簡易檢索 / 詳目顯示

研究生: 鍾孟桓
Chung, Meng-Huan
論文名稱: 國際油輪運費市場資訊不對稱性與槓桿效果分析
An Analysis with News Shocks on Asymmetries and Leverage Effects of International Tanker Freight Market
指導教授: 張瀞之
Chang, Ching-Chin
學位類別: 碩士
Master
系所名稱: 管理學院 - 交通管理科學系
Department of Transportation and Communication Management Science
論文出版年: 2009
畢業學年度: 97
語文別: 中文
論文頁數: 66
中文關鍵詞: 油輪運費市場槓桿效果ARMA-EGARCH模式訊息衝擊曲線
外文關鍵詞: Tanker Freight Market, Leverage Effect, News Impact Curve, ARMA-EGARCH
相關次數: 點閱:88下載:2
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 本研究針對油輪運費市場是否為不對稱市場進行實證分析,探討三種典型的油輪:超級油輪 (VLCC)、蘇伊士極限型油輪 (Suezmax)、阿芙拉極限型油輪 (Aframax) 之運費市場在正負面資訊衝擊下,是否存在著不對稱反應與槓桿效果,並以ARMR-EGARCH模式及訊息衝擊曲線對三種船型之一年期論時傭船租金資料進行分析。研究結果顯示:由三種船型所估計出之模式及訊息衝擊曲線可得知,三種船型中只有Aframax之運費具有不對稱性與槓桿效果,當負面訊息越大時,其條件變異數也越大。而VLCC、Suezmax兩種船型資料所估計出來的模式顯示其不對稱現象與槓桿效果皆不顯著。建議油輪市場之投資者,可以從資訊面以外的角度來尋找影響運費市場較為顯著的潛在風險因子,以更精確地預測、解釋運費市場的波動。若從反應資訊面衝擊的數據來作分析,其預測與避險效果有限。

    This research aims to explore whether the asymmetric volatilities and leverage effects under the news shocks exist in VLCC tanker freight market, Suezmax tanker freight market, and Aframax tanker freight market. This research used ARMA-EGARCH model and news impact curve to analyze the three tanker markets. The result showed that the asymmetric volatility and leverage effects under the news shocks existed in Aframax tanker freight market. In Aframax tanker freight market, when the negative news shocks happened, the conditional variances became larger. Besides, the leverage effects under the news shocks do not happen in VLCC and Suezmax tanker freight markets. The influence of news shocks in tanker freight markets is not significant. The news shocks are not a direct factor to influence freight on the tankers’ market. This paper suggests the tankers’ owners do not consider news shock as their main factors under forecasting and hedging.

    第一章 緒論 1 第一節 研究背景 1 第二節 研究動機 2 第三節 研究目的 3 第四節 研究範圍與流程 3 第五節 論文架構 4 第二章 文獻回顧 6 第一節 油輪產業概述 6 第二節 油輪產業取價 10 第三節 資訊不對稱性與槓桿效果分析之市場相關研究 11 第四節 時間序列分析方法論 19 第三章 研究方法 21 第一節 ARMR-EGARCH模式 21 第二節 訊息衝擊曲線模式(News Impact Curve Model) 28 第四章 實證分析 30 第一節 研究假說 30 第二節 研究設計 30 第三節 實證研究 33 第四節 實證結果 61 第五章 結論與建議 62 第一節 結論 62 第二節 研究限制與建議 63 參考文獻 64

    一、中文文獻

    1. 王志敏(2006),國際散裝海運市場租金費率與船價波動關係之研究,高雄海洋科技大學航運管理所碩士論文。
    2. 林光(2003),海運學,第五版,台北:華泰書局。
    3. 林光、張志清(2006),航業經營與管理,第五版,台北:航貿書局。
    4. 林震岩(2006),多變量分析SPSS的操作與應用,初版,台北:智勝書局。
    5. 陳永順(2005),散裝海運經營學理論與實務,初版,台北:文笙書局。
    6. 溫祐D(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。
    7. 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。
    8. 楊曉麗(2004),合併換股比率之模擬研究,中山大學經濟學研究所碩士論文。

    二、英文文獻

    1. Akaike, H. (1973). Information Theory and an Extension of the Maximum Likelihood Principle. Second International Symposium on Information Theory, 267-281.
    2. Black, F. (1976). Studies in stock price volatility changes. Proceedings of the 1976 Business Meeting of the Business and Economic Statistics Section. American StatisticalAssociation, 177-181.
    3. Blenman, L. P., Chatterjee, A., & Ayadi, O. F. (2005). Volatility persistence, market anomalies and risk in Latin American equity markets. The International Journal of Finance, 17(2), 3413-3445.
    4. Bollerslev, T.(1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31, 307-327.
    5. Bollerslev, T. (1987). A Conditional Heteroskedastic Time Series Model for Speculative Price and Rates of Return. Reviews of Economics and Statistics, 69, 542-547.
    6. Bollerslev, T., Chou, R., & Kroner, K. (1992). ARCH Modeling in Finance: A Review of the Theory and Empirical Evidence. Journal of Econometrics, 52, 5-59.
    7. Box, G. E. P., & Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control, Holden-Day, San Francisco, Calif.
    8. Chen, C. W. S., Chiang, T. C., & So, M. K. P. (2003). Asymmetrical reaction to US stock-return news: Evidence from major stock markets based on a double-threshold model. Journal of Economics and Business, 55, 487-502.
    9. Chen, C. W. S., & Yu, T. H. K. (2005). Long-term dependence with asymmetric conditional heteroscedasticity in stock returns. Physica A: Statistical Mechanics and its Applications, 353, 413-424.
    10. Christie, A. (1982).The Stochastic Behavior of Common Stock Variance: Value, Leverage and interest Rate Effects. Journal of Financial Economics, 10,407-432.
    11. Engle, R.F. (1982). Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50, 987-1007.
    12. Engle, R. F., & Ng, V. K. (1993). Measuring and Testing the Impact of News on Volatility. Journal of Finance, 48, 1749-1778.
    13. Fornari, F., & Mele, A. (1997). Sign and volatility-switching ARCH models: Theory and applications to international stock markets. Journal of Applied Econometrics, 12(1), 49-65.
    14. Kassimatis, K. (2002). Financial liberalization and stock market volatility in selected developing countries. Applied Financial Economics, 12(6), 389-394.
    15. Kavussanos, M.G. (1996a).Comparisions of Freight Market Volatility in the Dry-Cargo Ship Sector. Spot v.s. Time-Charter and Smaller v.s.Larger Vessels, Journal of Transport Economics and Policy, XXX1, 67-82.
    16. Koutmos, G. (1998). Asymmetries in the conditional mean and the conditional variance: Evidence from nine stock markets. Journal of Econometrics and Business, 50, 277-290.
    17. Leeves, G.. (2007). Asymmetric volatility of stock returns during the Asian crisis: Evidence from Indonesia. International Review of Economics & Finance, 16(2), 272-286.
    18. Mohanty, P. (2006). A study of asymmetric volatility in the Indian equity market: A GARCH approach. Decision, 33(1), 121-134.
    19. Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59, 347-370.
    20. Pati, P. C. (2006). Maturity and volume effects on the volatility: Evidences from NSE fifty futures. 10th Capital Markets Conference, Indian Institute of Capital Markets Paper.
    21. Schwarz, G. (1978). Estimating the Dimension of a Model. The Annals of Statistics, 6, 461-464.
    22. Tvedt, J. (2003).A new perspective on price dynamics of the dry bulk market. Maritime Policy and Management, 30 (3), 221-230.
    23. Wu, G., & Xiao, Z. (2002). A generalized partially linear model of asymmetric volatility. Journal of Empirical Finance, 9(3), 287-319.

    下載圖示 校內:2010-11-17公開
    校外:2010-11-17公開
    QR CODE