Two Different Exits: Prediction and Performance of Stocks that are About to Stop Trading

Ting Bai (), Jens Hilscher and Yitian Xiao
Additional contact information
Ting Bai: University of California, Davis, USA
Yitian Xiao: Mingshi Investment, 488 Middle Yincheng Road, Shanghai, China

Quarterly Journal of Finance (QJF), 2023, vol. 13, issue 01, 1-28

Abstract: This paper predicts the two most common stock market exits — mergers and drops — using logit models based on firm-level variables and analyzes the returns of stocks that have high exit probabilities. Such analysis is important for investors given that frequent exits are partly responsible for the large US listing gap (Doidge et al., 2017). High merger probability stocks have positive 3-factor alphas and lower-than-average volatility. Firms with high drop probabilities have anomalously negative 3-, 4-, and 5-factor alphas between −1.8% and −4% per month. Results are robust to controlling for the effects of skewness, volatility, and turnover on returns.

Keywords: Mergers; exits; stock returns; anomalies (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S2010139223500039
Access to full text is restricted to subscribers

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:wsi:qjfxxx:v:13:y:2023:i:01:n:s2010139223500039

Ordering information: This journal article can be ordered from

DOI: 10.1142/S2010139223500039

Access Statistics for this article

Quarterly Journal of Finance (QJF) is currently edited by Fernando Zapatero

More articles in Quarterly Journal of Finance (QJF) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().