High Dimensional Factor Models with an Application to Mutual Fund Characteristics

Martin Lettau

No 17091, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: This paper considers extensions of 2-dimensional factor models to higher-dimension data that can be represented as tensors. I describe decompositions of tensors that generalize the standard matrix singular value decomposition and principal component analysis to higher dimensions. I estimate the model using a 3-dimensional data set consisting of 25 characteristics of 1,342 mutual funds observed over 34 quarters. The tensor factor models reduce the data dimensionality by 97% while capturing 93% of the variation of the data. I relate higher-dimensional tensor models to standard 2-dimensional model and show that the components of the model have clear economic interpretations.

Keywords: Tucker decomposition; Cp decomposition; Tensors; Pca; Svd; Factor models; Mutual funds; Characteristics (search for similar items in EconPapers)
JEL-codes: G12 G38 (search for similar items in EconPapers)
Date: 2022-03
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