Determination of the Number of Breaks in High-Dimensional Factor Models via Cross-Validation

Abstract

Abstract This paper proposes a cross-validation method to estimate the number of breaks in high-dimensional factor models. To preserve the original change structure, the parity-splitting strategy is adopted when employing the cross-validation method. The consistency of the estimator is established under some mild conditions. Simulation results show desired finite sample performance of the proposed method, especially in comparison with methods that need to predetermine the tuning parameters.