Modeling Quarterly Dividends and Stock Returns Jointly

Summary

This note motivates bivariate time-series models for quarterly stock returns and dividends. It highlights features a model may need to capture: managers have discretion over payouts, dividends tend to remain stable or rise modestly, and cuts are often comparatively large. It also states that dividends are positively related to past stock returns.

The note points to two possible applications: comparing investment in stocks with dividend swaps, and valuing long-dated stock options. It does not specify a model, estimation procedure, data set, or empirical results, so it serves as a research question and motivation rather than a developed method. Any application would need to account for the limited frequency of dividend observations and the asymmetry between dividend increases and cuts.

Key ideas

• Quarterly dividends and stock returns can be modeled jointly as bivariate time series.
• Dividend decisions reflect managerial discretion and tend to be sticky.
• Dividend cuts are often larger than the small increases that occur more commonly.
• The note reports a positive relationship between dividends and lagged stock returns.
• Joint models may inform stock versus dividend swap choices and long-term option pricing.

Tags

# Joint time series model of dividends and stock returns


# Joint time series model of dividends and stock returns












Dividends on stocks are typically paid quarterly. Is there research on bivariate time series models of quarterly stock returns and dividends? Corporate management has discretion over dividends, and they are often unchanged or increased slightly, because investors dislike dividend cuts. When dividend cuts are made, they are often large. Stock dividends are positively correlated to lagged stock returns.

Two applications of time series models of stock returns and dividends are deciding whether to invest in stocks vs. dividend swaps and pricing long-term stock options.

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.