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Semiparametric test for multiple change-points based on empirical likelihood

Author

Listed:
  • Shuxia Zhang
  • Gejun Bao
  • Boping Tian
  • Yijun Li

Abstract

In the dynamic financial market, the change of financial asset prices is always described as a certain random events which result in abrupt changes. The random time when the event occurs is called a change point. As the event happens, in order to mitigate property damage the government should increase the macro-control ability. As a result, we need to find a valid statistical model for change point problem to solve it effectively. This paper proposes a semiparametric model for detecting the change points. According to the research of empirical studies and hypothesis testing we acquire the maximum likelihood estimators of change points. We use the loglikelihood ratio to test the multiple change points. We obtain some asymptotic results. The estimated change point is more efficient than the non parametric one through simulation experiments. Real data application illustrates the usage of the model.

Suggested Citation

  • Shuxia Zhang & Gejun Bao & Boping Tian & Yijun Li, 2017. "Semiparametric test for multiple change-points based on empirical likelihood," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(7), pages 3574-3585, April.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:7:p:3574-3585
    DOI: 10.1080/03610926.2015.1066815
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