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研究生:黃銘德
研究生(外文):Ming-Te Haung
論文名稱:國際散裝海運市場與原物料運量因果關係之研究
論文名稱(外文):Causality Analysis between Raw Materials and International Dry Bulk Market
指導教授:張瀞之張瀞之引用關係
指導教授(外文):CHING-CHIH CHANG
學位類別:碩士
校院名稱:國立成功大學
系所名稱:交通管理學系碩博士班
學門:運輸服務學門
學類:運輸管理學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:中文
論文頁數:59
中文關鍵詞:VEVM模型VAR模型論時傭船佣金因果關係檢定
外文關鍵詞:Timecharter rateVAR modelVEVM modelGranger Causality test
相關次數:
  • 被引用被引用:2
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自2002年起原物料之需求在世界經濟成長下不斷增加,間接影響國際散裝海運運價指數使得運費指數居高不下,2008年下半年由於全球景氣受到次貸風暴衝擊,海運市場亦隨著景氣衰退,大幅度下跌。因此對海運業者來說,海運運費的暴漲報跌增加了營運不確定性與風險。因此,如果能瞭解影響運價的因素,就能對市場參與者的經營決策提供重要的參考資訊,有效降低其營運的風險。
本文利用榖類、鐵礦砂、煤炭及鋼製品對海岬型、巴拿極限型與極限適宜型散裝貨輪6個月期論時傭船佣金為變數,藉由向量自我迴歸模型(vector autoregression; VAR)及向量修正誤差模型(Vector Error Correction Model; VECM Model)來探討榖類、鐵礦砂、煤炭及鋼製品等運量與海岬型、巴拿極限型與極限適宜型散裝貨輪6個月期論時傭船佣金間之連動關係,藉由實證剖析不同船型的傭船費用是否有長期均衡現象,以及各個船型的傭船費率變動與所運送貨物的運載量變動是否有長期均衡現象。更進一步探討運送貨物運量在落後幾期下會影響單一船型的租金費率及各變數間的因果關係,本研究得到幾項結論如下:(1)單根檢定顯示所研究的變數之時間序列,呈現非定態序(Non-stationary);經一次差分後變數之時間序列呈現定態時間序列。(2)Johansen共整合檢定與VAR(VECM),顯示三種船型之論時傭船租金間存在長期均衡關係。(3)因果關係檢定(Granger Causality Test) ,顯示海岬型傭船費率居於影響其他船型運費的地位,且具有單向因果關係。
The demand for the raw materials is increasing constantly under the development in economy of the world in 2002, influence the freight rate with international dry bulk market; make the international freight rate remain high. Due to the crisis of Subprime mortgage, the economy of the marine shipping industry continues recession rapidly from the second half of the 2008. However, shipping industry still faces relatively high risks, coming mainly from the volatile freight rates. As such, knowing the factors attributable to the volatility of freight rates will greatly enhance the profitability of the market participants.
This research regards capsize 6 month timecharter rate, panamax 6 month timecharter rate, handysize 6 month timecharter rate, and raw materials as the research variables, the methodology are Vector Auto-regression and Vector Error Correction Model. The finding on this paper could be summarized as: (1) empirical tests of all variables are non-stationary. However, they are all stationary after using first difference. (2) Johansen co-integration and VAR(VECM)test is discovered that the ship price followed capsize 6 month timecharter rate, panamax 6 month timecharter rate, and handysize 6 month timecharter rate with one common stochastic trend. (3)The panamax 6 month timecharter rate and handysize 6 month timecharter rate are Granger Cause by capsize 6 month timecharter rate.
第一章緒論..............................................1
1.1研究動機.............................................1
1.2研究目的.............................................3
1.2研究背景.............................................4
1.2研究流程.............................................5
第二章文獻回顧..........................................8
第三章研究方法.........................................15
3.1資料來源及假設......................................15
3.1.1資料來源..........................................15
3.1.2研究假設..........................................16
3.2計量方法說明........................................18
3.2.1單根檢定..........................................19
3.2.2共整合檢定........................................22
3.2.3因果關係檢定......................................23
3.2.4向量修正誤差模型..................................24
3.2.5向量自我迴歸模型..................................26
第四章實證分析.........................................28
4.1資料分析............................................28
4.1.1研究範圍及資料來源................................28
4.1.2變數定義與簡稱....................................31
4.1.3變數之敘述統計分析................................31
4.2資料單根檢定分析....................................33
4.2.1 Augmented Dickey-Fuller 單根檢定.................33
4.2.1 PP單根檢定.......................................34
4.2.1 KPSS單根檢定.....................................35
4.3Granger Causality Test..............................37
4.4共整合檢定..........................................41
4.4.1三船型間共整合檢定................................42
4.4.2海岬型與貨物運載量間共整合檢定....................43
4.4.3巴拿馬極限型與貨物運載量間共整合檢定..............44
4.4.4極限適宜型與貨物之運載量間共整合檢定..............45
4.5VAR&VECM............................................46
4.5.1三船型間VECM分析..................................48
4.5.2巴拿馬極限型與貨物之運載量間VECM分析..............50
4.5.3極限適宜型與貨物之運載量間VECM分析................50
4.5.4海岬型與貨物之運載量間VAR分析.....................51
第五章結論與建議.......................................53
5.1結論................................................53
5.2建議................................................54
參考文獻...............................................55
ㄧ、中文文獻
林光、張志清(2006)。航業經營與管理( 第四版)。台北:航貿文化。
楊奕農(2006)。時間序列分析經濟與財務上之應用,初版。台北:雙葉書局。
交通部統計處。中華民國94年台灣地區進出口貨品運保費統計報告。
溫珮伶(2005)。散裝海運市場運價決定機制及影響因素分析。中原大學國際貿易學 系碩士論文,未出版,中壢。
陳永順(2004)。運價波動與最適避險模型之研究-以散裝海運界為例,國立台灣海洋大學博士論文,未出版,基隆。
二、英文文獻
Adland, R., & Strandenes, S. P. (2004). A Discrete-time Stochastic Partial Equilibrium
Model of the Spot Freight Market. Norwegian School of Economics and Business
Administration, Discussion Papers, November.
Andreou, E.,Osborn, D.R.,& Sensier, M.(2000). A comparison of the statistical properties of financial variables in the USA, UK and Germany over the business cycle, Manchester School, Blackwell Publishing,68(4),396-418, Special I.
Adland, R., & Strandenes, S. P. (2006).Market efficiency in the bulk freight market revisited, Maritime Policy & Management, 33(4), 107-117.
Berg-Andreassen, J. A. (1996). Some Properties of International Maritime Statistics. Maritime Policy and Management, 23(4), 381–395.
Dikos, G., & Papapostolou, N. (2002). The assessment of market efficiency in the shipping sector: a new approach, Maritime Policy & Management: An International Journal of Shipping and Port Research, 29(2), 179-181.
Engle,R.F., &Granger,C.W.J.(1987). Co-integration and Error Correction: Representation, Estimation and Testing. Econometrica, 55(2), 251-276.
Granger, C.W.J., & Newbold, P. (1974). Spurious Regressions in Econometrics. Journal of
Econometrics, 2, 111-120.
Granger, C.W.J.(1969).Investigating Causal Relation by Econnometric Model and Cross-
Spectral Method. Econometric, 36, 424-438.
Johansen, S., & Juselius, K. (1990).Maximum Likelihood Estimation and Inference on
Cointegration-With Application to the Demand for Money. Oxford Bullentin of
Economics and Statistics, 52, 169-210.
Johansen, S., & Juselius, K. (1990). Maximum Likelihood Estimation and Inference on Cointegration-With Application to the Demand for Money. Oxford Bullentin of Economics and Statistics, 52, 169-210.
Kwiatkowski, D. P., Schmidt, P., & Shin, Y. (1992).Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics, 54, 159-178.
Kavussanos, M.G., & Visvikis, I.D. (2004).Market interactions in returns and volatilities between spot and forward shipping freight markets. Journal of Banking & Finance, 28, 2015–2049.
Kavussanos, M.G., & Nomikos, N.K. (2003).Price discovery, causality and forecasting in the freight futures market. Review of Derivatives Research,6, 203–230.
Kavussanos, M.G., & Alizadeh, A.H. (2001). Seasonality pattern in dry bulk shipping spot and time charter freight rates. Transportation Research, 37,443- 467.
Kavussanos, M.G., & Aisvikis, I.D. (2006), Shipping freight derivatives: a survey of recent evidence. Maritime Policy & Management, 33(3), 233–255.
Mookerjee, T.K., & Naka, A.(1995). Dynamic relations between macroeconomic variables and the Japanese stock market: An application of a vector error correction model. Financial Research, 18(2), 223-237.
Phillips, P.C.B., & Perron, P.(1988). Testing for a Unit Root in Time Series Regression, Biometrika , 75, 335-346.
Koekebakker, S., Adland, R., & Sodal S. (2006). Are spot freight rates stationary. Journal of Transport Economics and Policy, 40(3), 449–472.
Veenstra A .W., & Franses, P. H. (1997). A co-integration approach to forecasting freight rates in the dry bulk shipping sector. Transportation Research ,31, 447-458
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