Page's sequential procedure for change-point detection in time series regression
Page's sequential procedure for change-point detection in time series regression
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DOI：
10.1080/02331888.2013.870568
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发表时间：
2015-01-02
期刊：
影响因子：
1.9
通讯作者：
Fremdt, Stefan
中科院分区：
文献类型：
--
作者：
Fremdt, Stefan
在各种不同的设置中，累积和 (CUSUM) 程序已应用于随机模型参数中结构断裂的顺序检测。然而，它们的性能在很大程度上取决于变革的时间，并且在早期变革场景下效果最佳。对于后来的变化，他们的有限样本行为是相当值得怀疑的。因此，我们提出改进的 CUSUM 程序，用于检测多个时间序列回归模型的回归参数的突然变化，与普通 CUSUM 程序相比，该程序在变化时间方面表现出更高的稳定性。提供了检验统计量的渐近分布和程序的一致性。模拟研究表明，所提出的程序在有限样本中表现良好。最后，该程序应用于与 CAPM 的 Fama-French 扩展相关的一组资本资产定价数据。
In a variety of different settings cumulative sum (CUSUM) procedures have been applied for the sequential detection of structural breaks in the parameters of stochastic models. Yet their performance depends strongly on the time of change and is best under early change scenarios. For later changes their finite sample behavior is rather questionable. We therefore propose modified CUSUM procedures for the detection of abrupt changes in the regression parameter of multiple time series regression models, that show a higher stability with respect to the time of change than ordinary CUSUM procedures. The asymptotic distributions of the test statistics and the consistency of the procedures are provided. In a simulation study it is shown that the proposed procedures behave well in finite samples. Finally the procedures are applied to a set of capital asset pricing data related to the Fama-French extension of the CAPM.