Please use this identifier to cite or link to this item:
Title: Loan loss provisions and return predictability: a dynamic perspective
Authors: Gao, Phoebe
Lim, Chu Yeong
Liu, Xiumei
Zeng, Colin Cheng
Keywords: Business::Accounting
Issue Date: 2022
Source: Gao, P., Lim, C. Y., Liu, X. & Zeng, C. C. (2022). Loan loss provisions and return predictability: a dynamic perspective. China Journal of Accounting Research, 15(2), 100224-.
Journal: China Journal of Accounting Research
Abstract: This paper examines the impact of loan loss provisions (LLPs) on return predictability during 1994–2017. We find that on average, LLPs are negatively associated with one year ahead stock returns. This effect is particularly significant during the global financial crisis but much weaker during the Basel II and III periods. Consistent with these findings, a long–short trading strategy based on LLPs generates positive abnormal returns during the Basel II and III periods but negative abnormal returns during the financial crisis. Cross-sectional tests show that this effect is more pronounced among banks with greater information asymmetry. Decomposition of LLPs suggests that these findings are driven mainly by nondiscretionary LLPs. Overall, our results suggest that the relationship between LLPs and future stock returns is not linear but contingent on bank regulations and macroeconomic conditions.
ISSN: 1755-3091
DOI: 10.1016/j.cjar.2022.100224
Schools: Nanyang Business School 
Rights: © 2022 Sun Yat-sen University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:NBS Journal Articles

Files in This Item:
File Description SizeFormat 
1-s2.0-S1755309122000041-main.pdf514.61 kBAdobe PDFThumbnail

Citations 50

Updated on Dec 5, 2023

Page view(s)

Updated on Dec 7, 2023


Updated on Dec 7, 2023

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.