Analyses of Influential Factors and Forecasting of Baltic Dry Index: Markov Chain and Entropy Grey Theory Modeling

• Main Authors: SHENG YI FAN, 范聖義
• Other Authors: HSIEN LUN WONG
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/73452731043964673771

碩士 === 明新科技大學 === 企業管理研究所 === 97 === Maritime industry plays an important role in international trade. International tramp bulk marine market is a perfectly competitive market. The market price depends on the equilibrium of supply and demand of the market. The changes of the freight rates and the charter hires are influenced by many unpredictable factors. It makes the enterprise to confront enormous operation risk and uncertainty. As such, knowing and grasping the factors attributable to the volatility of freight rates will greatly enhance the profitability of the market participants. Baltic Dry Index (BDI) is a freight index of the market. The importance of BDI is that the change of shipping freight can be observed from the variation pattern of that index. This study aims to explore factors influencing the change of Baltic Dry Index, as well as to find out a suitable method and model to forecast the change of this index. The data employed in this research covers from January 2006 to Jnne 2008 on the Monthly basis. We adopted the Grey Relational Analysis (GRA) and Entropy methods to explore factors influencing the change of BDI.We also applied the GM(1,1)、GM(1,1)Alpha model and grey Markov chain to predict the BDI and examined the accuracy by applying the mean absolute percentage error (MAPE). The empirical results showed that freight rates are significantly affected by the prices of raw materials. From strong to weak ranking are the international steel prices, international crude oil prices, grain prices and coal prices. On the other hand, the precision of grey Markov chain for forecasting BDI is better than that of GM(1,1)and GM(1,1)Alpha model. The results of this research can provide information to the market participants for their decision-making.