Estimation of high dimensional factor model with multiple threshold-type regime shifts

This paper considers the estimation of high dimensional factor model with multiple threshold-type regime shifts in factor loadings. Firstly, the number of thresholds is determined by comparing the number of factors in the adjacent subintervals. Secondly, the thresholds are estimated one by one by concentrated least squares, and then the factors and loadings are obtained by the principal component method in the augmented subgroups with a single threshold. Under some regularity conditions, the consistency of these estimators can be obtained. Monte Carlo simulation results demonstrate that the proposed method has desirable performance in finite samples. A real data analysis is carried out for illustration. (C) 2020 Elsevier B.V. All rights reserved.

Automated summary

This paper introduces a new method for estimating high-dimensional factor models, where the number of thresholds is determined by comparing the number of factors in adjacent subintervals. The thresholds are then estimated one by one to obtain factors and loadings, and the performance of the method is demonstrated in finite samples.