Applied Econometrics and International Development Vol.7-1 (2007)

Transcription

1 Applied Economerics and Inernaional Developmen Vol.7- (7) THE INFLUENCE OF INTERNATIONAL STOCK MARKETS AND MACROECONOMIC VARIABLES ON THE THAI STOCK MARKET CHANCHARAT, Surachai *, VALADKHANI, Abbas HAVIE, Charles Absrac The paper examines he impac of several sock marke price indices and macroeconomic variables on he Thai sock marke, using a GARCH-M model and monhly daa (988M-4M). We find ha (a) changes in reurns in Singapore, Malaysia and Indonesia before he 997 crisis, and changes in Singapore, he Philippines and Korea afer 997 insananeously influenced reurns in he Thai sock marke; (b) changes in oil prices negaively impaced on i only prior o 997; (c) volailiy clusering and a GARCH-M model were presen only before 997; and (d) markes ouside he region had no immediae impac on he Thai marke. JEL Classificaion: E44, G4, G5 Keywords: Sock marke; condiional volailiy; macroeconomic variables; GARCH; Thailand.. Inroducion Sock marke volailiy appears now o move rapidly across counries. This has been possibly affeced by he liberalizaion of capial markes in he pas wo decades. A clearer undersanding of sock marke deerminans is very imporan for invesors, regulaors and academic researchers. Therefore, increased knowledge of sock marke deerminans is necessary in he selemen of pricing, hedging and regulaory policy. A number of analyss have invesigaed he impac of macroeconomic variables and inernaional linkages on sock reurns. Mos of hese sudies, however, have focused on developed markes by using he Auoregressive Condiional Heeroscedasiciy (ARCH) model and he Generalized ARCH (GARCH) model. For insance, Schwer (989) and Flannery and Proopapadakis () esed he effec of domesic macroeconomic variables on sock volailiy for he Unied Saes. They found weak evidence ha such facors could predic sock marke reurns which are inherenly volaile. Moreover, Hamao, Masulis and Ng (99), Bae and Karolyi (994) and Susmel and Engle (994) focused on he inernaional spillover of sock reurn volailiy beween Japan, he Unied Kingdom and he Unied Saes and found some evidence of volailiy spillovers beween hese markes. In addiion, he effec of foreign sock markes and macroeconomic news on he Ausralian sock marke were furher invesigaed by Kim and In (). The resuls indicaed ha he movemens of he major sock markes * Surachai Chanchara, Abbas Valadkhani * Charles Havie, School of Economics and Informaion SysemsUniversiy of Wollongong, Ausralia. * Corresponding auhor: Dr. Abbas Valadkhani, School of Economics and Informaion Sysems, Universiy of Wollongong, NSW 5, Ausralia. abbas@uow.edu.au

2 Applied Economerics and Inernaional Developmen Vol.7- (7) (namely Japan, he Unied Kingdom and he Unied Saes) and some macroeconomic news significanly influence he Ausralian sock marke. Oher sudies have examined he impac of macroeconomic variables and inernaional linkages on he Thai sock marke. Granger, Huang and Yang () and Phylakis and Ravazzolo (5b) employed a coinegraion model. Fang () and Caporale, Piis and Spagnolo () used a GARCH model o analyse he relaionship beween sock reurns and various exchange raes. Mos sudies find ha he exchange rae leads sock reurns, posiively, in Thailand. In addiion, Liu, Pan and Fung (996) and Liu, Pan and Shieh (998) used vecor auoregressive analysis and coinegraion models o invesigae he inernaional linkages beween he sock markes of he Unied Saes and Asia-Pacific counries. The resuls indicaed ha he Unied Saes marke influenced he condiional volailiy of mos Asian markes. Japan and Singapore had a significan and persisen impac on oher Asian markes. On he oher hand, Ng (), Baharumshah, Sarmidi and Tan (3) and Phylakis and Ravazzolo (5a) repored no evidence o indicae ha he inernaional linkages among he Souh-Eas Asian sock markes was significan. In, Kim, Yoon and Viney (), however, used a GARCH model and found a significan volailiy linkage beween Korea and Thailand. Hence here is no consensus on he naure of hese relaionships. In he 99s, mos sock markes in Asia experienced considerable growh and urbulence. This process resuled in a profound change in Thailand s economy. The Sock Exchange of Thailand (SET) significanly influences Thai economic developmen by providing a mechanism for resource re-allocaion beween differen secors of he Thai economy. As a rapidly developing emerging marke he SET also plays an imporan role in a worldwide conex by affecing inernaional capial flows. The experience of he Thai sock marke is probably ypical of Asian sock markes in general because of is manageable size and diverse characerisics (Bos, Ding and Feherson, 998; Chusanachoi and Kamah, ). An undersanding of he mechanisms of he Thai sock marke s dynamics is, herefore, very imporan. This is he firs sudy o invesigae he impac of inernaional linkages and macroeconomic variables on he Thai sock marke using a GARCH model. The primary objecive is o examine he impac of inernaional sock markes and domesic macroeconomic variables on he Thai sock marke price reurn, in he pre- and pos-997 Asian crisis period, by applying various GARCH models. The main reason o use GARCH perains o he fac ha he variance of forecas errors depends on he size of he preceding disurbances. A generalized form of he condiional heeroscedasiciy allows for lagged variances and furher lagged values of he error erm. Consequenly, i is naurally expeced ha he GARCH model is an efficien way o deal wih volailiy clusering observed in residuals which usually occur in sock price daa. The remainder of his paper is organized as follows. The nex secion describes he daa employed and presens he summary saisics as well as he uni roo es resuls. The hird secion briefly discusses he GARCH models from a heoreical perspecive in idenifying he major deerminans of Thai sock price variaions. The fourh secion presens various esimaes of a model capuring he volailiy of sock price reurns. The penulimae secion discusses he major findings and implicaions arising from his sudy. Finally, he las secion provides some brief concluding remarks.

3 Chanchara, S., Valadkhani, A., Havie.C. Macroeconomic Variables in Thai Sock Marke. Daa and Empirical Mehodology This sudy uses he sock price index of Thailand (TH) which is based on marke capializaion, and calculaed from he prices of all common sock on he marke board. Moreover, we uilise fifeen oher inernaional sock price indices from various regions, including he following counries: Argenina (AR), Ausralia (AU), Brazil (BA), Germany (GE), Hong Kong (HK), Indonesia (IN), Japan (JA), Korea (KO), Malaysia (MA), he Philippines (PH), Russia (RU), Singapore (SG), Taiwan (TA), he Unied Kingdom (UK) and he Unied Saes (US). Monhly daa are used covering he period January 988 o December 4 wih a base value of in December 987, excep for he sock price index of Russia covering he period December 994 o December 4 which has a base value of in December 994. This differen base year has been modified accordingly. All sock indices were obained from Morgan Sanley Capial Inernaional (MSCI: hp:// In addiion, he macroeconomic variables seleced for Thailand include he consumer price index (CPI), he exchange rae (EX), he ineres rae (on money) (MR), he money supply (M) and oil price (OP) and were obained from he Inernaional Financial Saisics (IFS: hp://ifs.apdi.ne/imf/logon.aspx) daabase (hese five macroeconomic variables will be included in Equaion () in he nex secion). All variables used are monhly observaions spanning he ime period from January 988 o December 4 and are expressed in erms of growh raes. Figure. Plo of five macroeconomic variables employed Consumer Price Index Exchange Rae E+ Money Supply 5 Moneary Rae 6.E+ 5.E+ 4.E+ 5 3.E+.E+.E+ 5.E+ 5 Oil Prices 4 3 Sources: IFS. Inernaional Financial Saisics. 3

4 Applied Economerics and Inernaional Developmen Vol.7- (7) Figure above and Figure, in he Annex, presen he graphs of he variables employed in his sudy. We presen he full daa in graphical form separaing he pre- Asian crisis period (i.e. from January 988 o December 997 oaling monhly observaions) from he pos-asian crisis period (i.e. from January 998 o December 4 using 84 monhly observaions). The pos-997 period is shown by he shaded areas in Figures and in he Annex. Table in he Annex presens he descripive saisics of he daa. Sample means, medians, maximums, minimums, sandard deviaions, skewness, kurosis as well as he Jarque-Bera saisics and p-values are presened. The highes mean reurn is.3 per cen in Russia and he lowes is -. per cen in Japan. The sandard deviaions range from. per cen (he leas volaile) for he growh rae of he money supply o.3 per cen (he mos volaile) for he growh of he ineres rae. The sandard deviaions of sock price indices are lowes in he developed economies of he US, UK, Ausralia, Germany, Japan and Singapore, while, on he oher hand, he mos volaile are in Russia, Brazil, Argenina, Indonesia, Thailand and Taiwan, respecively. All sock reurns have excess kurosis which means ha hey have a hicker ail and a higher peak han a normal disribuion. The calculaed Jarque-Bera saisic and corresponding p-value is used o es he null hypohesis ha he monhly daa follow a normal disribuion. Mos of he Jarque-Bera saisics and p-values rejec he normaliy assumpion a any convenional level of significance for all variables, wih he only excepions being he monhly sock reurns in Ausralia, Japan and he Unied Kingdom. Figures 3 and 4 in he Annex show he plos of he sock reurns and he monhly growh raes of a number of relevan macroeconomic variables for Thailand. In order o make robus conclusions abou he ime series properies of he daa his sudy uses he Augmened Dickey-Fuller (ADF) es and he DF-GLS es inroduced by Dickey and Fuller (979) and Ellio, Rohenberg and Sock (996), respecively. In his paper he lowes value of he Schwarz Crierion (SC) is used o deermine he opimal lag lengh in he esing procedure. These lags augmen he relevan regressions o ensure he error erm is whie noise and free of any serial correlaion. Based on he resuls of he uni roo ess presened in Table in he Annex, we conclude ha all variables employed in his paper are I(), as hey were non-saionary in levels bu saionary in firs difference form. 3. An Applicaion of he GARCH Model As discussed earlier, we have segmened he sample period ino he pre- and pos-997 Asian crisis. Iniially, he following equaion was esimaed by he OLS mehod for he wo periods separaely: k= 5 k= 5 TH i i ω θi P ηi M u () i= i= P = However, in he pre-997 period he esimaed correlogram of squared residuals of such a model exhibied significan Auoregressive Condiional Heeroscedasiciy (ARCH) effecs (see Figure 5 in Annex). In order, herefore, o capure any possible ARCH and Generalized ARCH (GARCH) effecs, we specified a GARCH-in-mean (GARCH-M) in his paper. The GARCH model was developed by Bollerslev (986) from 4

5 Chanchara, S., Valadkhani, A., Havie.C. Macroeconomic Variables in Thai Sock Marke he ARCH model previously inroduced by Engle (98). Boh models esablish he paerns of ime varying volailiy in reurns. For a deailed accoun of hese models see e.g. Bollerslev, Chou and Kroner (99) and Pagan (996). The GARCH-M (Bollerslev, 986; Engle, Lilien and Robins, 987) specificaion provides he forecas variance o vary over ime and lag values o be included in he variance equaion, which is a convenien and robus measure since i connecs condiional volailiy o he sock price reurns in he following manner: k= 5 k= 5 TH i i i i i= i= P = ω + θ P + η M + γ h + u () where u h q p = α + α iu i + β jh j i= j= ε (3) q p + α iu i + β j i= j= = α h (4) TH P i P and j i M denoe he value of he Thai sock index, he 5 inernaional sock indices (as oulined in he previous secion) and he five macroeconomic variables, respecively. Moreover, ω and α are he corresponding inercep erms in he mean and variance equaions, respecively, θ i shows he insananeous responsiveness of he Thai sock reurns o he i h inernaional sock reurns, η i shows he responsiveness of he Thai sock reurns o he i h macroeconomic variables, he esimaed coefficien γ is referred o as a measure of he risk-reurn radeoff in financial economerics. In his paper his erm indicaes ha he condiional mean of P TH depends on he condiional sandard deviaion obained from Equaion (4), h is he condiional variance which is dependen on lagged values of squared errors and lagged values of he condiional variance, α i and β j are he ARCH and GARCH coefficiens, respecively, q is he order of he moving average ARCH erm, p is he order of he auoregressive GARCH erm. These ypes of models are usually employed in financial economerics o es he effec of he expeced asse risk on he expeced reurn on an asse. Relevan sudies include French, Schwer and Sambaugh (987), Poon and Taylor (99), Choudhry (996), Engle () and Andersen, Bollerslev, Diebold and Labys (3) among ohers. 4. Empirical Resuls There are explanaory variables on he righ hand side of Equaion (). We used he general-o-specific modelling approach o omi he insignifican variables in Equaion () on he basis of a baery of maximum likelihood ess. A firs we esimaed his equaion for he pre-997 period. Afer excluding he insignifican variables a cursory look a he correlogram of residuals (See Figure 5) of he esimaed parsimonious model, which does no capure he ARCH and GARCH effecs, reveals a serious ype of volailiy clusering. However, once he ARCH and GARCH effecs, or he condiional heeroscedasiciy in he residuals, are modelled, as described in Equaions () o (4), he correlogram of he resuling residuals appear o be more saisically accepable (see Figure 6). According o Gujarai (3) he correlogram of residuals a various lags ha drif around zero imply 5

6 Applied Economerics and Inernaional Developmen Vol.7- (7) ha he esimaed model is probably saionary. Table 3 presens he esimaion resuls for Equaions () and (). As can be seen from he resuls, he parsimonious model esimaed by OLS does no pass he ARCH es using various lags. However, once he ARCH effecs are aken ino accoun he repored GARCH-M model passes he diagnosic ess in Table 3. Table 3. Esimaion of he Thai monhly reurn model, ln P TH, in he pre-997 crisis period OLS GARCH-M Variables p- Coefficien -saisic p-value Coefficien z-saisic value Mean equaion Inercep *** -4.. IN.56 *** *** P P MA.4 *** *** P SG.588 *** *** M OP -.34 *** *** h ***.78.7 Variance equaion Inercep ** u *** -3.. u ***.73. h ***.77.6 Adjused R Log-L Akaike Schwarz Overall F-sa ***. 5. ***. ARCH LM F-sa lag lag 6.38 *** lag *** lag 4.8 *** lag.967 *** lag.965 *** Jarque-Bera Noe: ** and *** indicaes ha he corresponding null hypohesis is rejeced a he 5 and per cen significance level, respecively. The Lagrange Muliplier (LM) es is used for esing serial correlaion. The null hypohesis of he LM es is ha here is no serial correlaion up o lag order p (a prespecified ineger). The resuls show no serial correlaion up o order welve for he esimaed GARCH models. Therefore, i is imporan o capure hese effecs by a GARCH(p, q) process as in Equaion (). Assuming ha γ, Table 3 presens he economeric resuls of he GARCH-M model using he maximum likelihood mehod. One 6

7 Chanchara, S., Valadkhani, A., Havie.C. Macroeconomic Variables in Thai Sock Marke can observe ha he esimaed γ is highly significan and posiive (i.e ) supporing he view ha he higher he sock marke volailiy, he higher would be he rae of reurn. I should be noed ha our preferred model has he lowes SC, he highes adjused R, passes various ARCH ess repored in Table 3 and is resuling correlogram is wellbehaved (see Figure 6 in he Annex). From Bollerslev (986) he preferred equaion also saisfies he saionariy of he parsimonious model, GARCH-M (q=, p=), as q p αi + β j < i= j=. I should be noed ha he SC and significan spikes in he relevan correlogram of squared residuals are used o deermine he opimum values of p and q. In order of magniude he esimaed coefficiens for Singapore (.586), Malaysia (.383) and Indonesia (.) were highly significan a he per cen significance level, whereas he remaining sock marke reurns were no saisically significan a any convenional level. Table 4. Esimaion of hethai monhly reurn model, lnp TH, in he pos-997 crisis period Variables Coefficien -saisic p-value Mean equaion Inercep KO.4 *** P P PH.59 *** P SG.4 *** h Variance equaion Inercep u h Adjused R.679 Log-L Akaike -.66 Schwarz -.5 Overall F-sa 59.4 ***. ARCH LM F-sa lag lag lag lag lag lag Jarque-Bera Noe: *** indicaes ha he corresponding null hypohesis is rejeced a he per cen significance level. Ou of he five macroeconomic variables in he model only he oil price was significan, suggesing ha higher growh raes in oil price can cause reurns on he Thai 7

8 Applied Economerics and Inernaional Developmen Vol.7- (7) sock marke o plumme. The insignifican variables were excluded from he final repored models.we have also used he OLS mehod and Equaion () o model he Thai sock reurn in he pos-997 crisis, and he resuls are repored in Table 4. As can be seen from Figure 7 in he Annex, he correlogram of residuals for his model shows no sign of ARCH or GARCH effecs. In addiion, he esimaed model passes he ARCH LM es wih various lags and, compared o various esimaed models (which are no repored in his paper due o he lack of space bu hey are available from he auhors upon reques), has he lowes value of he SC. Therefore, we do no need o use he ARCH and GARCH models for his period. In fac, he esimaed ARCH and GARCH and γ coefficiens were all insignifican, and as a resul hey have no been repored in Table 4. So we can conclude ha he sock reurns in he Philippines (.59), Korea (.4) and Singapore (.4) were he only major variables ha insananeously impaced on he Thai sock marke. 5. Major Findings and Implicaions Based on Tables 3 and 4 he major findings of he paper can be summarized as follows. Firs, i appears ha Singapore is he only counry whose sock reurns are posiively relaed o ha of Thailand in boh he pre- and pos-997 crisis periods. This evidence is no surprising because Singapore is a major regional financial hub wih exensive invesmen hroughou he region, a price leader wih is dominance in he Asian marke and also he major producer of informaion. Moreover, inernaional invesors ofen overreac o news from Singapore s marke and place less weigh on informaion from oher Asian markes. Thus, innovaions in Singapore could be used as an indicaor o predic he performance of he Thai sock marke. Second, apar from Singapore, in he pre-997 period changes in sock reurns in Indonesia and Malaysia were he mos significan deerminans of he reurns in Thailand, bu pos-997 he Philippines and Korea replaced hese. This shif in imporance in he pos-997 period is a resul of capial conrols imposed in Malaysia during 998 and he economic urbulence in Indonesia, while Korea has aained more economic inegraion wih Thailand. However, he case of he Philippines is more difficul o explain. Third, none of he sock markes in oher counries ouside he region played an imporan role in explaining he variaion of Thai sock marke reurns before or afer 997. Fourh, consisen wih previous sudies, he effec of macroeconomic variables on he dependen variable was insignifican, wih he only excepion being changes in he price of oil. I appears ha a rise in oil prices had a negaive effec on sock reurns prior o 997 bu became insignifican afer 997. Finally, he significan esimaed coefficien γ on he ime varying condiional variance h indicaes ha volailiy iself exered a posiive impac on Thai sock marke reurns in he pre-asian crisis period only. 6. Concluding Remarks The main purpose of his empirical research has been o invesigae how fifeen inernaional sock markes and five relevan Thai macroeconomic variables influenced 8

9 Chanchara, S., Valadkhani, A., Havie.C. Macroeconomic Variables in Thai Sock Marke monhly sock marke reurns in Thailand in he pre- and pos-997 Asian crisis eras. I was found ha he Singapore sock marke influenced he Thai sock marke significanly in boh he pre- and pos-997 periods. Before 997 he Indonesian and Malaysian sock markes were significanly relaed o he Thai sock marke whereas afer he crisis, Korea and he Philippines played a dominan role in explaining sources of variaion in he monhly reurns in he Thai sock marke. Therefore, o a large exen one may conclude ha he Thai sock marke is very much influenced by he performance of is neighboring counries sock markes, bu non-regional markes exered an insignifican effec. This goes some way o explaining why he financial crisis of 997 remained a primarily regional crisis. References Andersen, T.G., Bollerslev, T., Diebold, F.X. and Labys, P. (3), "Modeling and forecasing realized volailiy", Economerica, 7, No., pp Bae, K.-H. and Karolyi, G.A. (994), "Good news, bad news and inernaional spillovers of sock reurn volailiy beween Japan and he U.S." Pacific-Basin Finance Journal,, No. 4, pp Baharumshah, A.Z., Sarmidi, T. and Tan, H.B. (3), "Dynamic linkages of ASIAN sock markes: An analysis of pre-liberalizaion and pos-liberalizaion eras", Journal of he Asia Pacific Economy, 8, No., pp Bollerslev, T. (986), "Generalized auoregressive condiional heeroskedasiciy", Journal of Economerics, 3, No. 3, pp Bollerslev, T., Chou, R.Y. and Kroner, K.F. (99), "ARCH modeling in finance: A review of he heory and empirical evidence", Journal of Economerics, 5, No. -, pp Bos, T., Ding, D. and Feherson, T.A. (998), "Searching for periods of volailiy: A sudy of he behavior of volailiy in Thai socks", Pacific-Basin Finance Journal, 6, No. 3-4, pp Caporale, G.M., Piis, N. and Spagnolo, N. (), "Tesing for causaliy-in-variance: An applicaion o he Eas Asian markes", Inernaional Journal of Finance and Economics, 7, No. 3, pp Choudhry, T. (996), "Sock marke volailiy and he crash of 987: Evidence from six emerging markes", Journal of Inernaional Money and Finance, 5, No. 6, pp Chusanachoi, J. and Kamah, R. (), "Marke condiions, reurn disribuions and he day-ofhe-week effecs in Thailand: The experience of he 99s", American Business Review,, No., pp Dickey, D.A. and Fuller, W.A. (979), "Disribuion of he esimaors for auoregressive ime series wih a uni roo", Journal of he American Saisical Associaion, 74, No. 366, pp Ellio, G., Rohenberg, T.J. and Sock, J.H. (996), "Efficien ess for an auoregressive uni roo", Economerica, 64, No. 4, pp Engle, R. (), "GARCH : The use of ARCH/GARCH models in applied economerics", Journal of Economic Perspecives, 5, No. 4, pp Engle, R.F. (98), "Auoregressive condiional heeroscedasiciy wih esimaes of he variance of Unied Kingdom inflaion", Economerica, 5, No. 4, pp Engle, R.F., Lilien, D.M. and Robins, R.P. (987), "Esimaing ime varying risk premia in he erm srucure: The ARCH-M model", Economerica, 55, No., pp Fang, W. (), "The effecs of currency depreciaion on sock reurns: Evidence from five Eas Asian economies", Applied Economics Leers, 9, No. 3, pp Flannery, M.J. and Proopapadakis, A.A. (), "Macroeconomic facors do influence aggregae sock reurns", Review of Financial Sudies, 5, No. 3, pp

10 Applied Economerics and Inernaional Developmen Vol.7- (7) French, K.R., Schwer, G.W. and Sambaugh, R.F. (987), "Expeced sock reurns and volailiy", Journal of Financial Economics, 9, No., pp Granger, C.W.J., Huang, B.-N. and Yang, C.-W. (), "A bivariae causaliy beween sock prices and exchange raes: Evidence from recen Asian flu", The Quarerly Review of Economics and Finance, 4, No. 3, pp Gujarai, D.N. (3), Basic economerics, 4h edn, McGraw-Hill, Singapore. Hamao, Y., Masulis, R.W. and Ng, V. (99), "Correlaions in price changes and volailiy across inernaional sock markes", Review of Financial Sudies, 3, No., pp In, F., Kim, S., Yoon, J.H. and Viney, C. (), "Dynamic inerdependence and volailiy ransmission of Asian sock markes: Evidence from he Asian crisis", Inernaional Review of Financial Analysis,, No., pp Kim, S. and In, F. (), "The influence of foreign sock markes and macroeconomic news announcemens on Ausralian financial markes", Pacific-Basin Finance Journal,, No. 5, pp Liu, Y.A., Pan, M.-S. and Fung, H.-G. (996), "Inernaional ransmission of sock price volailiy: Evidence from he US and six Pacific Basin markes", Journal of Mulinaional Financial Managemen, 6, No. -3, pp Liu, Y.A., Pan, M.-S. and Shieh, J.C.P. (998), "Inernaional ransmission of sock price movemens: Evidence from he US and five Asian-Pacific markes", Journal of Economics and Finance,, No., pp Ng, T.H. (), "Sock marke linkages in Souheas Asia", Asian Economic Journal, 6, No. 4, pp Pagan, A. (996), "The economerics of financial markes", Journal of Empirical Finance, 3, No., pp. 5-. Phylakis, K. and Ravazzolo, F. (5a), "Sock marke linkages in emerging markes: Implicaions for inernaional porfolio diversificaion", Journal of Inernaional Financial Markes, Insiuions and Money, 5, No., pp Phylakis, K. and Ravazzolo, F. (5b), "Sock prices and exchange rae dynamics", Journal of Inernaional Money and Finance, 4, No. 7, pp Poon, S.-H. and Taylor, S.J. (99), "Sock reurns and volailiy: An empirical sudy of he UK sock marke", Journal of Banking and Finance, 6, No., pp Schwer, G.W. (989), "Why does sock marke volailiy change over ime?" Journal of Finance, 44, No. 5, pp Susmel, R. and Engle, R.F. (994), "Hourly volailiy spillovers beween inernaional equiy markes", Journal of Inernaional Money and Finance, 3, No., pp On line Annex a he journal websie: hp:// 3

11 Applied Economerics and Inernaional Developmen Vol.7- (7) Table. Descripions of he daa employed, January 988-December 4 Variable Mean Median Max. Min. S.Dev Skewness Kur osis Jarqu e- p- value Bera TH P AR P ln = P AU P ln = P BA 3 P ln = P GE 4 P ln = P HK 5 P ln = P IN 6 P ln JA 7 P P - = P KO 8 P P MA 9 P ln = P PH P ln = P RU P ln = P SG P ln = P TA 3 P ln = P UK 4 P ln = P US 5 P ln = P CPI M = M EX M =M MR 3 M = M M 4 M = M OP M = M Sources: () hp:// and () hp://ifs.apdi.ne/imf/logon.aspx

12 Applied Economerics and Inernaional Developmen Vol.7- (7) Figure. Plo of sock price indices Argenina Ausralia Brazil Germany Hong Kong Indonesia Japan Korea Malaysia Philippines Russia Singapore Taiwan Thailand Unied Kingdom Unied Saes Sources: hp:// 3

13 Chanchara, S., Valadkhani, A., Havie.C. Macroeconomic Variables in Thai Sock Marke Table. Uni roo es resuls Variables ADF ERS DF-GLS Consan Opi mal lag Consan and rend Opimal lag Consan Opi mal lag Consan and rend Opi mal lag TH *** *** * *** P AR P P *** 3.84 ***.64 ***.47 *** AU P P *** 5.3 *** BA 3 P P *** 6.36 *** 4.46 *** 5.58 *** GE 4 P P *** 5.5 *** 4.78 *** 5.48 *** HK 5 P P *** *** ***.3 *** IN 6 P P ***.959 ***.97 ***.8 *** JA 7 P P *** *** *** *** KO 8 P P *** 3.6 *** MA 9 P *** *** *** *** P PH P P ***.396 ***.3 ***.47 *** RU P *** *** -.7 ** *** P SG P P *** 3.93 ***.656 ** 3.53 *** TA 3 P P ** ***.7 ***.78 *** UK 4 P P *** ***. ***.97 *** US 5 P P ** *** ***.5 *** CPI M =M *** *** 4.9 ***.544 *** EX = *** *** -9.6 *** *** M M MR 3 M =M *** 5.85 *** *** 5.8 *** M 4 M =M -3.3 ** *** 4.73 *** OP 5 M =M *** ***.73 ***.38 *** Noe: ** and *** indicaes ha he corresponding null hypohesis is rejeced a he 5 and per cen significance level, respecively. 33

14 Applied Economerics and Inernaional Developmen Vol.7- (7) Figure 3. Plo of monhly sock reurns Argenina Ausralia Brazil Germany Hong Kong Indonesia Japan Korea Malaysia Philippines Russia Singapore Taiwan Thailand Unied Kingdom Unied Saes Sources: hp:// 34

15 Chanchara, S., Valadkhani, A., Havie.C. Macroeconomic Variables in Thai Sock Marke Figure 4. Plo of he monhly growh rae of he five macroeconomic variables Consumer Price Index Exchange Rae Money Supply. Moneary Rae Oil Prices Sources: hp://ifs.apdi.ne/imf/logon.aspx 35

16 Applied Economerics and Inernaional Developmen Vol.7- (7) Figure 5. Correlogram of squared residuals before capuring GARCH effec for pre-asian crisis period Sample: 988M-997M Included observaions: Source: auhors calculaions.

17 Chanchara, S., Valadkhani, A., Havie.C. Macroeconomic Variables in Thai Sock Marke Figure 6. Correlogram of squared residuals afer capuring GARCH effec for pre-asian crisis period Sample: 988M-997M Included observaions: Source: auhors calculaions. 37

18 Applied Economerics and Inernaional Developmen Vol.7- (7) Figure 7. Correlogram of squared residuals before capuring GARCH effec for pos-asian crisis period Sample: 998M-4M Included observaions: 84 Source: auhors calculaions. 38