隨著近年來新興國家之迅速發展，在人口上升與頻繁工程建設下，帶動以原物料為主要運輸物之散裝航運市場迅速成長，導致原物料運輸需求增加，造成散裝船各市場皆處於劇烈波動之情況，尤其是散裝航運之二手船市場面臨二手船價格波動劇烈之高風險。所以若能有效掌控與預測未來二手船價格可能之波動情形，對於市場之參與者而言，可提供降低市場風險之重要資訊。
由於散裝航運之二手船價格資料具有強烈之季節性與週期性之特性，所以在本文中將採用時間序列分析方法，透過季節調整與濾波分析方式將二手船價格中之週期因素分解出來，而在二手船市場中，有許多種不同船齡與不同大小之船型，其中以船的載重噸位DWT(Dead Weight Tonnage)區分為三種主要船型，由大到小依序為海舺型(Capesize)、巴拿馬極限型(Panamax)以及輕便極限型(Handymax)船，本文將對於三種船型船齡五年之月平均價格資料進行分析。
在本論文之中，主要使用時間序列X-11季節調整方法與階段平均法PAT (Phase average trend)來分析散裝航運二手船市場的週期因素(Cyclical component)，為了更加了解與掌握週期之走勢與波動，在本文中提出一個預測模型用來預測二手船價格之週期行為與走勢。對於模型預測能力之驗證，採用平均絕對誤差百分比MAPE (mean absolute percentage error)判斷基準，MAPE對於本文所建立之預測模型之檢驗結果皆低於20%，因此，表示透過預測模型之建構，能夠有效了解且預測未來散裝航運市場二手船價格之週期變動，以降低市場參與者對於二手船價格劇烈波動下所承受之風險。

The purpose of this research is to develop a novel model to forecast the cyclical movements for the monthly secondhand ship price for three different vessel sizes (Capesize, Panamax and Handymax) in the dry bulk market over the period of January 1996 to December 2007. Both X11 decomposition method and the Phase average trend (PAT) method are applied in the extraction of the cyclical components. The empirical results indicate that there are two whole cycles during the research period for Panamax and three whole cycles for Capesize and Handymax. This research builds some prediction models to approximate these whole cycles and to predict the full cyclical movement from the last trough point of this research for each vessel size. This study adopted the mean absolute percentage error (MAPE) validate the accuracy of these kinds of models. MAPE value in practical models is found to be varying from 0.004 to 0.17 in different cycles. All the value of MAPE less than 0.2, it suggests that the novel model gives a good prediction for the cyclical movements for secondhand ship price. The results of forecasting model for three different vessel sizes reveal that the next cyclical trough point beyond this research period is around late 2009. From this point, this study predict the trough of international economics could be on the mid or end of 2009, followed by a three years sideway, the next recovery stage could happen in 2012/13.

CONTENTS I
LIST OF TABLES II
LIST OF FIGURES III
CHAPTER 1 Introduction 1
1.1 Research motivation and background 1
1.2 Research objective 2
1.3 Research scope 3
1.4 Flow chart 4
CHAPTER 2 Literature Review 6
2.1 Time series analysis 6
2.2 Detrending method 10
2.3 Model accuracy with MAPE 12
2.4 Summary 14
CHPATER 3 Methodology 15
3.1 Data collection 15
3.2 Time series 16
3.3 X11 time series decomposition 16
3.4 Phase average trend (PAT) 18
3.5 The novel prediction model 22
3.6 Mean absolute percentage error (MAPE) 26
3.7 Summary 27
CHPATER 4 Empirical Analysis 28
4.1 Data description and statistics 28
4.2 PAT analysis of dry bulk secondhand ship price 31
4.3 Numerical analysis for the cycle movements 34
4.3.1 Numerical analysis for the cycle movements in the Capesize market 34
4.3.2 Numerical analysis for the cycle movements in the Panamax market 38
4.3.3 Numerical analysis for the cycle movements in the Handymax market 40
4.4 Forecasting 43
4.5 Summary 46
CHPATER 5 Conclusion and Suggestion 48
References 53

Table 3-1 Typical MAPE Values and Interpretation………………………………………27
Table 4-1 Descriptive Statistics for Dry Bulk Secondhand Ship Price, from Jan-1996 to Dec-2007 30
Table 4-2 The Durations of Recovery and Recession of Capesize Secondhand Ship Price. 33
Table 4-3 P The Durations of Recovery and Recession of Panamax Secondhand Ship Price 33
Table 4-4 The Durations of Recovery and Recession of Handymax Secondhand Ship Price 34
Table 4-5 Performances of Predicted Models in different Vessel Sizes 47

Fig. 1-1 Research Flow Chart 5
Fig. 3-1 The Approximated Change Rate and Variation Trend of Secondhand Ship Price Relative to the Period Studied 23
Fig. 3-2 Comparison of Approximating Data Distribution of Different Deviation Values in the Dry Bulk Secondhand Ship Market. 24
Fig. 3-3 Comparison of Approximating Data Distribution of Different Month of Maximum Values in the Dry Bulk Secondhand Ship Market. 25
Fig. 3-4 Comparison of Approximating Data Distribution of Different Initial Values in the Dry Bulk Secondhand Ship Market. 25
Fig. 3-5 Comparison of Approximating Data Distribution of Different Peak of Variation in the Dry Bulk Secondhand Ship Market. 26
Fig. 4-1 Historical Secondhand Ship Prices for Capesize , Panamax and Handymax from 1996–2007. 30
Fig. 4-2 Seasonally Adjusted Series (STC), Trend (T) and Cycle (C) for Capesize Secondhand Ship Price from 1996 to 2007 31
Fig. 4-3 Seasonally Adjusted Series (STC), Trend (T) and Cycle (C) for Panamax Secondhand Ship Price from 1996 to 2007 31
Fig. 4-4 Seasonally Adjusted Series (STC), Trend (T) and Cycle (C) for Handymax Secondhand Ship Price from 1996 to 2007 32
Fig. 4-5 Prediction Model and Original Data of the First Cycle for Capesize Secondhand Ship Prices 36
Fig. 4-6 Prediction Model and Original Data of the Second Cycle for Capesize Secondhand Ship Prices 37
Fig. 4-7 Prediction Model and Original Data of the Third Cycle for Capesize Secondhand Ship Prices 37
Fig. 4-8 Prediction Model and Original Data of Three Whole Cycles for Capesize Secondhand Ship Prices (Whole Cycle Period). 38
Fig. 4-9 Prediction Model and Original Data on the First Cycle for Panamax Secondhand Ship Prices 39
Fig. 4-10 Prediction Model and Original Data of the Second Cycle for Panamax Secondhand Ship Prices 40
Fig. 4-11 Prediction Model and Original Data of Three Whole Cycles for Panamax Secondhand Ship Prices (Whole Cycle Period) 40
Fig. 4-12 Prediction Model and Original Data on the First Cycle for Handymax Secondhand Ship Prices 42
Fig. 4-13 Prediction Model and Original Data of the Second Cycle for Handymax Secondhand Ship Prices 42
Fig. 4-14 Prediction Model and Original Data on the Third Cycle for Handymax Secondhand Ship Prices 43
Fig. 4-15 Prediction Model and Original Data of Three Whole Cycles for Handymax Secondhand Ship Prices (Whole Cycle Period) 43
Fig. 4-16 Prediction Model and Original Data for Capesize Secondhand Ship Prices 45
Fig. 4-17 Prediction Model and Original Data for Panamax Secondhand Ship Prices 45
Fig. 4-18 Prediction Model and Original Data for Handymax Secondhand Ship Prices 46

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