A Nonparametric Test for Multiple Changes in the Mean of Independent Random Series

A nonparametric procedure is proposed to detect multiple changes in the mean of independent random series and the asymptotic distribution is derived. Simultaneously, the estimators for the locations of the change points are obtained. Moreover, the performance of the test is studied by Monte Carlo simulation, which demonstrates that the proposed test has high powers and good sizes for heavy-tailed innovations. Finally, the feasibility of the proposed test is illustrated by the application on the LBC data of stock prices.