The cross-sectional return predictability of employment growth: A liquidity risk explanation
journal contribution
posted on 2021-10-11, 08:43 authored by Weimin Liu, Di Luo, Seyoung Park, Huainan ZhaoHuainan ZhaoEmployment growth (EG) is related to liquidity fundamentals of investment opportunities, firm health, and information environment and quality. This, in turn, implies that liquidity risk may play a role in explaining the relation between EG and stock returns. We find strong empirical evidence supporting the link between EG and liquidity risk. Stocks of high-EG firms are more liquid and exposed to lower liquidity risk than stocks of low-EG firms. After adjusting for liquidity risk, EG loses its power to predict returns.
Funding
Ministry of Education of the Republic of Korea
National Research Foundation of Korea. Grant Number: NRF-2019S1A5A2A03054249
History
School
- Business and Economics
Department
- Business
Published in
Financial ReviewVolume
57Issue
1Pages
155-178Publisher
WileyVersion
- AM (Accepted Manuscript)
Rights holder
© 2021 The Eastern Finance AssociationPublisher statement
This is the peer reviewed version of the following article: Liu, W. ... et al. (2021). The cross-sectional return predictability of employment growth: A liquidity risk explanation. Financial Review, 57(1), pp. 155-178. Doi: 10.1111/fire.12279, which has been published in final form at https://doi.org/10.1111/fire.12279. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibitedPublication date
2021-08-11Copyright date
2022ISSN
0732-8516eISSN
1540-6288Publisher version
Language
- en
Depositor
Prof Huainan Zhao. Deposit date: 8 October 2021Usage metrics
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