Modeling exchange rate exposure in the Japanese industrial sectors

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1 Ed Cowan Unversy Researc Onlne ECU Publcaons 0 0 Modelng excange rae exposure n e Japanese ndusral secors P. Jayasnge A Tsu Zaoyong Zang Ed Cowan Unversy Ts arcle was orgnally publsed as: Jayasnge, P., Tsu, A., & Zang, Z. (0). Modelng excange rae exposure n e Japanese ndusral secors. Paper presened a e 9 Inernaonal Congress on Modellng and Smulaon. Ausralan Maemacal Scences Insue. Per, Ausrala. Orgnal arcle avalable ere Ts Conference Proceedng s posed a Researc Onlne. p://ro.ecu.edu.au/ecuworks0/650

2 9 Inernaonal Congress on Modellng and Smulaon, Per, Ausrala, 6 December 0 p://mssanz.org.au/modsm0 Modelng excange rae exposure n e Japanese ndusral secors P. Jayasngea, A.K. Tsu b and Z.Y. Zangc a Deparmen of Busness Economcs, Unversy of Colombo, Sr Lanka Deparmen of Economcs, Naonal Unversy of Sngapore, Sngapore c Scool of Accounng, Fnance & Economcs, Ed Cowan Unversy, Ausrala Emal: zaoyong.zang@ecu.edu.au b Absrac: In recen years e volaly of excange rae exposure and s assocaed rsk ave become a o ssue n nernaonal fnancal managemen. I s ofen assumed a a frm s fuure operang cas flows s proxed by s marke value, and e exposure coeffcen would be able o effcenly measure e mpac of excange rae canges on a frm s reurn and s sensvy o e canges. Recenly, some sudes begn o nvesgae weer excange rae exposure s asymmerc beween currency apprecaons and deprecaons. By far mos exsng sudes on excange rae exposure assume a e varances of a frm s reurns and excange raes canges are me-nvaran. In s paper, we assess emprcally e valdy of s assumpon, and argue a e convenenly defned excange rae exposure s nadequae for measurng e enre mpac of excange rae canges on a frm s fuure operang cas flows n cases of me-varyng varances. Tere are a leas four alernave roues roug wc a frm s reurns are exposed o foregn excange rsks wen e varances are me-varan. Te four aspecs of excange rae exposure or e mul-elemens of excange rae exposure are defnes as follows: e frs roue s a a frm s sock reurns are exposed o e excange rae canges eer drecly or ndrecly roug s busness lnkages w oer frms. e second roue capures e exposure o e volaly of excange rae canges, namely, e sensvy of a frm s value o e degree of flucuaons of excange raes. If e degree of flucuaons s me-varyng, e frm may reac o cange s markeng, producon locaon and edgng sraeges. e rd level of excange rae exposure measures e sensvy of condonal varance of e reurns o e volaly of excange rae canges. Even f e second relaonsp s absen, as long as e condonal varances of reurns are exposed o volaly of excange rae canges and e reurns are sensve o s own volaly canges, ere sll exss e possbly of an ndrec mpac of excange rae volaly on reurns. As a consequence, e frm may ave o re-assess and even cange s curren busness sraeges wc may n urn affec s profably. Te four roue ndcaes e me-varyng condonal correlaon beween reurns and excange rae canges, roug wc e dynamcs of a frm s excange rae exposure wll be capured. We employ e bvarae GJR-GARCH-M models o nvesgae e four aspecs of excange rae exposure, by usng daa of e daly ndusral ndexes of en secors n Japan durng e perod from 99 o 000. Te resuls ndcae a ere are cases wc are no exposed o currency rsk under e convenonal measure (exposure coeffcen), bu sgnfcanly exposed o currency rsk roug e alernave roues denfed we fnd sgnfcan evdence of suc excange rae exposure wc s no capured by e convenonal measure. Te dagnosc sascs confrm e adequacy of our model, and ence e robusness of e resuls. Keywords: Excange rae exposure; volaly spllovers; mulvarae GARCH-M models; me-varyng 56

3 Jayasnge e al., Modelng Excange Rae Exposure n e Japanese Indusral Secors. INTRODUCTION In recen years e volaly of excange rae exposure and s assocaed rsk ave become a o ssue n nernaonal fnancal managemen. Excange rae exposure s emprcally defned as e cange n a frm s fuure operang cas-flows n response o canges n excange raes. I s ofen assumed a a frm s fuure operang cas flows s proxed by s marke value, and e exposure coeffcen would be able o effcenly measure e mpac of excange rae canges on a frm s reurn and s sensvy o e canges (Adler and Dumas, 984). Recenly, Kanas (997) and Koumos and Marn (003) nvesgae weer excange rae exposure s asymmerc beween currency apprecaons and deprecaons. Kanas (000), and Gurda and Tzavala (004) analyse asymmery n volaly of sock reurns relaed o excange rae exposure a counry level. Alou (007) explores e naure of e mean, volaly and causaly ransmsson mecansm beween sock and foregn excange markes for e Uned Saes and some European markes. Ragavan and Dark (008) use a Vecor Auoregressve GARCH (VAR-GARCH) model o examne e reurn and volaly spllover effecs beween e US dollar/ausralan dollar excange rae and e Ausralan All Ordnares Index (AOI). By far mos exsng sudes on excange rae exposure assume a e varances of a frm s reurns and excange raes canges are me-nvaran. In s paper, we assess emprcally e valdy of s assumpon, and argue a e convenenly defned excange rae exposure s nadequae for measurng e enre mpac of excange rae canges on a frm s fuure operang cas flows n cases of me-varyng varances. Tere are a leas four alernave roues roug wc a frm s reurns are exposed o foregn excange rsks wen e varances are me-varan, as llusraed n Fgure. In s paper, we employ a bvarae GARCH-ype model o nvesgae e aforemenoned sensves of excange rae exposure by usng daly ndusral ndexes of en secors n Japan durng e perod from 99 o 000. Te resuls ndcae a ere are cases wc are no exposed o currency rsk under e convenonal measure (exposure coeffcen), bu sgnfcanly exposed o currency rsk roug e alernave roues denfed n Fgure. Te res of s paper s organzed as follows. Secon dscusses e eorecal framework and meodology used n s sudy. In secon 3 we dscuss brefly e daases used n our sudy and analyze e emprcal resuls. Some concludng remarks are gven n Secon 4.. METHODOLOGY AND THE MODEL Te frs movemen of excange rae exposure as been orougly dscussed n e leraure durng e las wo decades (among oers, see Adler and Dumas, 984; Joron, 990). Te augmened marke model s ofen used o esmae e excange rae exposure coeffcens n e mean equaon as follows: r, a0 + amrm, + axr + ξ,,,... n, () and ξ ~ N( 0 σ ),, were r, s reurns on frm s sock a me ; r m, s reurns on marke porfolo a me ; r x, s canges n excange rae a me. Here e excange rae s expressed as e local currency prce of one un of e foregn currency; a m s frm s exposure o marke reurns; a x s frm s excange rae exposure coeffcen wc measures e sensvy of a frm s reurns o e excange rae movemens; and ξ, s e regresson resdual wc s assumed o follow a normal dsrbuon w zero mean and consan varance. Te major problem of e augmened marke approac s e quesonable assumpon of me-nvarance n e varance of frm s reurn and n canges of excange rae. In recen years, as become common o use generalzed auoregressve condonal eeroskedascy (GARCH)-ype models o accommodae e mevaryng volaly n emprcal sudes of excange rae canges. Te condonal volaly leraure as been Mean Condonal varance Condonal correlaon Frm value [e] Reurns Volaly of Oer frms w wc as l k [a] [b] [c] [d] Excange rae Canges n Volaly of Fgure. Mul-elemens of excange rae 56

4 Jayasnge e al., Modelng Excange Rae Exposure n e Japanese Indusral Secors dscussed exensvely n recen years (see, for example, L, Lng and McAleer, 00; McAleer, 005; and McAleer, Can and Marnova, 007). In s sudy we employ a me-varyng condonal correlaon bvarae GJR-GARCH(,)-M model (Glosen e al., 993) o capure e four elemens of excange rae exposure of secoral reurns. Accordng o Engle e al. (987), as e degree of rsk assocaed w e reurns on asses s lkely o vary over me, e compensaon requred by rsk averse nvesors for oldng suc asses mus also be me-varyng, wc was ence ncorporaed no er asse prcng models w a GARCH-n-mean erm. Ts provdes some jusfcaon for our coce of e GJR-GARCH models. Te ypcal specfcaon underlyng e bvarae condonal mean and condonal varance n reurns are gven as follow: ( x ), + q r, a0 + amrm, + ax r + a j k r, k + ag ε, k ;,,... n () s r b0 + bx lr l + ε l H (3) z ε (4) ε ν I ( ε, ε ) I ~ f ( ε I ), + α ε, + γ d, ε, + β, + α ε + γ d ε ω (5) x + α xε + γ xd ε + β x ω (6) ( ) ρ (7), were r, s reurns on secoral ndex a me ; r m, s reurns on marke ndex a me ; r x, s e log dfference n excange rae a me. In addon, ε s a x vecor of e daly socks of ( ε, ε ) a me par-wse w eac secor. And ε I denoe e x vecor of random socks a me gven all avalable nformaon a me ( ). We assume a follows a bvarae -dsrbuon w ν degrees of freedom, zero mean and condonal varance H, wc s a x varance-covarance mar. For eac secor, e man dagonal elemens of H are e condonal varances of secoral reurns and canges n excange rae, represened by, and x,, respecvely. Te wo condonal varances are assumed o follow GJR-GARCH(,) srucure gven by equaons (4) and (5), and d u, f ε u, < 0 and zero oerwse for u, x. Fnally, z denoes e sandardzed errors wc are assumed o be ndependenly and dencally dsrbued w mean 0 and varance. Te condonal covarance of secoral reurns and excange rae canges s defned by equaon (7), specfed as e produc of condonal correlaon coeffcen and e square roo of e condonal varance of reurns and excange rae canges. Followng Tse and Tsu (00), we assume a e condonal correlaon beween secoral reurns and excange rae canges s me-varyng, and can be specfed as: ( θ θ ) ρ + θρ + θ ψ ρ (8) ρ As suc, e condonal correlaon a me ( ) s gven by e weged average of me-nvaran componen ( ρ ), s own lag erm n prevous perod ( ρ ) and ψ wc s assumed o be a funcon 563

5 Jayasnge e al., Modelng Excange Rae Exposure n e Japanese Indusral Secors of lagged observaons of sandardzed error z. More specfcally, θ are non-negave and ( θ +θ ). ψ j, M z, j, M M ( z, )( z j, ) z. Bo θ and Assumng a e sandardzed resduals of e suggesed bvarae model are -dsrbued, e condonal log-lkelood of resdual vecor ε a me can be defned as follows: ν + ν ν + ε ( D R D ) ε (9) ( ) ( ( ) ) ϕ ln Γ lnγ ln π υ ln ln + H ν were ϕ s e vecor of parameers o be esmaed; Γ (.) s e Gamma funcon; D s a x dagonal mar wose dagonal elemens are and, ; R s e x condonal correlaon mar wose dagonal elemens conss of ones and off-dagonal elemens are represened by ρ. T Te log-lkelood funcon of e sample s obaned as: L( ) ( ) φ ϕ, were T s e number of observaons. Te parameer vecor ϕ of e bvarae GJR-GARCH-M model s esmaed by maxmzng L w respec o ϕ. All esmaes of e parameers n s paper are obaned by e meod of maxmum lkelood usng programs coded n GAUSS. 3. EMPIRICAL ANALYSIS 3. Daa Descrpon Our daase consss of en ndusral secors of e Japanese economy durng e perod from June, 99 o December, 000, and conans 40 observaons. Te coce of s sample s based on avalably of daa. In selecng e secoral reurns, we focus on level 04 ndusral classfcaon, wc s based on FTSE acuares sysem, avalable n Daasream. We coose 0 ou of e 39 secors wc are reasonably relaed o manufacurng goods, ncludng auomoble and pars (A&P), consrucon and buldng maerals (C&BM), dversfed ndusres (DI), elecrcal and elecronc equpmen (E&EE), engneerng and macnery (E&M), nformaon ecnology and ardware (IT&H), ol and gas (O&G), parmaceucals and boecnology (P&B), sofware and compuer servces (S&CS) and seel and oer meals (S&OM), respecvely. Marke porfolo s assumed o be represened by Nkke 5, e overall sock ndex n Japan. And all secoral reurns and marke reurns are expressed n local currency. Te connuously compounded daly reurns and excange rae canges are compued as follows: Ru, r, ln *00 u, m u Ru, were R u, and R are e closng values of sock prces/excange raes for e radng days and -, u, respecvely. Table dsplays e summary sascs of reurns from e ndusral secors and e marke porfolo represened by Nkke 5. Te ges wo daly reurns are found n IT&H and S&CS, averagng 0.036% and 0.06%, respecvely. Te lowes wo daly reurns are n E&M and S&OM, w negave averages a 0.3% and 0.04%, respecvely. Te mean daly reurn of e marke porfolo s a a loss of 0.03%, w a maxmum gan a 7.66% and a loss a 7.3%, respecvely. Te sandard devaons for reurns from ese ndusral secors range from.086% (P&B) o.063% (S&CS). Ou of ese 4 secors, PC&H and P&B are e leas volale, wle DI and S&CS are e mos volale. Moreover, reurns of e marke porfolo and ose of 3 ou of e 4 ndusral secors are posvely skewed and gly lepokurc w all values of kuross greaer an 3, ereby exceedng e kuross of reurns followng a normal dsrbuon. As all e seres are I () processes, we ave conduced e Joansen conegraon es. Te resuls are no suppor of 564

6 Jayasnge e al., Modelng Excange Rae Exposure n e Japanese Indusral Secors co-negraon beween secoral ndex and e excange rae durng e sample perod, ereby suggesng a e error correcon erms are no requred n e mean equaons. Table : Prelmnary sascs of secoral reurns Secor A&P C&BM DI E&EE E&M IT&H O&G P&B S&CS S&OM Nkke Mean Maxmum Mnmum S D Skewness Kuross Jarque-Bera Q (0) Q (0) Runs Tes ADF (prce) ADF (reurns) Q are Ljung-Box sascs of reurns and squared reurns for 0 lags. Tey follow a χ dsrbuon and e crcal value a e 5% level of sgnfcance w 0 degrees of freedom s 3.4. ADF (prce) and ADF (reurn) represen augmened Dcky Fuller sasc w an nercep for sock prces and reurns, respecvely. Noes: Q ( 0 ) and ( 0 ) 3. Emprcal Resuls Table repors e maxmum lkelood esmaes of e me-varyng condonal correlaon GJR- GARCH(,)-M model. Te resuls ndcae a over alf of e 0 Japanese ndusres are sgnfcanly exposed o excange rae canges n erms of er reurns, mplyng e exsence of e frs momen of excange rae exposure. Te absolue value of esmaed exposure coeffcen represened by a x ranges from n C&BM o 0.5 n O&G, and ere are four cases w e exposure coeffcens beng greaer an 0., wc suggess a reurns n ose secors are relavely gly sensve o e canges n excange rae. I s neresng o noe a reurns n some secors suc as A&P, E&EE and IT&H are posvely relaed o e excange rae canges, mplyng a reurns on suc secors ncrease w e deprecaon of e yen. Ts fndng s conssen w our causal observaon a devaluaon of e currency would favour e exporng secors. Te negave relaonsp beween O&G and excange rae canges can be arbued o Japan s eavy mpor relance n a secor. Aloug lack of all e naural resources, Japan s e world s rd larges ol consumer and second larges energy mporer (EIA, 004). Our fndngs are also conssen w a by Bodnar and Genry (993) and Domnguez (998), wo repor a elecrcal macnery, precson nsrumens and ndusral secors are posvely exposed o excange rae canges wle e energy and ules secors sow e oppose resul. Reurns n e C&BM secor are also found negavely exposed. However, unlke e O&G secor, s dffcul o craf a clear-cu explanaon for s n erms of mpors and expors. Te dffculy s parly due o e dfferen classfcaon sysems used n secoral sock ndexes and mpor/expor daa. On e oer and, s no sensble o solely arbue excange rae exposure of secoral reurns o e aggregaed mpor/expor rade sascs. Regardng e esmaes of e GARCH-M erm, we fnd evdence of volaly of excange rae exposure n ree ou of e en secors. I s also neresng o noe a, oug S&CS and S&OM secors are exposed o e volaly of excange rae, ey are no exposed o e excange rae canges. Te esmaed coeffcen of own GJR erm ( γ ) are sgnfcan a e 5% level and bear e expeced posve sgn n seven ndusral secors ncludng A&P, C&BM, DI, E&M, O&G, P&B and S&OM, suggesng a e leverage effec s a work wen ere s a reducon n secoral reurns. Te resuls confrm e exsence of asymmerc volaly n reurns n ese seven secors. Volaly assocaed w excange rae canges s also found o be asymmerc n fve secors (e resuls are no repored bu avalable upon reques from e auors). 565

7 Jayasnge e al., Modelng Excange Rae Exposure n e Japanese Indusral Secors Table : Maxmum lkelood esmaes for e me-varyng condonal correlaon GJR GARCH(,) M model (yen rade-weged excange rae) Parameer A&P C&BM DI E&EE E&M IT&H O&G P&B S&CS S&OM. a x 0.405*** *** *** 0.077* 0.500*** -0.5*** (6.30) (-3.8) (0.45) (6.57) (.84) (5.80) (-6.9) (-.6) (-0.78) (0.39). a g ** ** ** (-0.5) (.6) (0.95) (0.54) (-0.8) (.3) (-.) (0.49) (.35) (-.0) 3. α *** *** *** 0.076*** *** 0.087*** *** 0.060*** 0.668*** *** (4.3) (3.9) (3.6) (4.08) (3.5) (3.90) (3.09) (.90) (6.7) (4.7) 4. γ ** *** ** *** ** ** ** (.07) (.85) (.99) (0.9) (3.) (.3) (.3) (.97) (.40) (.4) 5. α 0.035* 0.07* 0.597*** ** * ** (.64) (.78) (3.37) (.6) (.30) (0.9) (0.9) (.) (.83) (.5) 6. γ * -0.94*** ** (-0.87) (-.67) (3.5)) (-.37) (-.05) (-0.46) (0.08) (-0.54) (.7) (-.46) 7. β *** 0.879*** 0.974*** 0.909*** 0.900*** *** 0.944*** 0.943*** *** *** (36.3) (35.60) (67.64) (4.8) (46.04) (39.89) (60.33) (39.70) (9.08) (4.47) 8. ρ * *** ** ** ** (.75) (-.58) (-0.6) (3.3) (.03) (.44) (-.09) (-0.9) (-0.7) (-.3) 9. θ 0.997*** *** *** *** *** 0.967*** *** *** NA (63.76) (35.) (4.96) (4.44) (.40) (5.6) (0.35) (47.85) (39.5) 0. θ NA (0.4) (0.95) (0.88) (0.44) (0.04) (0.80) (0.67) (0.8) (0.0). ν 4.96*** 5.400*** 5.667*** *** 6.954*** *** 5.490*** 5.9*** 5.865*** 5.36*** (.87) (.7) (.7) (.80) (0.87) (.83) (.08) (.8) (.33) (.58) Noes: ***, ** and * ndcae %, 5% and 0% levels of sgnfcance, respecvely; Values menoned wn pareneses are relevan -sascs; Te esmaed model consss of e Equaons 3b roug 9. For S&OM, consan correlaon model s used as e me-varyng verson of e suggesed model dd no converge. Excep for e me-varyng correlaon parameers, e resuls from e wo versons of e model are largely smlar and avalable upon reques; NA: No avalable. I s found a e cross squared error ( α ) s posve and sgnfcan a e 5% sgnfcan level n secors DI, E&M and S&OM, and sgnfcan a e 0% sgnfcan level n A&P, C&BM and S&CS. Te resuls confrm e meeorc sower effec n ese ndusral secors, and sugges a an ncrease n e volaly n excange raes wll rase e volaly of secoral reurns. Moreover, e coeffcen of e cross GJR erm ( γ ) s found o be negave and sgnfcan n e secors of DI, E&M and C&BM (row 6 n Table 3), suggesng e asymmerc excange rae exposure of e condonal varance n ese secors. Te mplcaon s a e reurns n ese ree secors are no only gly sensve o e volaly n foregn excange marke, bu also vulnerable o e deprecaon of yen. I s also found a e me-varyng condonal correlaon model converges n nne ndusral secors, of wc e me-nvaran componen of e correlaon ( ρ ) s sgnfcan only n ree cases. Moreover, θ s found gly sgnfcan n eg secors. Tese resuls sugges ere exs wo dfferen paerns of me-varyng condonal correlaon beween Japanese ndusral secors and e excange rae canges. Te frs one s a, aloug e correlaon beween e reurns and excange rae canges are me-varyng n ese secors, me varyng correlaon s more lkely o be dependen on s own pas and less lkely o be dsurbed by e recen canges as refleced n e sandardzed resduals. Te second one s a aloug e me-nvaran componen s no sgnfcan, me-varan componen s sgnfcan, suggesng a e me-nvaran componen alone s no a relable measure of e correlaon beween e wo varables. We ave also esmaed e mul-elemens of excange rae exposure assocaed w a yen-us dollar blaeral excange rae. Te resuls (no repored bu avalable upon reques) are smlar o e one w radeweged. Te dagnosc es and also e Box-Perce es confrm a e non-lnear dependences n almos all e secoral ndexes ave been adequaely capured by e proposed model, and e proposed bvarae GJR-GARCH(,)-M model s adequae for capurng all e four elemens of excange rae exposure of secoral reurns. 4. CONCLUDING REMARKS We employ a bvarae me-varyng condonal correlaon GJR-GARCH(,)-M model o esmae e mul-elemens of excange rae exposure n e en Japanese ndusral secors. We fnd srong evdence for e exsence of all e four elemens of excange rae exposure n e secoral reurns. Te resuls confrm e frs momen exposure o excange rae canges n e s secors, A&P, C&BM, E&EE, E&M, IT&H and O&G, and a e reurns n ree secors (IT&H, S&CS and S&OM) are sgnfcanly exposed o e 566

8 Jayasnge e al., Modelng Excange Rae Exposure n e Japanese Indusral Secors volaly of excange rae canges. Te condonal varances of e reurns n ree secors (DI, E&M and S&OM) are found o be sgnfcanly exposed o e volaly of excange rae canges. Te excange rae exposure of e condonal varances of e reurns n ree secors (DI, E&M and C&BM) are found asymmerc, mplyng a e volaly ncrease n secoral reurns caused by a deprecaon of yen would be greaer an a caused by an apprecaon of e same magnude. We fnd srong evdence a reurns n nne secors are sgnfcanly correlaed w e excange rae canges and e correlaon s me-varyng. In addon, e me-varyng correlaon beween secoral reurns and excange rae canges s more perssen. Ts sudy provde srong evdence suggesng a e commonly employed exposure coeffcen/bea s nadequae o capure e enre mpac of excange rae canges on frms fuure operang cas flows. In e presence of ose oer elemens of excange rae exposure, e enre currency rsk acually faced by a frm/secor s no fully capured by e excange rae exposure coeffcen alone. As suc, akng e convenonal exposure coeffcen as e sole measure of excange rae exposure of frms/secors may provde us w msleadng resuls. Tere are cases wc are no exposed o currency rsk under e convenonal measure, bu are found sgnfcanly exposed o e currency rsk roug e four alernave roues denfed n s paper. Te dagnosc sascs furer confrm e adequacy of our model, and ence e robusness of e resuls. REFERENCES Adler, M. and B. Dumas (984) Exposure o Currency Rsk: Defnon and Measuremen, Fnancal Managemen, 3, pp Alou, C. (007), Prce and volaly spllovers beween excange raes and sock ndexes for e pre- and pos-euro perod, Quanave Fnance 7(6), pp Bodnar, G. M. and W. M. Genry (993) Excange Rae Exposure and Indusry Caracerscs: Evdence from Canada, Japan and e USA, Journal of Inernaonal Money and Fnance,, pp Domnguez, K. M. E. (998) Te Dollar Exposure of Japanese Companes, Journal of e Japanese and Inernaonal Economes,, pp EIA (004) Counry Analyss Brefs: Japan, Energy Informaon Admnsraon p:// Engle, R. F., D. M. Llen and R. P. Robns (987) Esmang Tme-Varyng Rsk Prema n e Tme Srucure: Te ARCH-M Model, Economerca, 55(), pp Gurda, F. and E. Tzavala (004), Is e Currency Rsk Prced n Equy Markes?, Workng Paper # 5, Deparmen of Economcs, Queen Mary Unversy of London Glosen, L., R. Jegannaan and D. Runkle (993) On e Relaon beween e Expeced Value and Volaly of Nomnal Excess Reurn on Sock, Journal of Fnance, 46, pp Joron, P. (990) Te Excange Rae Exposure of U.S. Mulnaonals, Journal of Busness, 63, pp Kanas, A. (997) Is Economc Exposure Asymmerc beween Long-Run Deprecaons and Apprecaons? Tesng Usng Conegraon Analyss, Journal of Mulnaonal Fnancal Managemen, 7, pp. 7-4 Kanas, A. (000), Volaly Spllovers beween Sock Reurns and Excange Rae Canges, Journal of Busness and Fnance and Accounng, 7 (3), Aprl/May, pp Koumos, G. and A. D. Marn (003) Frs and Second Momen Excange Rae Exposure: Evdence from U.S. Sock Reurns, Te Fnancal Revew, 38, pp L, W.K., S. Lng and M. McAleer (00), Recen eorecal resuls for me seres models w GARCH errors, Journal of Economc Surveys, 6, McAleer, M. (005), Auomaed nference and learnng n modelng fnancal volaly, Economerc Teory,, 3-6. McAleer, M., F. Can and D. Marnova (007), An economerc analyss of asymmerc volaly: eory and applcaon o paens, Journal of Economercs, 39, Ragavan, M. and J. Dark (008) Reurn and Volaly Spllovers Beween e Foregn Excange Marke and e Ausralan All Ordnares Index, Te ICFAI Journal of Appled Fnance 4, pp Tse, Y. K. and A. K. Tsu (00) A Mulvarae GARCH Model w Tme-Varyng Correlaons, Journal of Busness and Economc Sascs, 0, pp