The qfactors library at globalq.org has just been updated through December 2019. The table below reports the latest headtohead factor spanning tests: The HouXueZhang (2015) qfactor model continues to dominate the FamaFrench (2018) 6factor model in the January 1967December 2019 sample. On the one hand, the 6factor model cannot subsume the qfactors. The investment premium is 0.36% per month (t = 4.45), with a 6factor alpha of 0.09% (t = 2.65). The return on equity (Roe) premium is 0.54% (t = 5.46), with a 6factor alpha of 0.26% (t = 4.25). The GibbonsRossShanken (1989, GRS) test strongly rejects the 6factor model based on the null hypothesis that the 6factor alphas of the investment and Roe premiums are jointly zero (p = 0.00). On the other hand, the qfactor model fully subsumes the FamaFrench factors. The HML, CMA, and RMW premiums are on average 0.3%, 0.29%, and 0.28% per month (t = 2.29, 3.24, and 2.82), but their qfactor alphas are tiny, 0.04%, 0.01%, and 0.03% (t = 0.35, 0.23, and 0.35), respectively. The momentum factor, UMD, is on average 0.63% (t = 3.66), but its qfactor alpha is small, only 0.15% (t = 0.66). The GRS test fails to reject the qfactor model based on the null that the qfactor alphas of HML, CMA, RMW, and UMD are jointly zero (p = 0.79). Don't take my word for it. Go ahead and replicate the numbers. If your replication fails, I am the jerk. Otherwise, how about using the better factor model from now on? That's right. Ten years on, it seems that the qfactor model is indeed "A Better Factor Model That Explains More Anomalies." My apologies for taking so long, but please know that we're doing the best we can.
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Lu Zhang
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