| 远期运费协议与粮食期货市场的波动溢出关系 |
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| 引用本文： | 温馨,丁一,林国龙.远期运费协议与粮食期货市场的波动溢出关系[J].上海大学学报(自然科学版),2015,21(6):774-783. |
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| 作者姓名： | 温馨 丁一 林国龙 |
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| 作者单位： | 上海海事大学物流研究中心, 上海201306 |
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| 基金项目： | 国家高技术研究发展计划(863 计划)资助项目(2013A2041106); 国家自然科学基金资助项目(71101088,71301101); 教育部博士点基金资助项目(20113121120002) |
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| 摘 要： | 从金融视角出发, 探究远期运费协议和粮食期货市场之间的波动溢出关系. 粮食作为世界三大干散货类型之一, 具备相当成熟的期货交易市场, 故选取远期运费协议(forwardfreight agreement, FFA)和巴拿马(Panamax)型船主要运载的粮食期货类型进行研究. 首先,采取统计特征分析及协整检验对日收益序列进行分析; 然后, 通过建立广义自回归条件异方差(generalized autoregressive conditional heteroskedasticity, GARCH)模型, 分析两个市场间的相关性并对比其波动性. 结果表明, 粮食期货市场在收益和波动性上均引导FFA 市场的变化, 论证了GARCH 族模型检验波动溢出特征的有效性, 并为干散货航运市场参与者和投资者提供理论参考.
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| 关 键 词： | 波动溢出性 粮食期货 远期运费协议 自回归条件异方差模型 |
| 收稿时间： | 2014-08-09 |
Volatility spillover effect between forward freight agreement and grain futures market |
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| WEN Xin,DING Yi,LIN Guo-Long.Volatility spillover effect between forward freight agreement and grain futures market[J].Journal of Shanghai University(Natural Science),2015,21(6):774-783. |
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| Authors: | WEN Xin DING Yi LIN Guo-Long |
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| Affiliation: | Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China |
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| Abstract: | From the financial point of view, this paper investigates volatility spillovers between forward freight agreement (FFA) and grain futures market. As one of the three major dry bulk cargoes in the world, grain has a mature futures market. FFA and main grain futures transported by Panamax are studied. First, statistical characteristics and co-integration relation of daily return series are analyzed and inspected. A generalized autoregressive conditional heteroskedasticity (GARCH) model is then constructed to analyze correlation and volatility spillover. The results indicate that the grain futures market leads to the changes of FFA market with respect to return and volatility. Thus, this paper demonstrates effectiveness of GARCH-class model to test volatility spillover, providing a theoretical basis for shipping operators. |
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| Keywords: | forward freight agreement (FFA) generalized autoregressive conditional heteroskedasticity (GARCH) model grain futures volatility spillover |
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