定期船運價決定因素與趨勢預測之研究

Abstract

貨櫃運輸自1960年代萌芽興起後，經歷數十年的發展，已經是競爭非常激烈的成熟產業。大陸在亞太地區已成為最重要的經濟體之一，然而目前從大陸經濟發展角度來探討海運運價的文獻相當少。近年來，中國大陸海運事業的興起，已對全球海運市場注入許多新的變化。隨著歐盟的成立，成員國也日益增加，其經貿發展也會對貨櫃海運運價造成明顯衝擊。因此可以預見歐盟會員國經濟發展的情況、進出口貿易金額等總體經濟變數對定期船運價變動趨勢有一定程度的影響。

大多數先前關於海運運價預測的研究，都是以迴歸分析和時間序列分析法為主要的分析工具。這兩種分析法皆需要大量的資料來測試模式本身的機率分配及配適度。從歷史資料角度來看，海運運價上升最快速的時期是在近十年間。因此，蒐集COSCO及HANJIN兩間貨櫃船公司自2005年到2007年12月的遠東-歐洲線的基本運價，再配合BAF、CAF及PSS等資料，針對影響定期船市場景氣之因素做探討，嘗試利用灰色理論來分析及預測未來幾年定期船運價，因為灰色理論不需要大量資料來建構模式。同時也採用ARIMA時間序列建立預測模式，並加以比較兩種預測方法的準確性。期能提供船公司、貨主決策上的參考。

The container transportation began in 1960s. After several decades，it has become a mature industry and been competing violently. In recent years，China becomes one of the most important economies in Pacific-Asia area, but only few papers discussed China’s maritime freight rate in terms of China economic development. The growth of China maritime industry brings many changes for marine market. With establishment of European Union，and members of EU is increasing，the economic development of these members must have obvious impact on liner marine freight rate. Therefore it can expect the economic development and some macro variables of EU members have influence on the trend of fluctuation about liner marine freight rate.

Regression model and time series model were the main tools in most of previous researches about marine freight rate prediction. They needed large amount of data for testing the probability distribution and curve fitting. In historical data perspective，marine freight rate increases rapidly only about ten-year period. Therefore, collecting data basic freight、BAF、CAF、PSS of two liner shipping company COSCO and HANJIN about the route from Far East to Europe. And we will also use Gray Theory to make the analysis and prediction, because it does not need large amount of data to formulate the model. We also try ARIMA time series, and compare the results. Expecting to provide references about decision-making for liner shipping company and shippers.