Estimation and Evaluation of Conditional Asset Pricing Models

• 成果类型: Article
• 署名作者: Nagel, Stefan; Singleton, Kenneth J.
• 署名单位: Stanford University; National Bureau of Economic Research
• 刊物名称: JOURNAL OF FINANCE
• ISSN/ISSBN: 0022-1082
• DOI: 10.1111/j.1540-6261.2011.01654.x
• 发表日期: 2011
• 页码: 873-909
• 关键词: CROSS-SECTIONAL TEST; generalized-method; sample properties; gmm; consumption; bounds

摘要

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.