Capital Market Anomalies and Quantitative Research

Abstract

Quantitative research analysts (Quants) produce in-depth quantitative and econometric modeling of market anomalies to assist sell-side analysts and institutional clients with stock selection strategies. Quants are associated with more efficient analyst forecasting behavior on anomaly predictors — stock recommendations and target prices on anomaly-longs (anomaly-shorts) are more (less) favorable and investment value of analyst research is higher. Quant research facilitates “smart money” trades of institutional clients on anomaly stocks — the likelihood of purchasing underpriced (overpriced) stocks unconditionally and in response to inflows is higher (lower) for client funds. Finally, we provide evidence that, all else equal, cross-sectional return predictability of anomaly long-short strategies is attenuated for stocks with increased Quant coverage. The evidence is consistent with the interpretation that Quants add value to financial markets, and consequently, increase market efficiency with respect to anomaly predictors.

Keywords: analyst recommendations, analyst research, mutual funds, institutional trading, anomalies, quantitative research, quants, market efficiency, cross-sectional return predictability

JEL Classification: G00, G11, G14, G23, G24