Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/60952
Authors: 
Adrian, Tobias
Crump, Richard K.
Moench, Emanuel
Year of Publication: 
2011
Series/Report no.: 
Staff Report, Federal Reserve Bank of New York 493
Abstract: 
We study regression-based estimators for beta representations of dynamic asset pricing models with affine and exponentially affine pricing kernel specifications. These estimators extend static cross-sectional asset pricing estimators to settings where prices of risk vary with observed state variables. We identify conditions under which four-stage regression-based estimators are efficient and also present alternative, closed-form linearized maximum likelihood (LML) estimators. We provide multi-stage standard errors necessary to conduct inference for asset pricing tests. In empirical applications, we find that time-varying prices of risk are pervasive, thus favoring dynamic cross-sectional asset pricing models over standard unconditional specifications.
Subjects: 
dynamic asset pricing
Fama-MacBeth regressions
financial econometrics
JEL: 
E58
G28
Document Type: 
Working Paper

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