Estimation and Evaluation of Conditional Asset Pricing Models
研究发现，用最优管理组合和条件矩约束评估几个新提出的消费型股票收益模型时，它们未能捕捉权益市场风险溢价的关键特征。为此构建了最优GMM估计量，并展示了检验零模型与备择模型的最优管理组合选择。
ABSTRACT 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.