Credit market conditions, expected return proxies, and bank stock returns

Huan Yang, Jun Cai, Lin Huang and Alan J. Marcus

Global Finance Journal, 2024, vol. 62, issue C

Abstract: We evaluate the performance of expected return proxies during extreme credit market conditions and extreme phases of business cycles when realized returns on banks stocks are large in absolute value. We construct three sets of expected return proxies for individual bank stocks: (i) characteristic-based proxies; (ii) standard risk-factor-based proxies; and (iii) risk-factor-based proxies in which betas depend on firm characteristics. Based on the newly developed minimum error variance (MEV) criterion (Lee et al., 2020), the best performing expected return proxy is the risk-factor-based model that allows betas to vary with firm characteristics. We also examine whether these three expected return proxies can capture actual returns during either extreme credit market or extreme business-cycle conditions. We find that both risk-factor-based proxies explain returns better than characteristic-based proxies during these periods.

Keywords: Bank stocks; Expected return proxies; Credit market conditions; Business cycles (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1044028324000930
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:glofin:v:62:y:2024:i:c:s1044028324000930

DOI: 10.1016/j.gfj.2024.101021

Access Statistics for this article

Global Finance Journal is currently edited by Manuchehr Shahrokhi

More articles in Global Finance Journal from Elsevier
Bibliographic data for series maintained by Catherine Liu ().