Stock price delay and the cross-section of expected returns: A story of night and day

Ge Yang and Ximing Yin

International Review of Economics & Finance, 2024, vol. 96, issue PB

Abstract: We examine how individual stock price reacts to intraday and overnight market information. By examining stock betas, we document a stark gap between day beta and night beta and nontrivial asynchronous beta, which captures the slow diffusion of information. We provide evidence that this information delay can predict future stock returns over a one-month period. Long-short portfolios sorted on the gap between day beta and night beta and asynchronous beta generate raw returns of 0.8% and 0.39% and risk-adjusted alphas of 0.77% and 0.28% per month. These results are robust to alternative asset pricing models and when controlling for firm characteristics, such as size, book-to-market ratios, liquidity, investor recognition and limits-to-arbitrage characteristics. We also explore the heterogeneity of the information delay premium and find that the predictive power of information delay for future return is stronger among small, value firms, less visible firms, illiquid firms and firms with higher limit-to-arbitrage. We further provide evidence that our measure of price delay indeed offers incremental information for cross-section return prediction after we explicitly control for the conventional measure of Hou and Moskowitz (2005)'s price delay.

Keywords: Information delay; Night beta; Cross-sectional expected return; Market friction; Asynchronous beta; Market efficiency (search for similar items in EconPapers)
JEL-codes: G12 G14 G15 (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1059056024006610
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:96:y:2024:i:pb:s1059056024006610

DOI: 10.1016/j.iref.2024.103669

Access Statistics for this article

International Review of Economics & Finance is currently edited by H. Beladi and C. Chen

More articles in International Review of Economics & Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().