The Dynamic, the Static, and the Weak: Factor Models and the Analysis of High‐Dimensional Time Series
本文回顾并讨论了因子模型中的几个基本问题，包括动态与静态载荷、强弱因子、弱共同成分等，结论支持广义动态因子模型优于静态近似因子模型。
ABSTRACT Several fundamental and closely interconnected issues related to factor models are reviewed and discussed: dynamic versus static loadings, rate‐strong versus rate‐weak factors, the concept of weakly common component recently introduced by Gersing, the irrelevance of cross‐sectional ordering and the assumption of cross‐sectional exchangeability, the impact of undetected strong factors, and the problem of combining common and idiosyncratic forecasts. Conclusions all point to the advantages of the General Dynamic Factor Model approach of Forni, Hallin, Lippi, and Reichlin over the widely used Static Approximate Factor Model introduced by Chamberlain and Rothschild.