英文文献：Forecasting long memory time series under a break in persistence-长记忆时间序列的持续性间断预测
英文文献作者：Florian Heinen,Philipp Sibbertsen,Robinson Kruse
英文文献摘要：
We consider the problem of forecasting time series with long memory when the memory parameter is subject to a structural break. By means of a large-scale Monte Carlo study we show that ignoring such a change in persistence leads to substantially reduced forecasting precision. The strength of this effect depends on whether the memory parameter is increasing or decreasing over time. A comparison of six forecasting strategies allows us to conclude that pre-testing for a change in persistence is highly recommendable in our setting. In addition we provide an empirical example which underlines the importance of our findings.

研究了记忆参数发生结构突变时，长记忆时间序列的预测问题。通过大规模蒙特卡洛研究，我们表明，忽略这种变化的持久性导致大幅度降低预测精度。这种效果的强度取决于记忆参数是随时间增加还是减少。通过对六种预测策略的比较，我们可以得出这样的结论:在我们的环境中，高度推荐对持续性变化进行预测试。此外，我们提供了一个实证例子，以强调我们的发现的重要性。