Estimation and inference in semiparametric quantile factor models

We consider a semiparametric quantile factor panel model that allows observed stock-specific characteristics to affect stock returns in nonlinear time-varying way, extending Connor, Hagmann, and Linton (2012) the restriction case. propose sieve-based estimation methodology is easy implement. provide tools for inference are robust existence of moments form weak cross-sectional dependence idiosyncratic error term. apply our method daily return data where we find significant evidence nonlinearity many characteristic exposure curves.