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• W3125133312 abstract "We develop a new approach to modeling dynamics in cash flow data extracted from daily firm-level dividend announcements. We decompose daily cash flow news into a persistent component, jumps, and temporary shocks. Empirically, we find that the persistent cash flow component is a highly significant predictor of future growth in dividends and consumption. Using a log-linearized present value model, we show that news about the persistent dividend growth component helps predict stock returns consistent with asset-pricing constraints implied by this model. News about the daily dividend growth process also helps explain concurrent return volatility and the probability of jumps in stock returns." @default.
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• W3125133312 date "2018-01-01" @default.
• W3125133312 modified "2023-09-23" @default.
• W3125133312 title "High-frequency Cash Flow Dynamics" @default.
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• W3125133312 doi "https://doi.org/10.2139/ssrn.3127042" @default.
• W3125133312 hasPublicationYear "2018" @default.
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