Universiy of Connecicu DigialCommons@UConn Economics Working Papers Deparmen of Economics 9-1-00 Currency Depreciaion and Korean Sock Marke Performance during he Asian Financial Crisis WenShwo Fang Feng Chia Universiy Sephen M. Miller Universiy of Nevada and Universiy of Connecicu Follow his and addiional works a: hp://digialcommons.uconn.edu/econ_wpapers Recommended Ciaion Fang, WenShwo and Miller, Sephen M., "Currency Depreciaion and Korean Sock Marke Performance during he Asian Financial Crisis" (00). Economics Working Papers. Paper 0030. hp://digialcommons.uconn.edu/econ_wpapers/0030 This is brough o you for free and open access by he Deparmen of Economics a DigialCommons@UConn. I has been acceped for inclusion in Economics Working Papers by an auhorized adminisraor of DigialCommons@UConn. For more informaion, please conac digialcommons@uconn.edu.
Deparmen of Economics Working Paper Series Currency Depreciaion and Korean Sock Marke Performance during he Asian Financial Crisis WenShwo Fang Feng Chia Universiy Sephen M. Miller Universiy of Nevada and Universiy of Connecicu Working Paper 00-30 Sepember 00 341 Mansfield Road, Uni 1063 Sorrs, CT 0669 1063 Phone: (860) 486 30 Fax: (860) 486 4463 hp://www.econ.uconn.edu/
Absrac Srucural shifs characerize he volailiy of he Korean sock and foreign exchange markes during he 1997 Asian financial crisis. This paper employs an unresriced bivariae GARCH-M model of sock marke reurns o invesigae empirically he effecs of daily currency depreciaion on Korean sock marke reurns. The evidence shows ha currency depreciaion significanly affecs sock marke performance hrough hree disinc channels: exchange rae depreciaion adversely affecs sock marke reurns, higher exchange rae depreciaion volailiy induces higher sock marke reurns, and exchange rae depreciaion volailiy raises sock marke reurn volailiy. The evidence suggess ha small open sock markes are vulnerable o exchange rae movemens.
Currency Depreciaion and Korean Sock Marke Performance during he Asian Financial Crisis Absrac Srucural shifs characerize he volailiy of he Korean sock and foreign exchange markes during he 1997 Asian financial crisis. This paper employs an unresriced bivariae GARCH-M model of sock marke reurns o invesigae empirically he effecs of daily currency depreciaion on Korean sock marke reurns. The evidence shows ha currency depreciaion significanly affecs sock marke performance hrough hree disinc channels: exchange rae depreciaion adversely affecs sock marke reurns, higher exchange rae depreciaion volailiy induces higher sock marke reurns, and exchange rae depreciaion volailiy raises sock marke reurn volailiy. The evidence suggess ha small open sock markes are vulnerable o exchange rae movemens. I. INTRODUCTION Modern heories of asse allocaion argue ha invesor s rade-off expeced reurn and riskiness (volailiy). In an early sudy, Chou (1988) argues ha high sock marke volailiy in 1974 caused he drop in he U.S. sock marke, and poins o he imporance of idenifying he sources of volailiy. Sock marke volailiy can reflec changes in money supply and oil prices (Engle and Rodrigues, 1989) and changes in delivery and paymen erms (Baillie and DeGennaro, 1989). While asse allocaion frequenly occurs wihin a counry, some invesors, however, allocae porfolios across asses in differen counries. Inernaional asse allocaion mus consider he addiional complicaion of currency conversion. Thus, exchange rae risk (volailiy) provides an addiional channel whereby an asse s expeced reurn rades-off wih riskiness (volailiy). Such 1
concern is heighened in small open economies where he sock marke is small, or emerging. The Asian financial crisis provides an experimen where exchange rae riskiness (volailiy) may have helped deermine he shor-run sock-marke movemens. This paper invesigaes he effecs of daily currency depreciaion on sock marke reurns during he Korean financial urmoil of 1997 o 000. Afer paricipaing in he Eas Asian miracle (World Bank, 1993), Korea s sock marke suffered severely during he 1997 Asian financial crisis, falling by 4.6 percen in 1997. I hen rose by 48.04 and 85.1 percen in 1998 and 1999 and fell by 50.9 percen in 000. The Korean won depreciaed by 68.5 percen in 1997 agains he U.S. dollar. I hen appreciaed by 14.74 and 5.45 percen in 1998 and 1999 and depreciaed by 9.90 percen in 000. The depreciaion of domesic currency agains he dollar raises he reurn on dollar asses. Invesors shif funds from domesic asses such as socks oward dollar asses due o higher expeced reurns. The shif in porfolio composiion favors dollar asses over domesic socks, leading o declining sock marke prices and reurns. According o he porfolio balance model, a depreciaing domesic currency should negaively correlae wih sock marke reurns. 1 Invesigaions of he effecs of currency depreciaion on sock marke reurns are scan and inconclusive, and lile aenion assesses his issue using daa from he 1997 financial urmoil. Solnik (1987) employs OLS regression analysis for eigh indusrial counries and finds boh a negaive and a posiive relaion beween domesic sock reurns and currency appreciaion over differen sample periods. Alhough Raner (1993) fails o find coinegraion beween he dollar foreign exchange raes of six indusrial counries and a U.S. sock marke index, Mukherjee and Naka (1995) and Ajayi and Mougoue (1996) find ha a sock marke index coinegraes wih he exchange rae in Japan and seven oher indusrial economies. Kououlas and Kryzanowski (1996) and Kearney (1998) provide evidence ha sock marke volailiy responds significanly o
exchange rae volailiy in Canada and Ireland. Jorion (1991) finds no evidence ha uncondiional exchange rae risk affecs he U.S. sock marke. Chiang, Yang and Wang (000) and Fang (001) find a significan negaive relaion beween sock reurns and currency depreciaion in boh bivaiae and univariae GARCH(1,1) processes for some Asian counries. This paper considers srucural shifs in volailiy of sock and foreign exchange markes and applies a bivariae GARCH-M model using Korean daa during he Asian financial crisis o provide more evidence for he effecs of currency depreciaion on sock marke reurns. Generalized auoregressive condiional heeroskedasiciy (GARCH) models (Bollerslev, 1986; Engle, Lilien, and Robins, 1987; and Bollerslev, Engle, and Wooldridge, 1988) have proved successful in modeling asse reurns and volailiy by allowing he mean of he asse reurn o depend on is ime-varying variance (and oher causes). Our unresriced bivariae GARCH-M approach differs from and improves on prior research in ha he model joinly esimaes sock reurns and he variance srucures of sock reurns and currency depreciaion, wih wo variances and currency depreciaion as explanaory variables. II. DATA, COINTEGRATION, AND GAUSALITY TESTS The daa consis of daily closing sock marke prices and he exchange raes from January 3, 1997 o December 1, 000. The sock marke price (P) is he Korea Composie Price Index of Souh Korea. The sock marke reurn wih no dividend adjusmen (R) is calculaed by he logarihmic difference of he sock marke price index, R = 100 (ln P ln P 1 ). The exchange rae (S) is expressed as Korean won per U.S. dollar. The depreciaion rae or he exchange rae reurn (E) is he logarihmic difference of he spo exchange rae, E = 100 (ln S ln S 1). We firs es o see if he Korean won exchange rae coinegraes wih he Korean sock 3
marke price. The repored resuls of he ADF uni roo es in Table 1 indicae he rejecion of non-saionariy in firs differences, suggess ha boh he sock marke price and he exchange rae are inegraed once, I(1). Accordingly, we consider he Johansen es for coinegraion (Johansen, 1991) beween hose wo variables. The resuls of he coinegraion es can be sensiive o he lag lengh. The likelihood raio (LR) es saisic selecs 6 lags for he VAR model. The insignifican λ max and Trace saisics sugges ha he null hypohesis of non-coinegraion is no rejeced for he wo markes. The 1997 Asian financial crisis may produce srucural breaks in he long-run relaion beween he wo marke prices, leading o non-coinegraion. Gregory and Hansen (1996) sugges residual-based coinegraion ess wih srucural breaks eiher a change in he inercep (level shif), a change in he inercep wih a ime rend (level shif wih rend), or a change in he coinegraing coefficiens (regime shif). In able 1, he hree residual-based augmened Dickey-Fuller es saisics for hose specificaions are.4348(8), -3.357(0), and.5081(), respecively, where he number in parenheses is he lag runcaion using he -es suggesed by Perron and Vogelsang (199). We se he maximum lag lengh o 1 and es downward unil he las lag difference included is significan a he 5-percen level. We fail o rejec he null hypohesis of no coinegraion in each insance. So including poenial srucural shifs due o he 1997 Asian financial crisis leaves our coinegraion findings unalered. No coinegraion suggess he use of firs-differenced daa in he VAR model o invesigae Granger causaliy (Granger, 1988). The lag lengh for he causaliy es maches ha of he es for coinegraion. The wo significan F-saisics sugges ha bidirecional Granger causaliy exiss beween he wo markes. III. STRUCTURAL SHIFT IN UNCONDITIONAL VARIANCE 4
Table displays preliminary saisics for he daily sock marke and exchange rae reurns over he sample period. The means of he sock marke and exchange rae reurns are negaive and posiive, respecively. Boh are close o zero. The sandard deviaion of he sock marke reurn exceeds ha of he exchange rae reurn. The sock marke reurn exhibis a negaive skewness, alhough no significanly differen from zero. The exchange rae reurn exhibis posiive and significan skewness. Invesors should have a preference for posiive skewness, for hey should prefer porfolios wih a larger probabiliy of large payoffs. The wo series are lepokuric. The Ljung-Box es (L-B Q) suggess he presence of auocorrelaion for boh series up o 1 lags. The Ljung-Box saisics for he squared series ( L B Q ) are all highly significan, implying he possible presence of ime-varying volailiy in sock and foreign exchange markes. Since squares of serially correlaed daa may yield resuls in favor of presence of heeroskedasiciy, he ime-varying propery of he variances for he wo series is furher examined wih Lagrange Muliplier (LM) ess for ARCH(q) errors (Engle, 198). Table 3 repors resuls of he es. The Ljung-Box Q-saisics showing no auocorrelaions up o 1 lags suggess ha he AR(1) and AR(14) processes are appropriaely modeled o obain whie noise errors for he sock marke and exchange rae reurns. Afer considering auocorrelaions, he LM saisics for he ARCH effec confirm heeroskedasic variances for sock marke and exchange rae reurns. We use he GARCH(1,1) specificaion, since i adequaely represens mos financial ime series. Lamoureux and Lasrapes (1990) sugges he use of dummy variables o correspond o shifs in he uncondiional variance. Negligence of such shifs may bias upward GARCH esimaes of persisence in variance and hus viiae he use of GARCH in esimaing he mean equaion, especially when he degree of permanence is imporan. The Korean experience provides an 5
ineresing case on his issue due o he 1997 Asian financial crisis and is effec on Korean sock and foreign exchange markes. Figure 1 shows he behavior of sock marke and exchange rae reurns. Saring on Ocober 4, 1997, he sock marke reurn became more highly variable and remained a he higher level of volailiy o he end of 000. In he same way, he exchange rae reurn began flucuaing more widely afer Ocober 4, 1997, bu reurned o a less volaile level afer Augus 1, 1998. The visual evidence suggess ha he sock marke reurn volailiy has one and he exchange rae reurn volailiy has wo srucural breaks in his sample period. Accordingly, in our GARCH(1,1) specificaion, a dummy variable D eners he sock marke variance equaion wih D=1 for he period Ocober 4, 1997 o he end of December, 000; 0 oherwise. For he foreign exchange marke variance, we include wo dummies: D =1 for Ocober 4, 1997 o Augus 1, 1998; 0 1 oherwise, and D =1 for Augus, 1998 o December 1, 000; 0 oherwise. The mean reurn in he unresriced GARCH(1,1) model, which includes shif dummies, is specified as an AR(1) process o accoun for nonsynchronous rading. Esimaion resuls are repored in Table 4. The significan esimaes of he dummies (i.e., α 3, β 3, and β 4 ) suppor our expecaion ha srucural shifs in he variance emerge for boh sock and exchange rae reurns. Wihou he dummies, he resriced GARCH(1,1) model of he exchange rae reurns emerges as an unsable variance process in which he sum of he GARCH esimaes is greaer han one. The inclusion of he shif dummies o decrease GARCH esimaes is srongly argued by Lamoureux and Lasrapes (1990). To invesigae furher, we canno rejec he Lagrange muliplier es (LM) for he consancy of he variance parameers, under he assumpion of non-normaliy, agains he alernaive hypohesis of a one-ime shif in he unresriced GARCH models (Chu, 1995). Auocorrelaion and heeroskedasiciy ess indicae ha he unresriced GARCH(1,1) specificaion sufficienly accouns for ime dependence in he condiional variance of R and E. 6
Each variance process is posiive, finie, and saionary as α 0, α1, α, α 3, β 0, β1, β, β 3, β 4 > 0 ; ( α 1 + α ) < 1, and ( β 1 + β ) < 1. The significan esimaes of α 1, α, β1 and β confirm he presence of GARCH effec in he wo series. IV. AN UNRESTRICTED BIVARIATE GARCH-M MODEL The finding of a causal relaion running from exchange rae depreciaion o he sock marke reurns (Table 1) implies ha changes in currency depreciaion induce changes in he sock marke reurns and is volailiy. The saisical evidence of saionariy (Table 1), lepokuriciy (Table ), heeroskedasiciy (Table 3), and srucural shifs in variances (Table 4) in he wo series of sock marke and exchange rae reurns suggess he use of unresriced bivariae GARCH models o analyze he effec of currency depreciaion on he sock marke reurn. The following eclecic GARCH model provides a framework for invesigaing he effecs of currency depreciaion on he sock marke reurn. n R = d 0 + i = 0 ai E i + n i = 0 b i h E, i E + = = (1) n n i 0 c ihr, i + i 1 di R i + ε R, = ω 0 + ω 1 E 1 + ε E, () ε v R h (3) R, = 0.5, ( R, ) ε v E h (4) E, = 0.5, ( E, ) hr, = α 0 + α + D (5) 1ε R, 1 + α hr, 1 α 3 h E, = β 0 + β1ε E, 1 β h E, 1 + β 3 D 1, + β 4D, + (6) hre, = γ 0 + 1ε R, 1ε E, 1 + γ hre, 1 γ (7) where and are i.i.d. wih consan mean and uni variance; h = Var ε ) and v R, v E, R, ( R, h = Var( ε E, ) ; h = Cov ε, ε ) ; ε R, and ε E, are assumed o be whie-noise sochasic E, RE, ( R, E, 7
processes. The effec of currency depreciaion may be insananeous and also may be disribued over a few days, depending on how fas he marke informaion is uilized. This dynamic feaure in he unresriced version disinguishes our model from mos empirical GARCH-M models ha include only conemporaneous variables as regressors in resriced specificaions. To pick up auocorrelaion in he reduced form errors caused by lagged adjusmen o changes in he exogenous variables, we specify an AR componen in he mean equaion of sock marke reurns. In he empirical GARCH model, condiional variances and covariance are ime-varying. For example, he large shocks of he Asian financial crisis hi he wo asse reurns of opposie signs. Tha is, he crisis raised he asse reurns of he dollars and lowered he reurns of socks. The crisis increased he variances of he wo correlaed asses and he covariance beween hem. The presence of h and h in he condiional mean equaion of he sock marke reurn implies E, i R, i ha he sysem of equaion (1) hrough equaion (7) is a bivariae GARCH-M model. 3 The parameers of he model are esimaed by maximum likelihood using he BHHH algorihm. V. EMPIRICAL RESULTS Table 5 repors he join esimaion resuls, including he esimaed coefficiens and asympoic -saisics for he general and simple models. Before esimaion, he lag lengh of he mean equaion of he sock marke reurn is deermined. We sar wih he lag srucure (i.e., n = 6) in he VAR model for coinegraion es. The general dynamic model could be overparamerized. Following he general o simple approach suggesed by Hendry (1985), we hen carry ou a daa-based simplificaion o reduce he model by eliminaing insignifican esimaes hrough LR χ -ess. We repor he likelihood raio saisic ha ess he validiy of his resricion. The 8
saisic has a χ disribuion wih 14 degrees of freedom. We also repor he Ljung-Box saisics for up o 1h-order auocorrelaion on he sandardized and squared sandardized residuals in and ε E,. In he able, he general model has neiher auocorrelaion nor heeroskedasiciy, bu oo many insignifican coefficiens exis. Using he general-o-simple approach, we eliminae foureen (14) insignifican variables. Diagnosic ess suppor he saisical appropriaeness of he simple unresriced bivariae GARCH(1,1)-M model. Each variance process is posiive and convergen as every esimaed coefficien exceeds zero, and ( α 1 + α ) and ( β 1 + β ) < 1. The significan GARCH(1,1) coefficiens of α 1, α, β1 and β sugges ime-varying volailiy in he sock and foreign exchange markes. The 1997 Asian financial crisis produced srucural shifs in variance for boh he sock marke reurn and exchange rae depreciaion. Table 5 indicaes ha he exchange rae depreciaion significanly affecs he sock marke reurn. The effec of currency depreciaion has a delayed effec, as only lagged effecs emerge. The firs, fifh, and sixh lagged depreciaion effecs are -0.0995, 0.1440, and -0.199, respecively. The sum (= -0.0854) of he coefficiens of he exchange rae depreciaion erms suppors a negaive relaion beween currency depreciaion and he sock marke reurn. The condiional variances of exchange rae depreciaion and he sock marke reurn all have significanly lagged effecs. Firs, he condiional variance of exchange rae depreciaion has a posiive cumulaive effec (=0.0103) on he sock marke reurn. The higher is he volailiy of exchange rae depreciaion, he higher is he sock marke reurn. Tha resul maches our prior expecaion ha higher exchange rae volailiy should reduce he demand for dollar asses and increase he demand for domesic socks. Second, he condiional variance of he sock marke reurn also has a posiive cumulaive effec (=0.0065) on he sock marke reurn. Tha finding provides suppor for a higher risk premium in he Korean sock marke over he period of financial ε R, 9
urmoil. Since boh he sock marke reurn and exchange rae depreciaion exhibi GARCH (Table 4), we also examine he exen o which changes in he condiional variance of exchange rae depreciaion pass hrough o he variance of sock marke reurns by specifying h R, as a funcion of h E,. To avoid serial correlaion, we specify an auoregressive disribued lag model. Afer allowing for welve lags and eliminaing insignifican effecs, he resuls appear in Table 6 wih -saisics repored in parenheses. The Ljung Box Q-saisics indicae ha he simplified model has no auocorrelaion in errors. The posiive cumulaive effec (i.e., λ i = 0.0074 > 0) indicaes ha depreciaion rae volailiy raises sock reurn volailiy. 4 The significan depreciaion coefficiens in he sock reurn process and he posiive effec of depreciaion rae volailiy on sock reurn volailiy sugges depreciaion movemens can explain periods of volailiy in he sock reurns series. The rise in sock marke volailiy has been argued o be a major reason for declines in sock prices (Malkiel, 1979; Pindyck, 1984; Chou, 1988). I is imporan o idenify any source of he marke volailiy. Modern inernaionalizaion and inegraion of financial markes have impacs on invesors in ha asse allocaion occurs across counries and asses. 5 In boh cases, invesors mus consider currency conversion. Thus, exchange rae movemens can provide a channel affecing sock marke prices and volailiy. Our findings provide evidence ha sock marke volailiy reflecs changes in he exchange rae, a leas in he period of financial urmoil for an emerging marke. VI. CONCLUSIONS We employ an unresricive bivariae GARCH-M model of he sock marke reurn o invesigae he relaionship beween currency depreciaion and he sock marke reurn. We perform ess for 10
Korea over he Asian financial urmoil from 1997 o 000. Our approach incorporaes hree imporan elemens. Firs, he daase covers he Asian financial urmoil era. Second, we include srucural shif dummies in he variance processes for boh sock and foreign exchange markes because of he financial crisis. Third, by considering adjusmen dynamics, we provide esimaes of insananeous and lagged effecs of he sock marke reurn o currency depreciaion. We find ha currency depreciaion has saisically significan effecs on sock marke reurns hrough hree channels. Firs, he level of exchange rae depreciaion negaively affecs sock marke reurns. Second, exchange rae depreciaion volailiy posiively affecs sock marke reurns. Third, sock marke reurn volailiy responds o exchange rae depreciaion volailiy. Our resuls show ha currency depreciaion imporanly alers he sock marke invesmen decision. The decision o inves in he Korean sock marke benefis from knowledge of boh he level and volailiy of he Korean won. Invesmen acions generae sock marke reurns ha are, a bes, uncerain, if invesors ignore he level, as well as he volailiy, of exchange rae depreciaion. 11
FOOTNOTES 1 Financial markes adjus rapidly and reach heir equilibrium in he shor run. This paper examines shor-run properies of he porfolio balance model, assuming ha he real secor is deermined. In he long run, a depreciaing domesic currency should favorably affec sock marke prices and reurns due o increased expors and domesic subsiuion for impored goods. Bollerslev, Chou, and Kroner (199) cie over 00 papers using (G)ARCH echniques in an exensive range of applicaions. 3 Engle and Kroner (1995) provide more deails abou specifying mulivariae GARCH models. 4 Kearney (1998) concludes ha exchange rae volailiy significanly deermines sock marke volailiy in Ireland. 5 For example, in he inernaionalizaion process, he U.S. sock marke was by far he larges in he world, bu foreign sock markes have been growing in imporance. The increased ineres in foreign socks has promped he developmen in he Unied Saes of muual funds specializing in rading in foreign sock markes. American invesors now pay aenion no only o he Dow Jones Indusrial Average bu also o sock price indexes for foreign sock markes. 1
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0 10 0 0 10-10 -0 0-10 -0 97/10/4 98/8/1 99/6/18 00/4/4 Figure 1. Exchange Rae ( E ) and Sock Marke ( R ) Reurns E R 16
Table 1. Uni-Roo, Coinegraion, and Causaliy Tess ADF Uni-Roo Tes Variable Level Firs difference Sock index ( P ) -1.3515() -.3783(1)* Exchange rae ( R ) -.3010(30) -4.9313(9)* Johansen Coinegraion Tes (VAR lags = 6) H 0 λ max criical value Trace criical value R = 0 7.60 10.60 9.99 13.31 R 1.40.71.40.71 ADF Coinegraion Tes wih Srucural Breaks Models -saisics criical value Level shif -.4348(8) -4.61 Level shif wih rend -3.357(0) -4.99 Regime shif -.5081() -4.95 Granger Causaliy Tes (VAR lags = 6) H 0 F(q,N-k) Granger causaliy es resul S does no cause P 3.507* S causes P P does no cause S.136* P causes S ADF(n) is he Augmened Dickey-Fuller es for saionariy wih n lags seleced o guaranee no auocorrelaion in he ADF regression residuals. The likelihood raio saisics deermine a lag lengh of 6 in he VAR for coinegraion and Granger causaliy ess. R is he number of coinegraion vecor. The lag lengh for he ADF coinegraion es wih srucural breaks is seleced on he basis of a es suggesed by Perron and Vogelsang (199). F(q,N-k) is Wald F saisic wih he degrees of freedom of q and N-k. *denoes significance a he 5% level. 17
Table. Preliminary Saisics for Daily Sock Marke and Exchange Rae Reurns Sock marke reurns Exchange rae reurns Sample size 97 97 Mean -0.05 0.0389 SD.8848 1.836 Skewness -0.0386 (0.195) 1.6454* (0.195) Kurosis 4.4884* (0.7698) 59.3951* (0.7698) L-B Q(6) 0.545* 0.60* L-B Q(1) 4.303* 38.60* L-B Q(6) 77.38* 467.3* L-B Q(1) 114.37* 856.14* SD is he sandard deviaion. L-B Q(k) and L-B Q(k) are Ljung-Box saisics for reurns and squared reurns for auocorrelaion up o k lags. The numbers in parenheses beneah he skewness and kurosis are sandard deviaions calculaed by 6 / N and 4 / N, respecively. *denoes significance a he 5 percen level. 18
Table 3. ARCH LM es K Sock marke reurns Exchange rae reurns 1 10.4687* 60.918* 8.3037* 105.1889* 3 9.671* 74.6935* 4 10.3114* 58.44* 5 10.403* 46.5011* 6 8.5730* 38.9311* 7 7.7966* 33.8558* 8 6.8555* 30.0013* 9 6.141* 30.940* 10 5.78* 33.6636* 11 5.4863* 30.6141* 1 5.1401* 33.06* ARMA(p,q) (1,0) (14,0) L-B Q(6) 9.9010 3.7545 L-B Q(1) 14.433 1.956 ARMA(p,q) represens he process in sock and exchange rae reurns. L-B Q(k) is he Ljung-Box saisic for residuals from he ARMA process for auocorrelaions up o 1 lags. LM saisic follows a χ disribuion wih k degrees of freedom, where k = 1,,3, 1. *denoes significance a he 5 percen level. 19
Table 4. Unresriced GARCH Models Sock Marke Reurns R c0 + c1r 1 + ε R, =, where ε ~ N(0, h ) hr, = α 0 + α1ε R, 1 + α hr, 1 + α 3 R = 0 R + R,.0019 ( 0.691) + 0.1083 1 (.9488) * ε R, Ψ 1 R, h R, = 0.00 + 0.1130ε R, 1 + 0.7799hR, 1 + 0.853D (.5943) * (4.0907) * (14.0664) * (.946) * D LB Q( 6) = 7.6631 LB Q(1) = 11.5856 ARCH (6) = 0.5700 ARCH (1) = 0.6510 LM = 1.3104 Exchange Rae Reurns =, where ε ~ N (0, h ) E d 0 + d1e 1 + ε E, e, Ψ 1 E, h E, = β 0 + β1ε E, 1 + β he, 1 + β 3D1, + β 4D, E = 0 E 1 + ε E,.0108 (1.046) + 0.167 (4.064) * h E, = 0.0079 + 0.3113ε E, 1 + 0.6485hE, 1 + 0.7350D1, + 0.0133D, (10.1104) * (10.1404) * (4.3661) * (8.7508) * (6.8877) * LB Q( 6) = 8.1405 LB Q(1) = 11.4543 ARCH (6) = 0.6446 ARCH (1) = 0.5010 LM = 9.319 L-B Q is he Ljung-Box saisic for sandardized residuals for auocorrelaion up o 1 lags. ARCH(k) is he LM es for addiional ARCH of he sandardized residuals. Asympoic -values are in parenheses. LM is he Lagrange muliplier es for parameer consancy o he condiional variance in he GARCH model. *denoes significance a he 5% level. 0
Table 5. Unresriced Bivariae GARCH-M Model R E h h h = 6 6 6 6 0 + +, +, + d aie i = 0 bihe i = 0 cihr i di i i i = 0 i = 1 R, E, RE, = ω + ω E 0 = α + α ε 0 0 = γ 0 1 + γ ε 1 1 R, 1 = β + β ε 1 E, 1 + ε E, + α h ε 1 R, 1 E, 1 R, 1 + β h E, 1 + γ h + α D 3 + β D 3 RE, 1 General model 1, + β D 4, R i + ε R, Simple model Coefficien -value Coefficien -value d 0-0.089-0.6691-0.0833-0.6888 a 0-0.1636-1.4085 a 1-0.104** -1.7547-0.0995* -1.9708 a -0.0411-0.5783 a 3-0.0055-0.0886 a 4-0.039-0.484 a 5 0.118** 1.6855 0.1440*.591 a 6-0.164** -1.708-0.199* -.0399 b 0 0.0360 1.3887 b 1-0.083-0.7139 b -0.0519-1.406-0.0483* -.7799 b 3 0.1048* 3.8779 0.0861* 3.7194 b 4-0.0869* -.4380-0.0733* -.489 b 5 0.0655 1.5634 0.076*.389 b 6-0.051-1.3066-0.0304* -1.9776 c 0-0.0388-0.593 c 1 0.0383 0.5067 c 0.070 1.0933 c 3-0.0603-0.848 c 4-0.119** -1.7118-0.1093** -1.96 c 5 0.193 1.4653 0.1158*.0314 c 6-0.0199-0.3479 d1 0.1036*.6706 0.107*.6931 d -0.0630** -1.8580-0.0534** -1.6661 d 3-0.0154-0.4598 d 4 0.04 0.7850 d 5-0.0858* -.7516-0.077* -.6344 d 6 0.0347 0.9953 ω 0 0.0091 0.951 0.009 0.946 ω 1 0.1545* 4.153 0.1511* 4.84 α 0 0.6955* 3.638 0.6178* 3.8647 α 1 0.140* 3.6437 0.144* 3.954 α 0.5506* 5.4007 0.586* 6.676 α 3.0454* 3.597 1.8990* 3.690 β 0 0.0064* 9.1511 0.0065* 9.3437 β 1 0.459* 10.308 0.454* 10.5410 β 0.7199* 30.8838 0.7167* 31.947 β 3 0.536* 7.301 0.5477* 7.9403 β 4 0.0090* 6.1685 0.0091* 6.330 γ 0-0.0009-0.3195-0.0019-0.645 1
General model Simple model Coefficien -value Coefficien -value γ 1 0.074* 3.0770 0.079* 3.4306 γ 0.8937 30.3445 0.8819* 3.7896 LR(14) 10.78 L-B Q R (6) 0.67 0.790 L-B Q R (1) 3.5500 4.365 L-B Q R (6) 6.5704 6.4117 L-B Q R (1) 17.165 16.5574 L-B Q E (6) 8.83 8.9009 L-B Q E (1) 1.514 1.6353 L-B Q E (6) 3.44 3.4746 L-B Q E (1) 5.898 5.9377 The columns repor he coefficien esimaes and asympoic -saisics for he general and simple models. LR(k) is he likelihood raio χ saisic ha ess his resricion wih k degrees of freedom. L-B Q and L-B Q are Ljung-Box saisics for sandardized and squared sandardized residuals in R, E for auocorrelaion up o 1 lags. *denoes significan a he 5-percen level and **denoe significance a he 10 percen level.
Table 6. Response of sock marke reurn volailiy o exchange rae depreciaion volailiy h R, n n λ i ihe i + = 0, i = 1 = γ 0 + γ ihr, i + η h R, = 0.664 (3.733) * + 0.0985h (4.811) * R, 1 + 0.6866hR, 1 (6.0458) * 0.0194hE, 8 ( 1.8373) * * + 0.0794h (.3034) * + 0.0444h (3.8005) * R, 3 E, 9 + 0.0541hR, (1.6847) * * 0.0176hE, (.6743) * 4 1 F( 3,943) = 6.793* λ = 0.0074 L BQ(6) = 3.5177 L BQ(1) = 8.67 i λ i is he sum of he coefficien esimaes of λ i. L-B Q is Ljung-Box saisic esing for he auocorrelaions in residuals up o 1 lags. -values are in parenheses. F(3,N-3) is Wald F saisic esing for he resricion of zero coefficien in he hree lagged he, i variables wih he degrees of freedom of 3 and N-3. * and ** denoe significance a he 5% and 10% level, respecively. 3