Testing multi-factor asset pricing models is instrumental for the asset pricing theory and practice. Due to the accumulation of errors in estimating high-dimensional parameters, traditional quadratic-form tests such as the Wald test perform poorly against the sparse alternative hypothesis in the...

The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the...

We develop new structural nonparametric methods for estimating conditional asset pricing models using deep neural networks. Our method is guided by economic theory and employs time-varying conditional information on alphas and betas carried by firm-specific characteristics. Contrary to many...