題 目: Doubly Constrained Factor Models: Estimation and Applications 主講人: 蔡恆修 博士 (中研院統計所) 時 間: 100年3月18日（星期五）上午 10:40 - 11：30 （上午10：20- 10：40茶會於統計所821室舉行） 地 點: 清大綜合三館837室 Abstract Factor models have been widely used in recent years to improve the accuracy of forecasting when many explanatory variables are available. However, the models often encounter the difficulties of over-parameterization and factor interpretation. In this paper, we first consider constrained factor analysis to obtain a parsimonious factor model and propose likelihood ratio statistics to test the adequacy of factor constraints. Real and simulated examples are used to demonstrate the proposed analysis. In an application, we show that the constrained factor analysis can provide a deeper understanding of variations in monthly financial asset returns. We then extend the constrained models to the doubly constrained factor models by incorporating external information on both rows (e.g., subjects) and columns (e.g., variables) of a data matrix. Maximum likelihood estimates and likelihood ratio statistics of the proposed models are derived. Finally, we consider the applications of doubly constrained factor models in economics and finance. (This is a joint work with Ruey Tsay of the University of Chicago). --

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