Abstract Multiple change-points problem has been discussed recently on the background of financial market. As a financial crisis or big event happened, the government should increase the macro-control ability in order to mitigate property damage. The above issue can be resolved through finding a more accurate model which fits the peculiar financial asset price, and finding a more efficient test. This paper proposes a method of detecting multiple change-points under a semiparametric model. Using empirical likelihood technique to acquire the maximum likelihood estimation of multiple change-points, and testing the estimation by loglikelihood ratio. Furthermore, we present a sequential approach to find the number of change-points. The simulation experiments prove that the proposed multiple change-points estimation is more efficient than the nonparametric one. The diagnosis with application for multiple change-points also illustrates the proposed model well.

中文翻译：

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识别金融市场多变点的半参数方法

摘要 多变点问题是最近在金融市场背景下讨论的。当发生金融危机或重大事件时，政府应提高宏观调控能力，以减轻财产损失。上述问题可以通过寻找更适合特定金融资产价格的更准确的模型，并寻找更有效的检验来解决。本文提出了一种在半参数模型下检测多个变化点的方法。利用经验似然技术获得多个变化点的最大似然估计，并通过对数似然比检验估计。此外，我们提出了一种顺序方法来查找变化点的数量。仿真实验证明，所提出的多变点估计比非参数估计更有效。应用多个变化点的诊断也很好地说明了所提出的模型。