A Stochastic discount factor approach to asset pricing using panel data asymptotics

Abstract

Using the Pricing Equation in a panel-data framework, we construct a novelconsistent estimator of the stochastic discount factor (SDF) which relies on thefact that its logarithm is the "common feature" in every asset return of theeconomy. Our estimator is a simple function of asset returns and does notdepend on any parametric function representing preferences.The techniques discussed in this paper were applied to two relevant issues inmacroeconomics and finance: the first asks what type of parametric preference-representation could be validated by asset-return data, and the second askswhether or not our SDF estimator can price returns in an out-of-sample forecasting exercise.In formal testing, we cannot reject standard preference specifications used inthe macro/finance literature. Estimates of the relative risk-aversion coefficientare between 1 and 2, and statistically equal to unity.We also show that our SDF proxy can price reasonably well the returns ofstocks with a higher capitalization level, whereas it shows some difficulty inpricing stocks with a lower level of capitalization.