基于高频数据的股指期货价格发现功能的动态研究  

Dynamic Research on Price Discovery of Stock Index Futures Market Based on High-Frequency Data

作　　者：顾京[1] 叶德磊[1] 

机构地区：[1]华东师范大学商学院,上海200241

出　　处：《河北经贸大学学报》2013年第3期48-53,共6页Journal of Hebei University of Economics and Business

基　　金：上海市哲学社会科学规划资助项目"我国股指期货市场功能的实证研究及政策引申"(2012BJB001)的阶段性研究成果

摘　　要：利用沪深300指数和股指期货主力合约的日内高频数据,创新性地采用递归协整和公共因子模型方法对股指期货价格发现功能的动态变化进行了深入研究,发现在股指期货运行之初,股指期货市场与现货市场并不具有稳定的协整关系,股指期货不具有价格发现功能。随着市场的不断完善,期现货市场之间开始存在稳定的协整关系,股指期货开始具有价格发现功能,但价格发现功能表现并不理想。在价格发现过程中,起主要作用的是现货市场,而并非期货市场。Using high-frequency CSI 300 stock index and main stock index futures contact date in China, and recursive co integration tests and the common factor model, we did a thorough research on time-varying price discovery function performance of CSI 300 stock index futures. We found that there was no stable co integration between futures and spot markets at its infancy stage, stock index futures did not have price discovery function. As the improvement of futures market, there began to have a stable co integration relationship between futures and spot markets. The futures market began to have price discovery function, but it did not function well. In price discovery performance process, we found that the spot market rather futures market played a more dominant role in the price discovery process.

关 键 词：高频数据 股指期货 价格发现 递归协整 公共因子模型 

分 类 号：F830.91[经济管理—金融学]