摘要
目前,我国国债期货市场正处于起步阶段,国债期货市场的价格发现、风险规避和套期保值等功能是否充分发挥其作用尚不明确,因此有必要对此进行研究。国债期货的再次推出,不仅是对我国金融市场的完善,更是为现货市场的发展保驾护航。为探究国债期货与现货价格之间的动态关系,选取国债期货交易真实数据并构建VAR模型和ECM模型进行研究,发现我国国债期货市场与现货市场价格都较多依赖旧的自身信息,而对同期的新信息反应比较弱,两种价格之间联系并不紧密,各自对对方信息变化反应强烈程度与反应缓慢程度不同,期货价格对现货价格的影响缓慢表现出来且影响较小。因此从长期来看,扩大国债规模、增加国债现货交易和加强期货交易制度的建设,才能使国债期货与现货市场紧密联系,互相引导。
The market of national debt futures in China is now in its infancy stage, it is not clear whether the functions of price discovery, risk aversion and hedging of market of national debt futures can fully play their roles, which need to be studied. The re-launch of national debt futures is not only the perfection of financial market in China, but also the escort of the spot market. In order to explore the dynamic relationship between the futures price and spot price of national debt, the data of futures transaction of national debt are selected; the models of VAR and ECM are constructed. It is found through the study that the futures price and spot price of national debt in China rely mostly on their respective past information, while the responses of the prices to the current new information are relatively weak. The link between the two prices is not close, and there are differences between the intensity degrees and tardiness degrees of responses of one price to the information change of the other price. The influence of futures price on spot price presents slowly and weakly. Therefore, in the long run, the scale of national debt should be expanded, the spot transactions of national debt should be increased, and the institutional construction of futures transaction should be strengthened, so as to connect the futures market and the spot market of national debt, and guide each other.
出处
《沈阳工业大学学报(社会科学版)》
2015年第6期524-529,共6页
Journal of Shenyang University of Technology(Social Sciences)
基金
教育部人文社会科学研究项目(11YJC790180)
安徽财经大学研究生科研创新基金项目(CXJJ2014048)
关键词
国债期货
国债现货
动态关系
传导机制
向量自回归模型
误差修正模型
futures of national debt
spot of national debt
dynamic relation
conduction mechanism
vector auto regression model (VAR)
error correction model (ECM)