Large Sample Estimators of the Stochastic Discount Factor
118 Pages Posted: 7 Mar 2018 Last revised: 18 Jan 2024
Date Written: January 17, 2024
Abstract
Abstract We propose estimators of the stochastic discount factor (SDF) using large cross-sections of individual stock returns. The estimators are obtained by a simple bias-corrected cross-sectional regression. Our small-sample bias correction for short time series allows us to exploit unbalanced panels of individual stock returns, thereby reducing survivorship biases. Our estimators can accommodate prespecified traded or non-traded factors, as well as latent factors. The estimators perform well in simulations. We apply our estimators to return data for U.S. individual stocks over a 50-year sample period and identify those factors in popular asset pricing models that command significant premia. A number of proposed non-traded factors have insignificant risk premia. Contrary to many studies, we find the market factor has a significant premium, as do profitability, value, and momentum factors.
Keywords: Asset Pricing, Factor Structure, Stochastic Discount Factor, SDF, Pricing Kernel
JEL Classification: G1, G12
Suggested Citation: Suggested Citation