臺灣博碩士論文加值系統

航運相關產業中，近年來以散裝航運市場變化最具挑戰性。其中散裝航運海岬型船市場不但承載貨源集中，運價變化亦最為激烈。因此，經營海岬型船之散裝航運公司，如何掌握市場運價變化，實乃經營成敗關鍵所在。本文主要採用灰色理論(Grey Theory)之灰預測模式與季節性灰預測模式(Seasonality Grey Model)，進行波羅地海海岬型船運價指數預測模式之構建。並根據德國航運經濟與物流研究中心(Institute of Shipping Economics and Logistics；ISL)之統計資料與波羅地海交易所(Baltic Exchange)發布之波羅地海海岬型船運價指數(Baltic Capesize Index；BCI)資料，分別應用於散裝海岬型船市場及其運價指數趨勢之分析。本文主要研究成果如下：
(一) 就海岬型船市場而言，承運貨源主要為鐵礦砂與煤炭，其貿易形態(Trading pattern)含蓋工業發展國家，其中又以中國影響貿易形態變化最大。整體而言，近年來海岬型船市場營運重心以遠東市場為主。
(二) 本文構建波羅地海BCI運價指數預測模式，以探求不同期間未來運價可能變動趨勢。整體而言，未來半年(2007年4-9月) BCI運價指數朝上漲趨勢發展。
(三) 有關傭船決策(Chartering decisions)之制定，預測結果考量區間預測值之範圍，並針對船東或傭船人之風險偏好，給定不同區間預測調整值，最後根據預測結果提出傭船決策法則。
期望研究結果可提出更詳細具體的資料，以提供船東或傭船人作為評估營運策略之參考。

In past few years, operation of bulk shipping faced the severest challenge among all shipping related industries. In the dry bulk market, Baltic Capesize not only concentrated the limited resource of goods but also accompanied with the most violent variation of freight rate and charter hire. Consequently, how the shipping companies manage the variation of freight rate and charter hire of Capesize is the key of successful management. This research mainly utilizes Grey Model (1,1) of Grey theory, Seasonality Grey Models to construct the forecast model of Baltic Capesize Index, which is applying the statistic data of the Institute of Shipping Economics and Logistics and the Baltic Exchange to the Capesize market and BCI development trend. The outcome of research as follows:
1. In terms of Capesize market, it points out that Capesize vessels mainly carry coal and iron, and developed countries of industry are covered with Capesize vessels’ trading pattern. Among these countries, China is one of the important countries which affect the global trading pattern. Consequently, the Far East is the core area of operation in Capesize market.
2. Constructing the forecast model of BCI, and derive the fluctuant trend of freight rate and charter hire in different periods. As far as outcome is concerned, BCI develop buoyantly in coming six months (from April to September, 2007).
3. Regarding the chartering decisions making, the forecast outcomes measure the scope of interval estimation and consider different risk preferences of shipowners and charterers, and then provide different adjusted value. Finally, according to the forecast outcome, the chartering decision-making policies are proposed in this research.
This research expects the findings to provide more detailed and accurate information of better operational business strategies for shipowners and charterers.

誌 謝 i
摘 要 ii
Abstract iii
目 錄 iv
表目錄 vi
圖目錄 vii

第ㄧ章 緒論 1
1.1 研究背景與動機 1
1.2 研究問題與目的 4
1.3 研究內容與方法 5
1.4 研究架構與流程 7
1.5 研究範圍與限制 10

第二章 文獻回顧與評析 11
2.1 市場運價與特性 11
2.2 效率市場與報酬 13
2.3 市場運價與船型 14
2.4 預測分析方法 15
2.5 綜合評析 21

第三章 海岬型船市場現況分析 22
3.1 波羅地海BCI運價指數演進過程 22
3.2 鐵礦砂進出口分析 26
3.3 煤炭進出口分 28
3.4 綜合討論 30
第四章 預測方法 31
4.1 灰預測方法 31
4.2 季節性灰預測 33
4.3 指數平滑法 35
4.4 預測精確度檢驗方法 37
4.4.1 灰預測滾動檢驗模式 37
4.4.2平均絕對百分比誤差 37
4.4.3均方差 38
4.4.4 Theil’s U統計量 38

第五章 海岬型船運價指數趨勢預測 40
5.1 BCI資料分析 40
5.2 灰預測結果分析 41
5.3季節性灰預測結果分析 49
5.4 預測結果比較分析 52
5.5 區間預測分析 56

第六章 結論與建議 58
6.1 結論 58
6.2 建議 60

參考文獻 61

附件一 波羅地海BCI運價指數 66
附件二 A History of the Baltic indices 74

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