基于证券价格时间序列的协整优化指数跟踪方法研究

Research on the Cointegration Optimization Index Tracking Approach based on the Time Series of Securities Prices

通过考虑不允许卖空约束和目标指数进行调整的现实情况,研究了基于证券价格时间序列的协整优化指数跟踪方法对目标指数进行直接跟踪的效果以及用简单平均法引入的非样本信息在指数跟踪中的作用.实证结果表明,相比于最小化跟踪误差优化指数跟踪方法,协整优化指数跟踪方法是一种非常好的指数跟踪方法,更多的信息可以进一步改进指数跟踪效果.

By considering the constraints of no short selling and the realistic condition of the adjustment of target index, the directly tracking performance of the cointegration optimization index tracking approach based on the time series of securities prices for the targeting index is researched in this paper. Meanwhile, by introducing into the nonsampling information with simple average method, the usage of the non-sampling information in index tracking is researched too. The empirical results show that, comparing to the index tracking approach of minimizing tracking error, the cointegration optimization index tracking approach is one good approach for index tracking; furthermore, the performance of index tracking can be improved with more information.