Testing Beta-Pricing Models Using Large Cross-Sections

Abstract

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 empirical findings regarding estimated risk premia and validity of beta-pricing models. We generalize our theoretical results to the more realistic case of unbalanced panels. The practical relevance of our findings is confirmed via Monte Carlo simulations.

Keywords: beta-pricing models, ex-post risk premia, two-pass cross-sectional regression, large $N$ asymptotics, specification test; unbalanced panel

JEL Classification: C12, C13, G12