Footnote:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments October 26, 2020 erstellt
Description:
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 particular correlation structure. We factor this structure into our test design,yielding a new regression model that generates the most accurate risk premium estimates. Wedemonstrate the theoretical appeal as well as the empirical relevance of our new estimator