Large Sample Estimators of the Stochastic Discount Factor
106 Pages Posted: 7 Mar 2018 Last revised: 7 Feb 2019
Date Written: February 5, 2019
We propose estimators of the stochastic discount factor (SDF) using large cross-section of individual stocks. We suggest a correction for the small sample bias in a standard GMM estimator induced by having a finite time series and show how to use the correction in exploiting unbalanced panels of individual stock returns. Our estimators can utilize both a prespecified set of traded or non-traded factors implied by a specific asset pricing model and latent factors estimated by multivariate statistical methods. The estimators perform well in simulations designed to mimic the U.S. equity markets. A lasso penalized version of the estimators does a good job of excluding systematic but unpriced factors. We apply our SDF estimators to the 10,112 individual stock price dynamics in the U.S. over 50 years from 1976 to 2016, and identify which factors in popular asset pricing models command a price of risk.
Keywords: Asset Pricing, Factor Structure, Stochastic Discount Factor, SDF
JEL Classification: G1, G12
Suggested Citation: Suggested Citation