R&D information quality and stock returns

Tao Huang, Junye Li, Fei Wu and Ning Zhu

Journal of Financial Markets, 2022, vol. 57, issue C

Abstract: Investors demand higher premiums from firms whose future R&D performance is difficult to evaluate. We construct a measure of R&D information quality (RDIQ) by linking a firm's historical innovation input (R&D expenditures) and innovation outcome (sales) and find significant evidence that expected excess returns decrease with RDIQ. We find that the high-minus-low RDIQ hedge portfolio earns excess returns of −23 (−25) bps per month in value-weighted (equal-weighted) returns. We also find that the RDIQ effect is weakly correlated with commonly used risk factors, is stronger for firms with greater uncertain business environment, and exhibits incremental pricing power.

Keywords: Research and development; Information quality; Return predictability; Factor models (search for similar items in EconPapers)
JEL-codes: G12 G14 O32 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finmar:v:57:y:2022:i:c:s1386418120300689

DOI: 10.1016/j.finmar.2020.100599

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