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1 : 3 :, :,,, : GARCH,,,,,, (,2003),,, (,2007),, Lynch (2002), ; Sharma (1998), GED GARCH GARCH ;Hamilton (2000) GDP, (,, 2004 ;,2003 ;,2006 ;,2006 ;,2005),, (2003) ARCH ; (2005) GARCH Granger ; (2007),,,,, Chen and Liu (1993) Gomez and Maravall (1997) Charles and Darne (2005), GARCH ; Hamao (1990) ; Granger, 3,, :100029, com ;,, :361005, : edu. cn ( : 07BJ Y065), 130

2 ;,, ( ),,,,, ;,,,, (2006) 6, :,,,, OPEC, 10,, 30 %, 9 Π,,12 Π 20 80,, ( 5 Π ), Π, 10 Π, (2003),,, ( ) 100,, (, ) 5,, 10,,, (, 2005), ( ),,,,,,(WTI),, WTI, 50 %, 131

3 : OPEC, OPEC,,,, (,2005) ( ) (1) 1981,, , ,,, (2) ,, 1,,,,, Π ,,,,, (3) ,, :,,,, 5 % (,2006),, 5 %,,, ,, ; 8 %, ( ), :,,, (,2006),,, WTI Brent Dubai 50 % Brent,,Brent,,,, 40 %, Brent,

4 Brent DP WP, 1 1,,,, (outliers) ( ), (Charles and Darne, 2006) Box and Tiao (1975), Chen and Liu (1993), Gomez and Maravall (1997) Charles and Darne (2006) ARIMA, 1 :DP ;WP ARIMA(p, d, q) y 3 t :, B, a t ( B) ( B) y 3 t = ( B) a t (1), ( B ) ( B ) ( B ) d p q, ( B) ( B), ( B) :, y 3 t y t = y 3 t + m j = 1 j j ( B) I t ( j ) (2) ARIMA, j ( B) t = j, j j ( B ), m, I t ( j ) : I t ( j ) = 1 if t = 0 otherwise Chen and Liu (1993), 4 : (AO) ( IO) (LS) (TC) ( B) : AO : AO ( B) = 1 IO : IO ( B) = ( B)Π ( B) ( B) LS : LS ( B) = 1Π(1 - B) TC : TC ( B) = 1Π(1 - B) :AO ;LS ; TC, (0 < < 1),IO,IO, (Chen and Liu, 2003) AOs IOs TCs LSs j (http :ΠΠwww. eia. doe. govπ) IO, 133

5 :,TCs, LSs, IO, LSs IOs ( ) AOs IOs (Balke and Fomby,1991 ;Maddala and Kim,2000),, 1 TRAMO T2, 1 WP IO t IO , DP IO , TC , ,, 9 11, 9 11, TC TC AO 4110,3 ( TCs), 2, Charles and Darne (2005) YC1 YC2, Brent DPC WPC, YC1 = 100log (DPCΠDPC ( - 1) ) YC2 = 100log (WPCΠWPC( - 1) ) , JB (P ), ( < 0101) ( < 0101), AC(1) , Q(P ) (0100) (0100), ARCH, Q(10) (0100) (0100),, Q 2 (10) (0100) (0100) ADF (P ) (0100) (0100) : 3,JB,AC(1) 2 1 Q Q(10) Q 2 (10) Liung2Box,, 1 10,, 0, ( < 0101) P ADF 5 %, 2,Q,Q 2 (10),,, ARCH, 134 ( ) GARCH

6 ,, ( Engle,1982),, GARCH, GARCH GARCH (p, q),, Y t ARMA(m, n) :, X t Y t = + X + t m i Y t - i n + t - j j = 1 j + t (3) I t - 1 = { Y s, s s t - 1},, ( t I t - 1 N (0, h t ) ) : h t i t - i + = q p j = 1 j h t - j (4) 0 > 0, i 0, j 0, q, j = 1 p,,, GARCH ( ),, Hamao (1990) GARCH : GARCH ;, B 2 Bt - l t - l, A t,, Hamao (1990), B A : h At = + < i q 2 At - i + p j = 1 j h At - j r + l = 1 2 l Bt - l (5) 2 Bt - l l B,,, ( ),, (,Tsay, 2005) ( ), : ,, ; ,, 135

7 : Z: , 1,,, Z,, : ,, 3 3 AIC SC R 2, 1, Q 1, 1, :, :Q 2 (10) = 5210 ( P = 0100), ( YC1) C Z YC1 ( - 1) MA(1) (1169) ( ) (8175) (1158) (8182) (8193) (1157) ( ) (7152) (1143) (7160) (7176) R DW logl SC AIC :, t, 3 10 % ARCH LM, 5 %, 4 ARCH 0, GARCH, GED GARCH GED GARCH(1,1) : : : YC1 t = (1193) Z t ( ) h1 t = (1120) t - 1 (2109) R 2 = 0112,LogL = ,AIC = 5144,SC = 5150 Q(10) = 8130 (P = 0150),Q 2 (10) = 5193 (P = 0175) t - 1 (7140) h1 r- 1 (4118) + 1 t (6) ARCH GARCH, AIC, GARCH 10 Q (P) 10 %, GARCH, (7) ARCH GARCH 01825, 1, 136, : : (7)

8 : YC2 t = YC2 t - 1 (10192) t - 2 (4164) YC2 t - 2 ( ) t - 3 (7193) h2 t = (1146) t - 1 (1193) R 2 = 0113,LogL = ,AIC = 5149,SC = 5160 Q(10) = 2145 (P = 0187),Q 2 (10) = 6171 (P = 0135) YC t - 4 (1175) t - 4 ( ) h2 t - 1 (10130) YC2 t - 6 ( ) t - 6 (2123) + 2 t (8) GARCH 2 GARCH,ARCH ( ) GARCH ( ), ( + ) 1, + = < 1, = 01736, 7316 % ; Brent = 01066, = 01847, 1, 8417 %, 2,, :,,,,, ,, 2 ( H1) ( H2),,,, ( (7) (9) ) 2,, (21346) (11264),,, ( ) Hamao, AIC 3 4 :,,h1,, h2,, 3 10 % ,,,,, (9) 137

9 :, 4 C h1 1 2 t t t t t t T h T ( ) 11 Granger 5 YC1 YC2 Granger Granger, F ( 5), 5 % YC2 YC1 Granger E205, Granger, YC1 YC2 Granger , : 2. (P ) 2max (P ) (010001) (010000) (018992) 1135 (018992) : 3 5 % DPC WPC Johansen SC HQ VAR 2,, 6 : ln ( DPC) = ln ( W PC) (10) (0106) (0102),, Brent 0198 VAR ( ),, VAR 3 ( : ), ( : ) : 30 %, 2 35 %, 5 40 % ;, 5 20 %, ( ) 138

10 , 6 %,, 90,,,,,, 3., : ecm ( ecm t ln ( DPC t ) = ecm t - 1 (0104) ln ( W PC t ) = ecm t - 1 (0104) i i 2 ln ( DPC t - i ) + 2 ln ( DPC t - i ) + = ln ( DPC t ) ln ( W PC t ) ) 2 i ln ( W PC t - i ) (11) 2 i ln ( W PC t - i ) (12),,,, 715 % ;,,,, ;,,, ;,,, ( OPEC ), VEC,,,,VEC,,, :,,, 9 11,,, 139

11 :,,,,,,, ;,,,,,,,, ( ), :, 50 %,,, 7000, 60 %, 1,, ( ),,,,,, ( ),,,,,,,,, 2005,242, 590, 3, 119, , 72 %( 2020 ), (63 %) ; ; ( 50 % ) ( 60 % ),, :,,,,,,2003 : ARCH, ( ) 4,2006 :, ( ) 2,2004 :, 3 140

12 ,2005 :,6,2006 :, 10,2007 :,,2006 :,,2005 :, 8,2003 :,9,2006 :,,2003 :,,2007 :, 4 Balke, N. S., Fomby, T. B., 1991, Shifting Trends, Segmented Trends, and Infrequent Permanent Shocks, Journal of Monetary Economics, 28, Bollerslev, T., 1986, Generalized Autoregressive Conditional Heteroscedasticity, Journal of Econometrics, 31, pp Box, G. E. P., and Tiao, G. C., 1975, Intervention Analysis with Applications to Economic and Environmental Problems, Journal of the American Statistical Association, 70, pp Charles, A., and Darne., O., 2006, Large Shocks and the September 11th Terrorist Attacks on International Stock Markets, Economic Modelling, 23, pp Charles, A., and Darne., O., 2005, Outliers and GARCH Models in Financial Data, Economic Letters, pp Chen, C., and Liu, L., 1993, Joint Estimation of Model Parameters and Outliers Effects in Time Series, Journal of the American Statistical Association, 88, pp Engle, R. F., 1982, Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation, Econometrica,Vol. 50, pp Engle, R. F., and Granger, C. W. J., 1987, Co2integration and Error Correction : Representation, Estimation, and Testing, Econometrica, 55, pp G mez, V., Maravall, A., 1997, Programs TRAMO and SEATS: Instructions for the User (beta version : June 1997), Working Paper No , Direcci n General de An lisis y Programaci n Presupuestaria, Ministerio de Econom a y Hacienda, Madrid. Hamilton, J. D., 2000, What is an Oil Shock? http :ΠΠwww. nber.orgπpapersπw7755. Harmo, Y., and Masulis. R. W., 1990, Correlations in Prices Changes and Volatility across International Stock Markets, Reviews of Financial Studies, 3, pp Johansen, S., 1988, Statistical Analysis of Co2integration Vectors, Journal of Economic Dynamics and Control, 2, pp Lynch, Michael C., 2002, Causes of Oil Price Volatility, Eighth International Energy Forum, 9, Maddala, G. S., Kim, I. 2M., 2000, Unit Roots, Cointegration and Structural Change. Cambridge University Press. Sharma, N., 1988, Forecasting Oil Price Volatility, http :ΠΠscholar. lib. vt. eduπthesesπavailableπetd πunrestrictedπetd. pdf. Tsay, R. S., 2005, Analysis of Financial Time Series, 2 nd, A John Wiley & Sons, Inc. International and Domestic Oil Price Volatilities and Their Interrelationship Wei Weixian and Lin Boqiang (School of International Trade and Economics, University of International Business and Economics ; China Center for Energy Economics Research, Xiamen University) Abstract :Based on an analyzing of international and domestic oil prices formation mechanism, several new econometric methods are applying to the volatilities in oil prices and their relationship. The empirical results show that the oil price volatilities show clustering, continuance and risk spillover effects, and the international oil price volatility has absolutely leading effect to the domestic market ; long2term cointegration between the two markets is prominent, but they have different short2term volatility processes. Key Words :Oil Price ; Volatility ; GARCH Model ; Spillover Effects ; Cointegration JEL Classification :Q410,Q430 ( : ) ( : ) 141

(156) / Spurious Regression Unit Root Test Cointergration TestVector Error Correction Model Granger / /

(156) / Spurious Regression Unit Root Test Cointergration TestVector Error Correction Model Granger / / (155) * ** / / / / 1973 ~1974 1979 ~1980 1987 ~1989 * ** (156) 1990 2004 1997 1996 1980 / Spurious Regression Unit Root Test Cointergration TestVector Error Correction Model Granger / / (157) Hedonic Price