摘要
粮食期货与现货价格的相关性问题一直是学术界研究的热点。基于市场整合视角,运用多种实证分析方法,研究了中国玉米期货市场与不同地区现货市场间相关性的差异。实证研究表明:粮食现货市场较低的地域整合度,是导致以往该方面研究得出不一致结论的主要原因,玉米的现货市场整合度较低;对于饲料和工业用途的粮食品种,其加工聚集区的现货价格与期货价格具有更强的相关性;对于口粮用途为主的粮食品种,其主产区的粮食现货价格与期货价格相关性更强。完善粮食流通体制的建设,并以此为基础提高粮食现货市场的区域整合度,是发挥粮食期货市场价格引导与调节功能的重要保障。
The correlation between grain futures and spot prices has always been the focus of academic research,but the results vary widely.Based on the perspective of market integration and using multiple models,this study first researched the relationship between the futures markets of corn varieties and the spot markets of different regions in our country.The study indicated that:1)The low degree of regional integration of grain spot market is the main reason for the inconsistency of previous studies in this field.Neither rice nor corn has a high degree of market integration.2)In terms of those grain varieties which are mostly for feed and industrial use,those areas which are dense with grain processing enterprises shared a stronger co-integration relationship with the prices of grain futures in China.3)In terms of those which are mostly used as food,major grain-producing areas'spot prices presented a stronger co-integration relationship with the prices of grain futures in China.Therefore,improving the construction of grain circulation system and the regional integration of grain spot market is an important guarantee to give full play to the guiding and regulating function of grain futures market.
作者
钱煜昊
武舜臣
侯立军
QIAN Yuhao;WU Shunchen;HOU Lijun(Institute of Food Economics,Nanjing University of Finance&Economics,Nanjing 210003,Chian;Tsinghua University,China Institute for Rural Studies,Beijing 100084,Chian;School of Business Administration,Nanjing University of finance&Econorruis,Nanjing 210023,China)
出处
《山西农业大学学报(社会科学版)》
2020年第2期45-53,共9页
Journal of Shanxi Agricultural University:Social Science Edition
基金
国家自然科学基金项目(71871110)
2017年国家教育部规划基金项目(17YJAZH031)
中国科协高端科技创新智库青年项目(DXB-ZKQN-2016-22)。
关键词
粮食期货市场
市场整合
协整关系
溢出效应
Grain futures market
Market integration
Co-integration
Volatility spillover