Capital Market Anomalies and Quantitative Research

Justin Birru, Sinan Gokkaya and Xi Liu
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Justin Birru: Ohio State University
Sinan Gokkaya: Ohio University
Xi Liu: Miami University of Ohio

Working Paper Series from Ohio State University, Charles A. Dice Center for Research in Financial Economics

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. Quant-backed analysts exhibit more efficient forecasting behavior on anomaly predictors--stock recommendations and target prices issued on anomaly-longs (anomaly-shorts) are more (less) favorable. Investment value of such analysts' research is higher and their research reports are more likely to discuss implications of quantitative modeling and market anomalies. Quant research facilitates "smart money" trades of institutional clients on anomaly stocks--Quant research is associated with an increased (decreased) likelihood of purchasing underpriced (overpriced) stocks. Market participants recognize Quants--thematic reports authored by Quants generate abnormal reactions for corresponding stocks. Finally, we provide evidence consistent with quantitative research increasing market efficiency by attenuating cross-sectional predictability of anomaly based long-short strategies.

JEL-codes: G00 G11 G14 G23 G24 (search for similar items in EconPapers)
Date: 2018-03
New Economics Papers: this item is included in nep-fmk
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:ecl:ohidic:2018-07

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