Risk Premium Estimation with Multicollinear and Invariant Betas by the Two-Pass Cross-Sectional Regressions
34 Pages Posted: 19 Mar 2010 Last revised: 17 Apr 2011
Date Written: March 25, 2011
Abstract
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 financial data, show that the TP estimation can lead to unreliable statistical inferences when betas are multicollinear and/or invariant. Estimates of factor risk prices and the pricing intercept can have biases larger than 100% of the true value. Also the t-test for hypothesis on risk prices and the intercept have very low statistical power in these cases. Various pre-diagnostic methods are proposed in order to evaluate the reliability of the inferences from the TP estimation in empirical work.
Keywords: Two-Pass, risk prices, betas, beta rank
JEL Classification: C12, C13, C3
Suggested Citation: Suggested Citation
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