Robust Estimation of Conditional Factor Models

This paper develops estimation and inference methods for conditional quantile factor models. We first introduce a simple sieve estimation, establish asymptotic properties of the estimators under large $N$. then provide bootstrap procedure estimating distributions estimators. also two consistent number factors. The allow us not only to estimate structures asset returns utilizing characteristics, but conduct robust in models, which enables analyze cross section with heavy tails. apply individual US stock returns.