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Latent factor analysis in short panels
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DOI：10.1016/j.jeconom.2026.106249.png)
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Abstract
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We develop a pseudo maximum likelihood method for latent factor analysis in short panels without imposing sphericity nor Gaussianity. We derive an asymptotically uniformly most powerful invariant test for the number of factors. On a large panel of monthly U.S. stock returns, we separate month after month systematic and idiosyncratic risks in short subperiods of bear vs. bull markets. We observe an uptrend in the paths of total and idiosyncratic volatilities. The systematic risk explains a large part of the cross-sectional total variance in bear markets but is not driven by a single factor and not spanned by observed factors.
Keywords:
Latent factor analysis
Uniformly most powerful invariant test
Panel data
Large n and fixed T asymptotics
Equity returns
C12
C23
C38
C58
G12
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