What is the Risk-Premium for the SDF?

Part of the Lubar Research Seminar Series

Speaker:  John Huck, University Wisconsin – Milwaukee

We develop a model that identifies a time-varying risk-premium for a latent stochastic discount factor (SDF) with minimal assumptions. The SDF risk-premium can be identified in two ways: (1) as a function of the weighted average variance risk-premium (VRP) for individual stocks and the VRP for the market, and (2) as a function of the cross-sectional weighted variance of expected stock returns. We construct empirical proxies for the SDF risk-premium, and show that they can price the cross-section of stock returns. Specifically, investors pay a premium for assets that have higher betas to the SDF risk-premium factors.