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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/30836

Title: 乾散貨運價衍生性商品與風險管理
Freight Rate Derivatives and Risk Management in Dry Bulk Shipping
Authors: 周恆志
Contributors: NTOU:Department of Shipping and Transportation Management
國立臺灣海洋大學:航運管理學系
Date: 2011-08
Issue Date: 2012-04-13T01:48:28Z
Publisher: 行政院國家科學委員會
Abstract: 摘要:此四年期計畫的主題為「乾散貨運價衍生性商品與風險管理之研究」,本研究計畫的主 旨在於進一步瞭解運價的風險特性,幫助航運業管理運價風險,提升航運業經營效率。研究 目的有三:(1)建構量化模型衡量乾散貨運價的價格風險,相對於傳統工具,我們擬採用的量 化模型包括價格變幅波動率模型(Range-based Volatility Models)、緩長記憶(Long Memory)模型 與風險值模型(Value at Risk Model);(2)以跨期資本定價模型(Intertemporal Capital Asset Pricing Model)探討運價風險與報酬率的抵換(Trade-off)關係;(3)分析運價衍生性商品的避險 績效,分別探討運價期貨(Freight Rate Futures)、遠期運價合約(Forward Freight Agreements) 與 運價選擇權(Freight Rate Options)的避險績效。希望藉此研究有助於航運業進一步掌握運價風 險的特性,以及相關衍生性商品的避險績效。 綜言之,此四年計畫的研究子題分別為:(1)乾散貨的運價風險:變幅波動率模型與風險 值模型之應用,(2)乾散貨運價風險與報酬的關係:跨期資本定價模型之應用,(3)乾散貨運價 期貨與遠期合約的避險績效:變幅動態條件相關模型之應用,及(4)乾散貨運價選擇權的評價 與避險績效:Koekebakker et al. (2007)運價選擇權評價模型之應用。 運價風險管理的績效決定於避險者對運價風險的精確掌握,不同於傳統文獻的做法,本 計畫則擬採用運價的價格變幅衡量運價風險,配適條件變幅自我相關模型(Conditional Auto-relation Range Model) 以及隨機變幅波動性模型(Range-based Stochastic Volatility Model)。除了波動率的短期特性外,我們也檢定運價波動的緩長記憶性(Long Memory),建構 運價的FIGARCH (Fractional Integrated GARCH)模型,有助於同時掌握運價波動的短期與長 期特性。此外,風險值技術在金融業行之有年,但是在運價風險的應用尚屬起步階段,我們 也考量運價的波動特性,擬以極端值理論(Extreme Value Theory)建構運價的風險值模型,希 望能有助於管理運價風險。在運價波動率與風險值模型的基礎上,本計畫接著以跨期資本資 產定價模型檢驗運價風險與報酬之關係。並以2008 年金融風暴為界,比較風暴前後的差異。 在分析運價衍生商品避險績效方面,我們納入相關係數的動態行程,擬用變幅動態條件相關 (Range-based Dynamic Conditional Correlation)模型估計運價期貨與遠期運價合約的避險比 率,冀能提升避險績效。最後本計畫將以運價選擇權市價配適Koekebakker et al. (2007)運價 選擇權評價模型,以檢驗該模型的評價績效,並評估運價選擇權的避險績效。本研究計畫的 成果不僅有助於提升航運業的風險管理績效,也可彌補學術文獻在此一領域的缺乏。
Abstract:The topic of this four-year study is “Freight Rate Derivatives and Risk Management in Dry Bulk Shipping Industry”, and the purpose of the study is to understand the characteristics of freight, to help the industry manage freight risk, and ultimately to increase the operation efficiency. In the study, we plan (1) to construct some innovative quantitative models, such as range-base volatility models, long memory models and value-at-risk (VaR) models, for the measuring of freight risk, (2) to explore the trade-off relation between the return and risk of freight rate, and (3) to analyze the hedge performance of fright derivatives including futures and options. We believe that the results of the study will help us grasp the characteristics of freight risk, and manage the risk successfully as well. This four-year study includes the following four parts: (1) the freight risk in the dry bulk shipping: the application of range-based volatility models and value-at-risk models, (2) the relation between return and risk of freight rate: the application of the intertemporal capital asset pricing model (ICAPM), (3) the hedge performance of freight futures: the application of range-based DCC models, and (4) the valuation and hedge performance of freight options: the application of Koekebakker et al.(2007) model. Literature review concludes that the superiority of risk management is mainly decided by the accurate estimation of the price volatility of the asset. Different from traditional tools, the study will adopt the price range of freight to measure its risk. Besides of examining the freight rate’s short term characteristics, we also test the significance of its long memory. On the other hand, the VaR model which is widely used in the financial world will also be applied to the measurement of freight risk. After measuring the freight risk, we will apply the ICAPM to explore the trade-off relation between the risk and return of the freight rate. In this part, we will examine the impacts of the 2008 financial crisis on the trade-off relation. In order to test the hedge performance of freight futures, the range-based DCC model will be used in consider the dynamics of correlation between spot and forward freight. Finally, the study examines the pricing and hedge performance of Koekebakker et al. (2007) option pricing model. The results of the study will not only provide some valuable knowledge regarding the dynamics of freight risk, but also make up for the shortage of literature in this area.
Relation: NSC100-2628-H019-001
URI: http://ntour.ntou.edu.tw/handle/987654321/30836
Appears in Collections:[航運管理學系] 研究計畫

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