its!determinants:!a! firm!and!industry!analysis!of!US!multinationals.!Financial(Management,!24(3),!77;88.! ! Cutler,!D.!M.,!&!Summers,!L.!H.!(1989).!The!costs!of!conflict!resolution!and!financial! distress:! Evidence! from! the! Texaco;Pennzoil! litigation.! Rand( Journal( of( Economics,(
19(2),!157;172.!
!
Danielova,! A.! N.,! Sarkar,! S.,! and! Hong,! G.! (2013).! Empirical! Evidence! on! Corporate! Risk;Shifting.!Financial(Review,!48(3),!443;460.!
!
Dominguez,! K.! M.,! and! Tesar,! L.! L.! (2006).! Exchange! rate! exposure.! Journal( of( International(Economics,!68(1),!188;218.!! ! Dumas,!B.!(1978).!The!theory!of!the!trading!firm!revisited.!The(Journal(of(Finance,! 33(3),!1019;1030.!! ! Eisdorfer,!A.!(2008).!Empirical!evidence!of!risk!shifting!in!financially!distressed!firms.! The(Journal(of(Finance,!63(2),!609;637.!! ! Eisdorfer,!A.!(2009).!Convertible!debt!and!risk;shifting!incentives.!Journal(of(Financial( Research,!32(4),!423;447.! !
Eisdorfer,! A.! (2010).! Risk;shifting! and! investment! asymmetry.! Finance( Research(
Letters,!7(4),!232;237.!
!
Griffin,!J.!M.,!and!Stulz,!R.!M.!(2001).!International!competition!and!exchange!rate! shocks:! a! cross;country! industry! analysis! of! stock! returns.! Review( of( Financial(
Studies,!14(1),!215;241.!! ! Hung,!J.!(1992).!Assessing!the!exchange!rate's!impact!on!US!manufacturing!profits.! Quarterly(ReviewWFederal(Reserve(Bank(of(New(York,!17,!44;44.!! ! Jensen,!M.!C.,!and!Meckling,!W.!H.!(1976).!Theory!of!the!firm:!Managerial!behavior,! agency!costs!and!ownership!structure.!Journal(of(financial(economics,!3(4),!305;360.! !
Jarrow,! R.! A.,! &! Oldfield,! G.! S.! (1981).! Forward! contracts! and! futures! contracts.!
Journal(of(Financial(Economics,!9(4),!373;382.!
!
Jorion,! P.! (1990).! The! exchange;rate! exposure! of! US! multinationals.! Journal( of(
Business,!331;345.!
