北京师范大学学报（自然科学版）Issue(4)：348-353,6.DOI:10.16360/j.cnki.jbnuns.2015.04.004
IF1407合约的长记忆回归模型与投资策略研究∗
A long memory regression model of IF1407 contract and investment strategy
摘要
Abstract
The time duration for price changes of financial asset is the focus of attention of trades in high frequency data analysis.In the past,people generally use the ARFIMA (p ,d ,q)model or the ACD model to study time duration.When high frequency data of stock index futures are analyzed,the time duration is found to be related not only to its lag terms,but also to the number of trades in the period with no price change,and to the size of the price change in Renminbi yuan.The ARFIMA (0,d ,0 )and the regression models are combined as a new model that allows the study of the linear relationship between time duration,which has a long memory,and other factors.This model is used to study the relationships among three parameters:(1 ) time duration between two price changes in high frequency trading,(2)number of trades during period of no price change,and (3)value of price change.Simulation results show that it is appropriate to use the profile least-squares method to estimate parameters in the new model.We used high frequency trading data of Shanghai and Shenzhen 300 stock index futures to illustrate application value of the new model.关键词
高频数据/长记忆/回归模型Key words
high frequency data/long memory/regression model分类
数理科学引用本文复制引用
曹志强,李慧,童行伟..IF1407合约的长记忆回归模型与投资策略研究∗[J].北京师范大学学报（自然科学版）,2015,(4):348-353,6.基金项目
国家自然科学青年基金资助项目(11201031) （11201031）
