Two‐Pass Tests of Asset Pricing Models with Useless Factors
研究标准两阶段方法在检验含错误设定因子的贝塔定价模型时的性质，发现无用因子（与所有资产收益独立）的贝塔风险被错误定价的频率偏高，且时间序列观测数越多偏差越大，并探讨了检测无用因子的方法。
In this paper we investigate the properties of the standard two‐pass methodology of testing beta pricing models with misspecified factors. In a setting where a factor is useless, defined as being independent of all the asset returns, we provide theoretical results and simulation evidence that the second‐pass cross‐sectional regression tends to find the beta risk of the useless factor priced more often than it should. More surprisingly, this misspecification bias exacerbates when the number of time series observations increases. Possible ways of detecting useless factors are also examined.