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<p>The basis for factor models is the principal component analysis (PCA) which is probably the most often used method in multivariate applications. In this article, we review the PCA, the factor models and their variants as applied to financial data. The uniqueness of financial applications is that we need to consider the constraints on the models resulting from finance theory as well. Recent extensions of PCA include models with time-varying factor loadings, applications in the context of time series data and models for tensor data. We illustrate the various applications with monthly data on 101 assets, 36 asset characteristics and 5 widely used Fama-French market wide variables.</p>

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On Variants of Factor Models With Applications in Finance

  • 期刊论文

  • 发表日期：

    2025年8月26日

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  • Raja Velu,
  • Zhaoque Chosen Zhou

摘要

The basis for factor models is the principal component analysis (PCA) which is probably the most often used method in multivariate applications. In this article, we review the PCA, the factor models and their variants as applied to financial data. The uniqueness of financial applications is that we need to consider the constraints on the models resulting from finance theory as well. Recent extensions of PCA include models with time-varying factor loadings, applications in the context of time series data and models for tensor data. We illustrate the various applications with monthly data on 101 assets, 36 asset characteristics and 5 widely used Fama-French market wide variables.