Abstract
We examine the asymptotic and finite-sample properties of the two-pass (TP) cross-sectional regressions estimators when factors and asset returns are conditionally heteroskedastic and/or autocorrelated. Using a minimum distance approach, we derive the heteroskedasticity- and/or autocorrelation-consistent (HAC) standard errors and the optimal TP estimator. A HAC model specification test statistic is also derived. Our Monte Carlo simulation results reveal the importance of controlling for autocorrelation. The HAC standard errors produce the most reliable inferences under autocorrelation. The HAC specification test is a viable alternative if the number of asset returns is small and the number of time-series observations is large.
Original language | English (US) |
---|---|
Article number | nbs006 |
Pages (from-to) | 669-701 |
Number of pages | 33 |
Journal | Journal of Financial Econometrics |
Volume | 10 |
Issue number | 4 |
DOIs | |
State | Published - Sep 2012 |
Keywords
- Cross-sectional regression
- Factor model
- Fama and MacBeth
- Minimum distance
- Robust standard errors
- Two-pass
ASJC Scopus subject areas
- Finance
- Economics and Econometrics