We propose an estimation methodology for a semiparametric quantile factor panel model. We provide tools for inference that are robust to the existence of moments and to the form of weak cross-sectional dependence in the idiosyncratic error term. We apply our method to CRSP daily data.

We confront prominent asset pricing models with the classical out-of-sample cross-sectional test of Fama and MacBeth (1973). For all models, we uncover three main findings: (i) the intercept coefficients are economically large and highly statistically significant; (ii) the cross-sectional factor...

This paper provides an overview of the recent literature on estimation and inference in large panel data models with cross-sectional dependence. It reviews panel data models with strictly exogenous regressors as well as dynamic models with weakly exogenous regressors. The paper begins with a...

In this paper, we consider statistical inference for high-dimensional approximate factor models. We posit a weak factor structure, in which the factor loading matrix can be sparse and the signal eigenvalues may diverge more slowly than the cross-sectional dimension, N. We propose a novel...