主讲人: 向镜洁 博士研究生
题 目: Estimating the Number of Factors in High Dimensional Constrained Factor Models
时 间: 2018年11月20日（周二）晚上19:30
地 点: 经济学院105
摘要：Constrained factor model proposed in a seminal work by Tsai and Tsay (2010) is an effective way to incorporate prior knowledge into applications of factor models, thus potentially can be widely used in practice. Correctly determining the number of factors is a fundamental issue for the application of factor models. In this paper we tend to investigate the estimation of the number of factors in constrained factor models where the two dimensions, cross-section size (N) and time period (T) increase. Using similar information criteria as proposed by Bai and Ng (2002), we show that the number of factors can be consistently estimated using the criteria. We also propose a two-step method to estimate the numbers of factors in partially constrained factor models. We conduct Monte-Carlo simulation to investigate the finite sample properties of the proposed approach.