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...

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...

This paper examines finite-sample properties of a model test method developed by Hansen and Jagannathan (1997) and Jagannathan and Wang (1996). As a model comparison tool, Hansen and Jagannathan (1997) propose a measure which estimates the maximum pricing error generated by an asset pricing...

The two-pass cross-sectional regression method has been widely used to evaluate linear factor pricing models. One drawback of the studies based on this method is that statistical inferences are often made ignoring potential conditional heteroskedasticity or/and autocorrelation in asset returns...

We propose new generalized method of moments (GMM) estimators for the number of latent factors in linear factor models. The estimators are appropriate for data with a large (small) number of cross-sectional observations and a small (large) number of time series observations. The estimation...