摘要
利用沪深300股指期货连续合约的高频数据,采用参数估计的方法运用R软件对数据进行处理,消除其日模式并建立ACD模型.还加入了市场微结构噪声,探讨交易量持续期的信息传递机制.实证分析表明,在选取样本中,价格波动和交易量与股指期货市场流动性显著正相关,交易量持续期与股指期货市场流动性显著负相关,信息交易增加导致流动性降低,进而为投资者进行决策提供一定的参考.
In this paper,we study the parameter estimation method in eliminating the intraday pattern and establishing the ACD model of the high-frequency data in CSI 300 stock index futures contracts.To detect the information transmission mechanism of trading duration,we also put the market microstructure noise in the model.The empirical analysis presents that the price volatility and trading volume have a significantly positive correlation with the market liquidity of stock index futures,and there exists a significantly negative correlation between the trading duration and the market liquidity of stock index futures.The increase in the information exchange in the information transaction is a reference for the investors to make a decision.
出处
《数学的实践与认识》
北大核心
2016年第9期54-60,共7页
Mathematics in Practice and Theory
基金
国家自然科学基金(11501015)
关键词
高频数据
股指期货
流动性
日模式
自回归条件持续期模型
high-frequency data
stock index futures
liquidity
intradny pattern
autoregressive conditional duration model
