This paper proposes two new estimators for determining the number of factors (r) in static approximate factor models. We exploit the well-known fact that the r largest eigenvalues of the variance matrix of N response variables grow unboundedly as N increases, while the other eigenvalues remain...

Under the APT framework and the assumption that the market portfolio is well-diversified, if not mean-variance efficient, the common factors in raw-returns are the market return plus the common factors in the space of excess-returns over the market return. This explains why the market betas fail...

We consider the estimation methods for the rank of a beta matrix corresponding to a multifactor model and study which method would be appropriate for data with a large number of assets. Our simulation results indicate that a restricted version of Cragg and Donald's (1997) Bayesian Information...

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...

This paper considers maximum likelihood (ML) based inferences for dynamic panel data models. We focus on the analysis of the panel data with a large number of cross-sectional units and a small number of repeated time-series observations for each cross-sectional unit. We examine several different...