(191) 瀞 * ** Granger Johansen (VECM)Granger 93 96 99% Linear ShiingTram Shiing * **
(192) Cae sizebaltic Caesize Index BCI 8 Panamax Baltic Panamax Index BPI 5~8 Baltic Suramax Index BSI 3~5 BCI BPI BSIBaltic Dry Index BDI BDI Eun & Shim, 1989Cheung & Mak, 1992Bailey & Stulz, 1990 1. BDIBCIBPIBSI US TWS 2. BDIBCIBPIBSI US Unit Root TestStationary Process VECMVAR Granger
(193) Veenstra & Franses1997 1983 9 1993 8 Fuller,1979 ADF Johansen 1990 Koekebakker, et al.2006 KSS Kavussanos & Nomikos 2003 BFI BIFFEX future ADFPPKPSS ADF Tvedt 2003 TCE ADF Alizadeh & Nomikos2007 PE P/E 1976-2004 PP KPSS Johansen SBCSchwartz Bayesian Criterion Granger Handysize Batch, et al.2007 FFA Kavussanos & Visvikis2004 ADFPPKPSS SBC Cheung & Mak1992 Granger causality test
(194) 1977 1988 global factorlocal factor Hammoudeh, et al.2004 1995/7/17 2001/10/10 ADF PP Banerjee, et al.1993adf AIC SBC Johansen 100 Nikkinen & Sahlstrom2004 1996 7 2000 2 ADF Granger Yang, et al. 2006G-7 data-determined VAR 1973-2003 ADF AIC Johansen CPI Syriooulos2007 1999 EMU EMU 1997 1 1 2003 9 20 EMU 1. EMU1997:1:1-1998:12:312. EMU1999:1:1-2003:9:20 ADF PP 5% Johansen trace testmaximum Eigenvalue test Granger EMU Yang, et al., 2006Sharma & Wongbango, 2002
(195) - US- TWS 1 2000 1 2007 12 1,622 BDI Clarkson Research Services Limited BDI BCIBPI BSI 1 UMG 99.88% 0.12% SNC 99.83% 0.17% TWN 93.38% 6.85% 1.77% CHI 99.77% 0.23% FST 96% 4% H1.1BDIBCIBPIBSI H1.2 H1.3 H1.4 H2.1BDIBCIBPIBSI H2.2BDIBCIBPIBSI H2.3BDIBCIBPIBSI H3.1BDIBCIBPI BSI H3.2 H3.3BDI H3.4BDI H3.5BDI
(196) H3.6 H3.7 H3.8 Fuller1976 Dickey and Fuller1979 Dickey-Fuller DF Augmented Dickey-Fuller ADF Phillis and Perron1988 PP ADF PP t t1 i ti1 t i2 1.ADFAugmented Dickey- Fuller Y Y Y 3.1 t 0 t1 i ti1 t i2 Y a Y Y 3.2 t 0 t1 1 i ti1 t i2 Y a Y at Y 3.3 Yt a0 intercet drift term at 1 i1 t Y i t i 1 t 2.PPPhillis and Perron ADF PP
(197) Y a + a Y 3.4 t 0 1 t1 t ~ ~ ~ Yt a0+ a1yt 1 2( T a t ) t 3.5 2 T t E t =0PP DF ADF Engle & Granger1987Co-integration Johansen trace testmaximum eigenvalue test 1.trace test H0 rank < r r H a rank r r+1 trace n () r T ln(1 ) i t 1 j T j H 0 r+1 1 2... n 0 0 r 1 0 2 0 r 0 r 1 r2 n 0 0 2.maximum eigenvalue test H0 rank = r r H a rank r=r+1 r+1 max (, rr1) Tln(1 r 1 ) r=0 r
(198) Granger1969 VAR X t Y t X X Y t i ti i i t i1 i1 Y Y X t i ti i i t i1 i1 3.10 white noise P Y X H 0 Y X Y X X Y H0 X Y X Y X Y F F F ( SSEr SSEc)/ P SSE /( N 2 1) 3.11 c SSE r SSEc N P log Batch, et al.2007 2 BCIBPI BSI
(199) J-B 5 2 BDI BCI BPI BSI 3.430 3.549 3.418 3.283 1.227 1.261 1.167 1.068 0.864 1.840 3.521. 0.287 0.312 0.285 0.257 0.468 0.380 0.305 0.421 0.442 0.155 0.118-0.051-0.153 0.057 0.045-0.271-0.324 0.029 0.755 0.875-0.544 0.135 2.095 2.159 2.164 1.956 1.642 1.737 2.787 2.672 3.062 2.381 1.784 J-B 56.05 * 54.08 * 48.11 * 74.17 * 144.51 * 136.13 * 113.29 * 161.45 * 207.10 * 105.88 * 104.80 * Prob. <0.0001 * <0.0001 * <0.0001 * <0.0001 * <0.0001 * <0.0001 * <0.0001 * <0.0001 * <0.0001 * <0.0001 * <0.0001 * * 5 3 BCI 3 BDI BCI BPI BSI BDI 1.0000 0.9959 0.9963 0.9895 0.9082 0.9176 0.9068 0.8241 0.8588 0.9355 0.6908 BCI 0.9959 1.0000 0.9871 0.9752 0.9070 0.9142 0.9020 0.8153 0.8446 0.9315 0.6861 BPI 0.9963 0.9871 1.0000 0.9867 0.8893 0.8989 0.8947 0.8191 0.8660 0.9256 0.6779 BSI 0.9895 0.9752 0.9867 1.0000 0.9150 0.9281 0.9147 0.8358 0.8660 0.9346 0.7051 0.9082 0.9070 0.8893 0.9150 1.0000 0.9900 0.9576 0.8998 0.8557 0.9449 0.8349 0.9176 0.9142 0.8989 0.9281 0.9900 1.0000 0.9487 0.9014 0.8587 0.9420 0.8434 0.9068 0.9020 0.8947 0.9147 0.9576 0.9487 1.0000 0.9075 0.8975 0.9272 0.7628 0.8241 0.8153 0.8191 0.8358 0.8998 0.9014 0.9075 1.0000 0.9415 0.8157 0.9093 0.8588 0.8446 0.8660 0.8660 0.8557 0.8587 0.8975 0.9415 1.0000 0.8238 0.8044 0.9355 0.9315 0.9256 0.9346 0.9449 0.9420 0.9272 0.8157 0.8238 1.0000 0.7171 0.6908 0.6861 0.6779 0.7051 0.8349 0.8434 0.7628 0.9093 0.8044 0.7171 1.0000 ADF PP 1. 2. 3.Enders
(200) 2004 4 ADF PP 1.11.2 1.3 random walk 5 4 - BDI BCI BPI BSI US TWS ADF -1.677-1.944-2.462-2.086-2.738-2.503 PP -1.599-1.753-1.740-1.719-2.673-2.453 ADF -2.311-2.903-2.654-1.931-1.761 PP -2.166-2.641-2.470-1.813-1.647 ADF SBC PP Eviews 5 - BDI BCI BPI BSI US TWS ADF -15.49996** -19.17462** -17.24787** -11.08671** -42.66414** -39.66892** PP -15.53929** -18.79801** -13.95616** -15.04342** -42.73068** -39.66670** ADF -38.62903** -39.23639** -38.51395** -37.68500** -42.95164** PP -38.40507** -39.08888** -38.36330** -37.34049** -43.08720** 1. ** 1%ADF PP 2. ADF SBC 3. PP Eviews 4. Dickey-Fuller1979 Johansen VECM
(201) 1-4 BDIBCIBPIBSI AIC 1 BDIBCIBPIBSI 2
(202) 3 4 6 7 BDIBCIBPIBSI H2.1 BDIBCIBPIBSI H2.2 H2.3 BDIBCI BPIBSI LR 6 7 LR 34456.80 LR 34460.99 LR LR=-2 LR LU =-234460.99-34456.80=-8.38< 2 (1) =3.84 VECM
(203) 6 Eigenvalue None * 0.031576 127.5142 At most 1 * 0.018201 75.66388 At most 2 * 0.017579 45.98067 At most 3 0.009721 17.32055 At most 4 0.000949 1.534258 3 Cointegrating Equations: Log likelihood 34456.80 * 5 7 - H 2.1 0 Eigenvalue None * 0.029852 120.0545 At most 1 * 0.017617 71.07886 At most 2 * 0.015428 42.35624 At most 3 * 0.009700 17.22968 At most 4 0.000914 1.478342 4 Cointegrating Equations: Log likelihood 34460.99 * 5 Granger AIC 2 8 BDI BCIBPI BSI BDI BPI BCIBPI BSI H3.1 8 H3.1 Null Hyothesis F-Statistic Probability BCI does not Granger Cause BDI 1.86549 0.15511 BDI does not Granger Cause BCI 16.5293 0.00000** BPI does not Granger Cause BDI 28.1484 0.00000** BDI does not Granger Cause BPI 17.9775 0.00000** BSI does not Granger Cause BDI 1.22388 0.29436 BDI does not Granger Cause BSI 115.949 0.00000**
(204) Null Hyothesis F-Statistic Probability BPI does not Granger Cause BCI 17.8015 0.00000** BCI does not Granger Cause BPI 13.9178 0.00000** BSI does not Granger Cause BCI 4.23621 0.01462* BCI does not Granger Cause BSI 64.8932 0.00000** BSI does not Granger Cause BPI 4.81748 0.00820** BPI does not Granger Cause BSI 114.847 0.00000** *** 51 H3.2 BDI BDI H3.3 BDI H3.4 BDI H3.5 10 5 H3.6 H3.7-3.2 3.7 10 9 H3.8 9 - H3.8 Null Hyothesis: F-Statistic Probability does not Granger Cause 4.5E-07 0.07965 does not Granger Cause 4.5E-07 0.07965 does not Granger Cause 8.76416 0.00016** does not Granger Cause 2.93214 0.05353 does not Granger Cause 6.97295 0.00096** does not Granger Cause 1.38823 0.24978 does not Granger Cause 12.6994 0.00000** does not Granger Cause 1.22617 0.29365 does not Granger Cause 10.2307 0.00000** does not Granger Cause 0.26871 0.76439 **
(205) BDIBCIBPI BSI VECMGranger ADF PP 5 1 Veenstra & Franses,1997avussanos & Visvikis,2004Koekebakker,et al,2006ikkiene & Sahlstrom,2004Syriooulos,2007 5% 1% avussanos & Nomikos,2003Elyas,et al,1998 Cheung & Mak,1992 Ghosh,1999 Yang,et al.,2006 BHMI 2001/1/2 2005/6/30 0.112183226 BSI 1041 BSI 2005/7/1 2007/12/24 581 1. Alizadeh,A., & Nomikos, N.(2007). Investment timing and trading strategies in the sale and urchase market for shis. Transortation Research Part B, 18, 126-143. 2. Ghosh, A. (1999). Who Moves the Asia-Pacific Stock Markets US or Jaan? Emirical Evidence Based on the Theory of Cointegration. The Financial Review, 34, 150-170.
(206) 3. Bailey, W., & Stulz, R. M. (1990). Benefits of International DiversificationThe Case of Pacific Basin Stock Market. Journal of Portfolio Management, 16, 57-61. 4. Banerjee, A., Dolado, J. J., Galbraith, W., & Hendry, D. F. (1993). Cointegration, Error-Correction, and the Econometric Analysis of Non-stationary Data. New YorkOxford University Press. 5. Batchelor, R., Alizadeh, A., & Visvikis, I. (2007). Forecasting sot and forward rices in the international freight market. International Journal of Forecasting, 14, 101-114. 6. Cheung, Y. L., & Mak, S. C. (1992). The International Transmission of Stock Market Fluctuation between the Develoed Markets and the Asian Pacific Markets. Alied Financial Economics, 2, 43-47. 7. Dickey, D. A. & Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of American Statistics Association, 74, 427-431. 8. Elyas, E., Perera, P., & Tribhuvan, N. P. (1998). Interdeendence and dynamic linkage between stock markets of Sri Lanka and its trading artners. Journal of Multinational Financial Management, 8, 89-101. 9. Enders, W. (2004). Alied Econometric Time Series. New YorkJohn Willey & Sons, Inc. 10. Engle, R. F. & Granger, C. W. J. (1987). Co-integration and Error Correction: Reresentation, Estimation and Testing. Econometrica, 55(2), 251-276. 11. Eun, C., & Shim, S. (1989). International Transmission of Stock Market Movements. Journal of Financial and Quantitative analysis, 24(2), 241-256. 12. Fuller, W. (1976). Introduction to Statistical Time Series. New YorkJohn Wiley. 13. Granger, C. W. J. (1969). Investigating Causal Relation by Econnometric Model and Cross-Sectral Method. Econometric, 36, 424-438. 14. Hammoudeh, S., Dibooglu, S., & Aleisa, E. (2004). Relationshis among U.S. oil rices and oil industry equity indices. International Review of Economics and Finance, 27, 427-453. 15. Johansen, S., & Juselius, K. (1990). Maximum Likelihood Estimation and Inference on Cointegration-With Alication to the Demand for Money. Oxford Bullentin of Economics and Statistics, 52, 169-210. 16. Tvedt, J. (2003). A New Persective on Price Dynamics of the Dry Bulk Market. Maritime Policy and Management, 30(3), 221-230. 17. Kavussanos, M., & Nomikos, N. (2003). Price Discovery, Causality and Forecasting in the Freight Futures Market. Review of Derivatives Research, 28, 203-230. 18. Kavussanos, M., & Visvikis, I. (2004). Market interactions in returns and volatilities between sot and forward shiing freight markets. Journal of Banking & Finance, 28, 2015-2049. 19. Koekebakker, S., Adland, R., & Sodal, S. (2006). Are Sot Freight Rates Stationary? Journal of Transort Economics and Policy, 24, 449-472. 20. Nikkinen, J., & Sahlstrom, P. (2004). International transmission of uncertainty imlicit in stock index otion rices. Global Finance Journal, 15, 1-15. 21. Phillis, P. C. B., & Perron, P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika, 75 (2), 335-346. 22. Syriooulos, T. (2007). Dynamic linkages between emerging Euroean and develoed stock markets: Has the EMU any imact? International Review of Financial Analysis, 20, 41-60.
(207) 23. Veenstra, A. W., & Franses, P. H. (1997). A Co-Integration Aroach to Forecasting Freight Rates in the Dry Bulk Shiing Sector. Transortation Research A, 31(6), 447-458. 24. Wongbango, Prahan & Subhansh C. Sharma. (2002). Stock market and macroeconomic fundamental dynamic interactions: ASEAN-5 countries. Journal of Asian Economics, 13, 27-51. 25. Yang, J., Guo, H., & Wang, Z. (2006). International transmission of inflation among G-7 countries: A datadetermined VAR analysis. Journal of Banking & Finance, 20, 2681-2700.