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Evaluating alternative methods for testing asset pricing models with historical data

机译:评估使用历史数据测试资产定价模型的替代方法

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摘要

We follow the correct Jagannathan and Wang (2002) framework for comparing the estimates and specification tests of the classical Beta and Stochastic Discount Factor/Generalized Method of Moments (SDF/GMM) methods. We extend previous studies by considering not only single but also multifactor models, and by taking into account some of the prescriptions for improving empirical tests suggested by Lewellen, Nagel and Shanken (2010). Our results reveal that SDF/GMM first-stage estimators lead to lower pricing errors than OLS, while SDF/GMM second stage estimators display higher pricing errors than the classical Beta GLS method. While Jagannathan and Wang (2002), and Cochrane (2005) conclude that there are no differences when estimating and testing by the Beta and SDF/GMM methods for the CAPM, we show that their conclusion cannot be extensible for multifactor models. Moreover, the Beta methods (OLS and GLS) seem to dominate the SDF/GMM (first and second stages) procedure in terms of estimators' properties. These results are consistent across benchmark portfolios and sample periods. © 2010 Elsevier B.V.
机译:我们遵循正确的Jagannathan和Wang(2002)框架来比较经典Beta和随机贴现因子/广义矩量法(SDF / GMM)方法的估计和规格测试。我们不仅考虑单因素模型,而且考虑多因素模型,并考虑到Lewellen,Nagel和Shanken(2010)提出的一些改进经验检验的方法,从而扩展了以前的研究。我们的结果表明,SDF / GMM第一阶段估算器的定价误差比OLS低,而SDF / GMM第二阶段估算器的定价误差比传统的Beta GLS方法更高。尽管Jagannathan和Wang(2002),以及Cochrane(2005)得出结论,通过CAPM的Beta和SDF / GMM方法进行估计和测试时没有差异,但我们证明了他们的结论对于多因素模型是不可扩展的。此外,就估计器的属性而言,Beta方法(OLS和GLS)似乎主导了SDF / GMM(第一阶段和第二阶段)过程。这些结果在基准投资组合和样本期间是一致的。 ©2010 Elsevier B.V.

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