invesigae he lag relaionship linkage beween he sock marke of U.S. and he sock of Japan and he sock of Taiwan.According o he empirical resuls analysis,

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1 Discussing he linkage beween he sock marke of U.S. and he sock of Japan and he sock of Taiwan Ching-jun Hsu, Associae Professor, Deparmen of Financial Managemen, Nan-Hua Universiy Ming-Heng Wu, Posgraduae suden,deparmen of Financial Managemen, Nan-Hua Universiy ABSTRACT High-Tech. Indusry will become a sar indusry which is one of he mos look afer in nex cenury. Following his ide can no keep off, he high echnology caegory in Taiwan sock marke which he firs of he percenage a every one caegory sock ha o marke price and day rading volume. Form he news relae o equiy marke; Invesors can find ha he sock marke of Taiwan has conneced wih inernaional sock, herefore, we can use he mehodology of ime series o 265

2 invesigae he lag relaionship linkage beween he sock marke of U.S. and he sock of Japan and he sock of Taiwan.According o he empirical resuls analysis, we can find he profiabiliy of sock price index of every counry only has single causaliy and does no have feedback relaionship. The profiabiliy of sock price index of U.S. would affec he profiabiliy of sock price index of Taiwan and Japan. Then he profiabiliy of sock price index of Japan also effec he profiabiliy of sock price index of Taiwan. We can find he OEM/ODM relaionship migh affec each sock price index. Each sock price index rushes impulse reacion response analysis. No maer wha he bull period and he bear period is, would finish o reacion in he shor imes. Therefore, finding ha he index of he hree counry really have influence each and oher, bu is no overall Sabiliy of he OEM/ODM relaionship of each counry would affec sock price index in shor period. Keywords Sock price index, Impulse Response Analysis, Variance Decomposiion 266

3 IC (NASDAQ) IBM (Inel) (Compaq) (Dell) NEC Markowiz (1952,1959) ( Porfolio heory) (OEM) / (ODM) Grubel (1968) OEM 267

4 Lessard(1974) ( ) 1987 (1993) ( VAR Fisher and Palasvira (1990) 23 (1998) Granger NASDAQ NASDAQ Liu. e al.(1993) (VAR) 268

5 Grubel(1968) Makridakis & Wheelwrigh(1974) Solnick(1974) Bang Nam Jeqn & Von Fursenberg(1990) Maldonado & Saunders(1981) Bailey & Sulz(1990) NASDAQ ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) Granger and 269

6 Newbold(1974) (Efficiency) (1)Dickey-Fuller(DF) (2)Augmened Dickey-Fuller(ADF) (3)Phillips-Perron (PP) Akaike(1973) AIC(Akaike Informaion Crierion) Dickey&Fuller(1981) ADF Schwarz(1978) SBC(Schwarz Bayesian P ( AR(P)) Informaion Crierion) AIC Hsiao(1981) Υ Υ = p 1 + δ i 1 + ε i = 1 = β Υ (1) + βυ p 1 + δ i Υ i + ε i= 1 α (2) p 1 + δ i Υ i + ε i= 1 Υ = α + γ + βυ (3) Υ y Υ (FPE) VAR y (Firs difference) α Granger(1981,1986) Engle & Granger (Drif) ε (1987) Y =0 Y H 0 0( ) H 1 0( ) Engle & Granger(1987) VAR 270

7 k k i i i j + i= 1 j= 1 Johansen(1988) Υ = a + α Υ + β Χ µ (6) k k Χ = b + ε iχ i + δ jυ j + ν (7) (Gaussian vecor auoregressive model) i= 1 j= 1 (F-es) (Likelihood raio) H 0 β1 = β2 = β3 = β4 =... = βk = 0 Johansen(1988) (Trace es) (Maximum eigenvalue es) X Y H 1 δ1 = δ 2 = δ3 = δ 4 =... = δ k = 0 Rank( ) r =αβ Y r p X λ race = 2ln( Q; r) = T ln(1 ˆ λi ) (4) i= r+ 1 Rank ( ) = r + 1 Rank( ) = r ) λmax = 2 ln( Q; r r + 1) = T ln( 1 λr+ 1) (5) (Brownian Sim(1980) Moion) Granger(1969) (Vecor Auoregress model (Predicabliliy) VAR) VAR 271

8 (innovaion) Eun and Shim(1989) VAR Sims(1980) VAR m Y = α + β iy i + µ i = 1 ' ( ) 0 E µ E = (8) µ (9) ' ( µ ) = 0, s µ (10) s Υ n β i n n µ n 1 α n 1 Υ n 1 Υ i i VAR (persisence ) 87.6% (volailiy) % VAR

9 ADF ( 1999/2/5~2000/2/17) ( 2000/2/18~2002/1/31) (0) (0) (0) (0) (0) (0) * ** *** 10% 5% 1% 2 (0) ADF (0) ADF (0) ADF 273

10 2 ( 1999/2/5~2000/2/17) ( 2000/2/18~202/1/31) (0) (0) (0) (0) (0) (0) -6.93*** -7.16*** -7.13*** *** *** *** *** *** *** *** *** *** -8.28*** -8.80*** -9.11*** *** *** *** 1 * ** *** 10% 5% 1% 2 (0) ADF (0) ADF (0) ADF 1 AIC FPE 3 3 Lag ( 1999/2/5~2000/2/17) ( 2000/2/18~202/1/31) FPE AIC FPE AIC E-11* * 1.00E-10* * E E E E Trace 5% 1% None A mos A mos

11 5% None A mos A mos % * ** 5% 1% 5 Trace 5% 1% None A mos A mos % 1% None A mos A mos (2) Granger(1969) (3) Granger (4) 6 Granger ( ) ( ) Granger Granger 6 (1) 275

12 4.035 Granger (VAR) (VAR) Taiwan Japan America Response of Am erica o N onfacorized One S.D. Innovaions Response of Japan o N onfacorized O ne S.D. Innovaions R e s p o n se o f T a iw a n o N o n fa c o rize d O n e S.D. Inno va io ns Response of Am erica o N onfacorized One S.D. Innovaions Response of Japan o N onfacorized O ne S.D. Innovaions Response of Taiwan o Nonfacorized One S.D. Innovaions Taiwan Japan America 276

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14 ( ) 225 ( ) ( ) ( ) Granger

15 1 IBM HP Dell Inel Apple IC Packard Bell NEC Cae way PCB PC NB SPS 2 NEC Canon Ti HP IC (LCD) PCB PC NB SPS (LCD) (LCD) 279

16 Transmission of Sock Marke Movemens, Journal of Financial and Quaniaive 1 Analysis 24, pp , Fisher, K. P. & A. P. Palasvira., High 2 Road o a Global Markeplace: The Inernaional Transmission of Sock Marke Flucuaion, The Financial Review 25, 3 pp , Grubel, H. G., Inernaional Diversified 88 Porfolio: Welfare Gains and Capial 4 Flows, American Economic Review 58, ppl , Granger, C. W. J., Invesigaing Causal 82 Relaions by Economeric Models and 5 Akaike, H., Informaion Theory and an Exension of he Maximum Likelihood Cross-Specral, pp , Economeria 37, Principle, in B. P., and F. C. eds., Second 12 Granger, C. W. J., Some Properies of Time Inernaional Symposium on Informaion Theory, Budapes : Akademiai Kiado, Bailey, W., and R. M. Sulz., Benefis of Inernaional Diversificaion: The Case of Pacific Basin Sock Markes, Journal of Porfolio Managemen 16 summer, pp57-61, Bang N. J. & V. Fursenberg, Growing Inernaional Co-movemen in Sock Price Indexes, Quarerly Review of Economic and Business 3, ppl5-29, Dickey, D.A. and W.A. Fuller, Likelihood Raio Saisics for Auoregressive Time Series wih Uni Roo, Economerica 49, pp , Engle, R. F. & C. W. J. Granger, Coinegraion and Error Correcion : Represenaion, Esimaion and Tesing, Economerica 55, pp , Eun, C. and S. Shim., Inernaional Series Daa and Their Use in Economeric Model Specificaion, Journal of Economerics 16(1), pp , Granger, C. W. J., Causaliy, Coinegraion and Conrol,Economic Dynamics and Conrol 68, pp , Granger, C. W. J., Developmens in he Sudy of Coinegraed Economic Variables, Oxford Bullein of Economics and Saisics 48, no.3, pp , Granger, C.W.J. and Newbold, P., Superious Regressions in Economerics, Journal of Economerics 2(2), pp , Hsiao, C., Auoregressive Modeling and Money-Income Causaliy Deecion, Journal of Moneary Economics, Vol.7, pp , Johansen, S., Saisical Analysis of 280

17 Coinegraion Vecors, Journal of Economics and Dynamics and Conrol 12, pp , Johansen, S., Esimaion and Hypohesis Tesing of Coinegraion Vecors in Gaussian Vecor auoregressive Models, Ecorneria 59, pp , Johansen, S., The Role of he Consan and Linear Terms in Coinegraion Analysis of Nonsaionary Variables, Economeric Review 13(2), pp , Lessard, Donald R., World, naional and indusry facors in equiy reurns, Journal of Finance 29, pp , Markowiz, H. M., Porfolio Selecion, Journal of Finance, pp.71-91, Markowiz, H. M., Porfolio Selecion: Efficien Diversificaion of Invesmens, New York: John Wiley & Sons, Makridakis, S.G., and S.C. Wheelwrigh., An Analysis of he Inerrelaionships among he Major World Sock Exchanges, Journal of Business Finance and Accouning 1, ppl95-215, Maldonado, R and A. Saunders, Inernaional Porfolio Diversificaion and he Ineremporal Sabiliy of Inernaional Sock Marke Relaionships, Financial Managemen, pp54-63, Schwer, G. W., Effec of Model Specificaion on Tess for Uni Roos in Macoreconomic Daa, Journal of Moneary Economics, pp , Sims, Chrisopher A., Macroeconomics and Realiy, Economeria, Vol.48, pp.1-48, Solnik B., The Inernaional Pricing: A Empirical Invesigaion of he World Capial Marke Srucure, Journal of Finance, pp ,

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《金融评论》投稿封面 The Choice of he Inermediae Targe of Moneary Policy in China 968 993 5 0073 85957073683550599 yqzhang@cass.org.cn MM 994Q-008Q4 VECM M M GDPCPI M M M 007 VECM JEL E5C3E58 The Choice of he Inermediae Targe