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Estimation and Evaluation of Conditional Asset Pricing Models




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    • Nagel and Singleton are at the Graduate School of Business, Stanford University, and are affiliated with the National Bureau of Economic Research. We are grateful to seminar participants at Baruch College, the Berkeley–Stanford joint finance seminar, London Business School, Northwestern University, Princeton University, UC San Diego, the National Bureau of Economic Research, and the Western Finance Association Meetings, as well as to Fousseni Chabi-Yo, Wayne Ferson, Lars Hansen, Cam Harvey, and two anonymous referees for helpful comments.


We find that several recently proposed consumption-based models of stock returns, when evaluated using an optimal set of managed portfolios and the associated model-implied conditional moment restrictions, fail to capture key features of risk premiums in equity markets. To arrive at these conclusions, we construct an optimal Generalized Method of Moments (GMM) estimator for models in which the stochastic discount factor (SDF) is a conditionally affine function of a set of priced risk factors, and we show that there is an optimal choice of managed portfolios to use in testing a null model against a proposed alternative generalized SDF.