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Seminar 217, Risk Management: Proliferation of Anomalies and Zoo of Factors – What does the Hansen–Jagannathan Distance Tell Us?Seminar: Risk Seminar  October 23  11 a.m.12:30 p.m.  1011 Evans Hall Speaker: Xiang Zhang, SWUFE Consortium for Data Analytics in Risk Recent research finds that prominent asset pricing models have mixed success in evaluating the crosssection of anomalies, which highlights proliferation of anomalies and zoo of factors. In this paper, I investigate that how is the relative pricing performance of these models to explain anomalies, when comparing their misspecification errors– the Hansen–Jagannathan (HJ) distance measure. I find that a tradedfactor model dominates others in a specific anomaly by incorporating the multiple HJ distance comparing inference. However, different from the current research of Barillas and Shanken (2017) and Barillas, Kan, Robotti and Shanken (2018), I result that the HJ distance is a general statistic measure to compare models and some modelderived nontraded factors even outperform traded factors. Second, there is a large variation in the shape and curvature of these confidence sets of anomalies, which makes any single SDF difficult to satisfy confidence sets of anomalies all. My results imply that further work is required not only in pruning the number of priced factors but also in building models that explain the anomalies better. 

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