This paper analyzes the finite-sample performance of the two-pass (TP) estimators of factor risk prices when betas have high cross-sectional correlations (Multicollinear) and when betas have small cross-sectional variations (Invariant). Our Monte Carlo simulations, calibrated using actual...

Since Black, Jensen, and Scholes (1972) and Fama and MacBeth (1973), the two-pass cross-sectional regression (CSR) methodology has become the most popular approach for estimating and testing asset pricing models. Statistical inference with this method is typically conducted under the assumption...

This paper examines the asymptotic and finite sample properties of the two-pass cross-sectional regressions estimators, when the factors and the asset returns are conditionally heteroskedastic and/or autocorrelated. Using a minimum distance approach, we derive heteroskedasticity- and/or...

We improve on the Instrumented Principal Component Analysis (IPCA) model developed in Kelly, Pruitt and Su (2019) by providing more efficient Generalized Least Square (GLS) estimators with a closed-form limiting distribution allowing for a more consistent (mis)pricing inference. The IPCA model...

We introduce a framework to test for the exogeneity of a variable in a regression based on cross-sectional data. By sorting data with respect to a function (sorting score) of known exogenous variables, it is possible to utilize a battery of tools originally developed to detect model...

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...