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1、硕士学位论文1硕 士 学 位 论 文中美豆粕期货市场风险溢出效应分析2014 年 12 月硕士学位论文2MASTER DISSERTATIONAnalysis of soybean futures market risk spillover effect between China and USDecember 2014硕士学位论文3摘要在全球化市场大氛围下，不同国家金融市场间的联动性越来越强，随着国内期货市场的逐步规范，我国农产品期货市场日益成熟，大连商品交易所（DCE）的豆粕市场也成为国内饲料加工企业和油脂企业重要的套期保值工具。最近几年，我国大豆每年产量维持1600万吨上下，消费量有50
2、00多万吨，进口达到4000万吨，对外依赖度达到80%。我国进口大豆都是转基因大豆，全部用来压榨豆油和豆粕，国产大豆只有一半用来压榨，从我国大豆压榨原料来说，进口大豆占非常大的比例，接近90%。给研究大连商品交易所与芝加哥商品交易所两市豆粕市场间的风险溢出效应提供了一个契机。（注：以上数据均来自中国饲料行业信息网 2006 年至 2013年八年间 CBOT 和 DCE 两市豆粕期货的风险价值（VaR），分析两市 VaR 值的相关性，然后通过 VAR 值分析两市风险溢出效应。本文的结构安排：第一章为前言，先介绍论文研究的背景与选题意义，然后介绍研究的思路和结构安排，并指出文章所用研究工具以及创新
3、点。第二章系统阐述了国内外有关研究文献。第三章则先简要介绍影响豆粕期货市场的供求因素，其次介绍豆粕期货市场风险度量方法以及数据上的选择处理。第四章则主要对 CBOT 和 DCE 豆粕期货市场的关联度进行检验，首先建立 GARCH 模型检验，计算两市场 VaR 值以及检验风险值之间的相关性。第五章主要通过 Granger 因果关系检验法和脉冲响应分析法进行实证分析两市豆粕期货风险溢出效应。第六章对论文的研究内容做总结，指出论文研究的不足之处和可能的研究方向。论文结合样本期在金融危机前后的不同表现，将研究时期划分成两个子样本区间，研究分析两市豆粕市场间风险溢出效应。从实证果得知：在总样本区间内，C
4、BOT 与 DCE 两市豆粕期货多空头市场互为风险 Granger 原因。在全球性金融危硕士学位论文4机发生前后的两个子样本区间，CBOT 豆粕多空头市场风险则单向是 DCE 豆粕多空头市场风险 Granger 原因。脉冲响应分析显示，各子样本及总样本区间内，两市场面对彼此的风险冲击中，CBOT 豆粕期货市场对于 DCE 豆粕市场大都呈稳定先增后减的正向冲击反应。DCE 豆粕期货市场面对 CBOT 豆粕期货市场风险冲击时短期内出现了短暂的剧烈不稳定溢出效应。而在面对各自自身市场风险冲击中，主要也都呈正向递减冲击反应。本文主要研究创新点表现在：豆粕作为国际性大宗农产品，是国内外饲料业，畜牧业的重
5、要需求品，中国每年进口数量巨大，但是对于中美豆粕市场关系的研究文献相对较少；本文之前的研究大多涵盖了中外农产品市场的研究，并没有深入具体到两个细分市场，同时也未将次贷危机的影响考虑进去；此前，很多文献仅根据价格以及收益率数据来研究市场间的风险关联性，本文则采用两市的 VaR值进行期货市场风险关系研究。关键词：风险溢出；豆粕市场；风险价值（VaR）；Granger 因果关系检验硕士学位论文5ABSTRACTIn the atmosphere of global market, the financial markets linkage between different countries is
6、 much stronger than ever before. with the gradual standardization of domestic futures market, Chinas agricultural product futures market is increasingly achieving mature, Soybean meal market of Dalian Commodity Exchange(DCE) has also become an important hedging tool of the domestic feed processing e
7、nterprises and oil enterprises. In recent years, Chinas annual soybean output is about 16 million tons, but the annual consumption is about 50 million tons per year .China need to import nearly 40 million tons of soybeans, the foreign dependency rate has reached 75%. Chinas soybean imports is geneti
8、cally modified soybean, soybean oil and meal are used to crush, half of domestic soybean is used to squeeze, from our raw material of soybeans squeezing, soybean imports accounted for a big proportion, close to 90%. The upper content provides an opportunity to study the Risk Spillover Effect between
9、 soybean meal market of Dalian Commodity Exchange and Chicago Commodity . (Note: the above data is from China Feed Industry Information Network, Because Chinas soybean futures varieties consist of soy one and soy two, and soy one is domestic soybean whose volume is active, However , it accounts for
10、 less than 30 percent of consumption of Chinas total soybean, thus less enterprises participate in the soy one futures and it is not widespread. In contrast, the annual consumption of soybean meals is up to more than 3000 tons , which is distributed in relatively widespread circulation area, Dalian
11、soybean futures markets turnover is extremely active, the main contract positions remain more than a million hands, belonging to agricultural futures star species. (Note: The above data is from the China Feed Industry Information Network , soybean future market of Dalian commodity Exchange (DCE) and
12、 Chicago Commodity Exchange (CBOT) own the relationship which is stronger, providing an opportunity of research on the Dalian futures with Chicago Commodity Exchange regarding of the risk spillover effect .This paper is based on the above background and the results of previous studies. Firstly, esti
13、mating the confidence level of risk (VaR) in two soybeans three 硕士学位论文6common value with the EGARCH model ,and analizing the correlation between two citys Var and then analyzing two citys risk spillover effect in two VaR value. Therefore, this paper is organized as follows: the first chapter is the
14、introduction part. Firstly introduce the background and significance of the research, and the major research ideas and structure of the thesis are arranged as introduced, The second chapter systematically summarize the search literature at home and abroad. The third chapter briefly introduces the su
15、pply and demand factors of soybean meal futures market, followed by the introduction of soybean futures markets risk measurement method and data on the choice of treatment.In the fourth chapter，firstly inspecting the association of CBOT with the DCE soybean futures market of inspection, mainly taking the GARCH model for the correlation between estimated two city based VaR value
