We develop a methodology for estimating and testing the effect of anomalies in conditional asset pricing models when premia are time-varying. Our method, which builds on the two-pass methodology, is developed for ordinary and weighted least-squares estimation, considering both cases of correct...

Building on the Shanken (1992) estimator, we develop a new methodology for estimating and testing beta-pricing models when a large number of assets N is available but the number of time-series observations is small. We show empirically that our large N framework can change substantially common...

This paper develops a methodology for inference on asset pricing models linear in latent risk factors, valid when the number of assets diverges but the time series dimension is fixed, possibly very small. We cast the factor model within the Arbitrage Pricing Theory of Ross (1976) and show that...

Our objective is to investigate the effect of model misspecification on mean-variance portfolios and to show how asset-pricing theory and asymptotic analysis (for large number of assets) can be used to provide powerful solutions to mitigate misspecification. The starting point of our analysis is...

Our objective is to develop a methodology to price the cross section of asset returns. Despite the hundreds of systematic risk factors considered in the literature (``factor zoo''), there is still a sizable pricing error. We show that what is missing in asset-pricing factor models is not...

We provide a short and selected review of the vast literature on cross-section predictability. We focus on the state of art methods used to forecast the cross-section of stock returns with major predictors and are primarily interested in the ideas, methods, and their applications. To understand...