Change-point problem in panel data is an important topic in finance and econometric. A multiple change-point estimation procedure based on the shape-based BS algorithm is extended to panel data, multiple change-point estimation in the mean and variance of panel data model is studied. The number and location of the change-points are also obtained, and the consistency of the change point estimators is proved. Monte Carlo simulation shows that the shape-based BS algorithm outperforms the BS algorithm in estimating both types of change points. Finally, this method is applied to different weekly index data of the stock market, which shows the effectiveness of the algorithm.