| Summary: | 碩士 === 國立東華大學 === 國際企業學系 === 101 === Supply and demand in the global market, especially, major dry bulk Maintain energy, infrastructure construction materials, food and other derived demand. They indirectly meet the business operations and community survival. Can achieve their transportation goals by dry bulk carrier. The Baltic Dry Index (BDI) is one of the leading indicators of world bulk shipping rates. Consequently, changes in BDI indicate the prosperity of the dry bulk shipping industry. In the past, raw material prices should have a close relationship with the changes of dry-bulk shipping freight indices. This study contain all of major dry bulk, this means that altogether 67.9% of the total world shipment volumes. This study encompass a wide range of BDI. The BDI factors in the four different sizes of oceangoing dry bulk transport vessels. We have a total of thirteen variables. The data employed in this research were daily data from November 5, 1987 to April 18, 2013. From the existing researches and studies, very few undertook a comprehensive research of both volatility and long run equilibrium. Price of major dry bulk and BDI investigate the forecasting of shipping market variables, these includes the demand, the risk, the volatility and the causality. This research take price of major dry bulk and BDI as the analysis object, and compares with Optimum based GARCH, TGARCH and EGARCH model, and have taken the GARCH model to investigate characteristics of price volatility in the bulk shipping industry, then examines the long-term equilibrium relationships between dry bulk prices and dry-bulk shipping freight indices by Johansen co-integration test. The results indicated that all variables have volatility clustering effect except for BSI. Most market which received good news have a higher fluctuation of shock than those received bad news. Existence of long-term equilibrium relationship, has a close correlation with dry bulk industry and freight. In addition, the results of Granger-Causality tests show that indicating that the inclusion of change information of maize price does improve the forecasting accuracy, especially for BHMI and BSI indices; the empirical results indicate that the fluctuation of the BDI index is most closely correlated with the BPI, followed by soybean prices and BCI. The conclusion has a beneficial guidance for decision-making in the bulk shipping industry.
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