In this paper, we derive a rate of convergence of the Lasso estimator when the penalty parameter Lambda for the estimator is chosen using K-fold cross-validation; in particular, we show that in the model with Gaussian noise and under fairly general assumptions on the candidate set of values of...

Errors-in-variables (EIV) biases plague asset pricing tests. We offer a new perspective on ad-dressing the EIV issue: instead of viewing EIV biases as estimation errors that potentiallycontaminate next-stage risk premium estimates, we consider them to be return innovationsthat follow a...

This paper considers forecast combination with factor-augmented regression. In this framework, a large number of forecasting models are available, varying by the choice of factors and the number of lags. We investigate forecast combination using weights that minimize the Mallows and the...

This paper considers forecast combination with factor-augmented regression. In this framework, a large number of forecasting models are available, varying by the choice of factors and the number of lags. We investigate forecast combination across models using weights that minimize the Mallows...