Factor Models and Covariance Matrices

Wei Lan and Chih-Ling Tsai
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Wei Lan: Southwestern University of Finance and Economics, School of Statistics and Data Science and Center of Statistical Research
Chih-Ling Tsai: University of California - Davis, Graduate School of Management

Chapter Chapter 8 in Covariance Analysis and Beyond, 2026, pp 121-137 from Springer

Abstract: Abstract Factor modelsFactor models involve a reduction of parameters in the covariance matrix, and they are highly related to principal componentsPrincipal components. Since these models have played a very important role in data analysis, we not only introduce classical factor modelsFactor models but also include four extended factor modelsFactor models, namely approximate factor modelsApproximate factor (AF) model, factor-augmented regression modelsFactor-augmented regression (FAR) model, dynamic factor modelsDynamic factor model (DFM), and matrix factor modelsMatrix factor models. In addition, three examples are presented to briefly illustrate empirical applications.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-032-08796-6_8

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DOI: 10.1007/978-3-032-08796-6_8

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