全球經濟與貿易環境變化快速,最近幾年鋼價波動幅度增大,進而影響許多相關產業,對散裝航運業影響深遠。在散裝乾貨市場中,運送鐵礦砂和煤炭的波羅的海海岬型船指數因為受到鋼價影響而變化劇烈相同,同時也面對極大的風險。本研究採用多變量時間數列模型做為理論基礎,主要針對波羅的海海岬型指數 (BCI) 和亞洲鋼價指數 (ACRU) 此兩數列進行指數預測與變動分析。主要目的為探討BCI和ACRU指數之關連性與落遲性,實證結果BCI與ACRU指數中各變數因果關係與方向顯示如下: (1) BCI和ACRU的最適模型為VARMA (2, 2)。 (2) BCI和ACRU兩者之間存在雙向之影響關係模型亦存在長期均衡關係。 (3) BCI與ACRU彼此各有兩次乘數效果與誤差修正項。 研究所獲得的結果可提供投資者做為參考,如此將可以提高投資者於亞洲鋼鐵物價指數變動的預測效果,藉由本研究結果將有利於投資者做出最佳決策。
The global economic and trade has been changing rapidly. For the past few years, the fluctuation of steel price has had a high level of volatility, and caused a significant effect upon many relative industries, especially for bulk shipping industry. In the dry bulk market, Baltic Capesize which carries the goods include iron ore and coal, accompanied with the most violent variation of fright fare and faces relatively high risks. In this paper we adapt the VARMA model to describe the relationship between the BCI and the ACRU index. After investigating and analyzing, the results of this research are as follows: (1) The BCI and the ACRU index for these two series on the best model of each other are VARMA (2, 2). (2) The BCI and the ACRU index have two-way influence relationship. (3) The ACRU index leads the BCI. The research expects the findings to contribute more detailed and accurate information of better operational business strategies to investor or ship carriers.