Dividends and cash flow risk: Exploring an inverted J-shaped relationship
Jing Nie,
Huiyun Ge and
Xue Chang
International Review of Financial Analysis, 2025, vol. 106, issue C
Abstract:
Our paper identifies an inverted J-shaped relationship between dividends and future cash flow risk in the Chinese stock markets. By applying a variance decomposition method based on machine learning techniques, we find that higher dividend portfolios have lower cash flow risk for dividend-paying stocks, while cash flow risk for non-dividend portfolio is lower than low dividend portfolios. After further sorting the stocks into subgroups of increased and decreased dividends, we find that cash flow risk is larger for subgroups with decreased dividends than that with increased dividends for both non-dividend and dividend-paying stocks. Subsample tests show greater discrepancies in cash flow risk between non-dividend and quintile dividend-paying portfolios after the implementation of the various dividend regulation guidelines. Moreover, the risk premiums of cash flow news are positive and more strongly priced in down markets than up markets due to investors' greater aversion.
Keywords: Dividend; Cash flow risk; Big data; Variance decomposition; Chinese stock markets (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:106:y:2025:i:c:s1057521925006088
DOI: 10.1016/j.irfa.2025.104521
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