Semiparametric method for identifying multiple change-points in financial market

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.

Keywords:

• Empirical likelihood
• Limit theory
• Multiple change-points model
• Semiparametric

Additional information

Funding

The authors declare no conflicts of interest. This research was supported by the project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions. This research is partly financed by NSFC grant [91646106].