Latent Factor Analysis in Short Panels - new publication by Olivier Scaillet
In a new study, Olivier Scaillet and his co-authors develop a pseudo maximum likelihood setting for latent factor analysis in short panels without imposing sphericity nor Gaussianity.
They derive an asymptotically uniformly most powerful invariant test for the number of factors. On a large panel of monthly U.S. stock returns, they separate month after month systematic and idiosyncratic risks in short subperiods of bear vs. bull market. They 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.
The paper has been accepted for publication in the Journal of Econometrics, and is co-authored with Alain-Philippe Fortin and Patrick Gagliardini.
Apr 20, 2026