Credit market conditions, expected return proxies, and bank stock returns
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
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Detail(s)
Original language | English |
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Article number | 101021 |
Journal / Publication | Global Finance Journal |
Volume | 62 |
Online published | 22 Jul 2024 |
Publication status | Published - Sept 2024 |
Link(s)
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. © 2024 Elsevier Inc.
Research Area(s)
- Bank stocks, Business cycles, Credit market conditions, Expected return proxies
Citation Format(s)
Credit market conditions, expected return proxies, and bank stock returns. / Yang, Huan; Cai, Jun; Huang, Lin et al.
In: Global Finance Journal, Vol. 62, 101021, 09.2024.
In: Global Finance Journal, Vol. 62, 101021, 09.2024.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review