In the past, the dividend yield was once considered a strong predictor for equity returns. For example, The Gordon Growth Model used to determine the “true” value of a stock based on a future series of dividends that grow at a constant rate discounted to the present time. There is a large amount of literature exploiting the properties of dividends and dividend yields to better understand the fundamentals of asset pricing both in the time series and cross-section.

However, more recent academic research started to show deteriorated results in recent years. This also confirms authors Gray and Vogel in the “Dissecting Shareholder Yield”. The authors state that: “We confirm on a newer dataset what other research has found; dividend yield no longer works, but more complete measures of shareholder yield hold promise.” The problem of dividends is that they are not the only way that companies are able to distribute their excess cash back to the shareholders. The other possibility of how to distribute the cash is a stock repurchase. The stock repurchase is a simple operation, where the company buys back its own shares from the marketplace. This results in a reduced number of existing shares, making each worth a greater percentage of the corporation. Recently, this has become a favorite way for firms. Adding the fact that there is growing evidence that stock repurchases have substituted dividends in the last 15-20 years, it is clear that this topic deserves attention from the academic world.

This paper suggests a new combined ratio, the “net payout yield”, combined from both dividends and stock repurchases. This results in a very strong predictor of future equity performance, which can be even used in a profitable trading strategy that goes long a portfolio of high yield stocks and short a portfolio of low yield stocks while rebalancing these holdings on an annual basis.

Fundamental reason

Although for a long time, dividends were considered to be a strong predictor for a stock’s health, the recent research shows that this does not hold true anymore and potential investor has to use another predictor. In the past, the high dividend yield showed that a stock is cheap compared to the stream of cash going back to shareholders. Naturally, it would be logical to use the same logic but adjust the predictor to the actual situation. Net payout yield enhances this ratio because it also considers alternative forms of cash redistribution.

Research proved that the cross-sectional relation between total payout yield and returns is more distinct than the relation between dividend yield and returns. This conclusion is reinforced by Fama-MacBeth regressions of returns on beta, size, book-to-market and yield variables in the paper. In these cross-sectional time-series regressions, dividend yields show an insignificant association with returns, whereas the payout measures exhibit highly significant associations with returns. Moreover, payout yields show no significant change in their dynamic properties, and consequently, their predictive ability remains intact across various time periods. It was also proved that payout yields exhibit significant out-of-sample predictability, whereas dividend yields do not. Last but not least, the trading strategy based on this idea is profitable and results in portfolios with negative market betas and negative loading on the size factor, suggesting that these returns are not likely to be explained by standard risk measures.

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Markets Traded

Financial instruments

Confidence in anomaly's validity

Backtest period from source paper

Notes to Confidence in Anomaly's Validity

Indicative Performance

Period of Rebalancing

Notes to Indicative Performance

per annum, annualized monthly return (geometrically) of 1,68%, long only portfolio based on net payout yield, data from table 3 Panel D,

Notes to Period of Rebalancing

Estimated Volatility

Number of Traded Instruments

Notes to Estimated Volatility

not stated

Notes to Number of Traded Instruments

more or less, it depends on investor’s need for diversification

Maximum Drawdown

Complexity Evaluation
Complex strategy

Notes to Maximum drawdown

not stated

Notes to Complexity Evaluation

Sharpe Ratio

Simple trading strategy

The investment universe consists of all stocks on NYSE, AMEX and NASDAQ. At the end of June of each year t, 10 portfolios are formed on the basis of ranked values net payout yield. The net payout yield is the ratio of dividends plus repurchases minus common share issuances in year t to year-end market capitalization. There are two measures of payout yield, one based on the statement of cash flows, the other based on the change in Treasury stocks. For the net payout yield, we use the cash flow-based measure of repurchases. The portfolio with the highest net payout yield is bought and held for one year after which it is rebalanced.

Hedge for stocks during bear markets

No - Long-only value stocks logically can’t be used as a hedge against market drops as a lot of strategy’s performance comes from equity market premium (as the investor holds equities, therefore, his correlation to the broad equity market is very very high). Now, evidence for using a long-short value factor portfolio as a hedge against the equity market is very mixed. Firstly, there are a lot of definitions of value factor (from simple standard P/B ratios to various more complex definitions as in this strategy), and the performance of different value factors really differ in times of stress. Also, there are multiple research papers in a tone of work of Cakici and Tan : “Size, Value, and Momentum in Developed Country Equity Returns: Macroeconomic and Liquidity Exposures” that link value factor premium to liquidity and growth risk and show that the implication is that value returns can be low prior to periods of low global economic growth and bad liquidity.

Source paper
Boudoukh, Michaely, Richardson, Roberts: On the Importance of Measuring Payout Yield: Implications for Empirical Asset Pricing
- Abstract

Previous research showed that the dividend price ratio process changed remarkably during the 1980’s and 1990’s, but that the total payout ratio (dividends plus repurchases over price) changed very little. We investigate implications of this difference for asset pricing models. In particular, the widely documented decline in the predictive power of dividends for excess stock returns in time series regressions in recent data is vastly overstated. Statistically and economically significant predictability is found at both short and long horizons when total payout yield is used instead of dividend yield. We also provide evidence that total payout yield has information in the cross-section for expected stock returns exceeding that of dividend yield and that the high minus low payout yield portfolio is a priced factor. The evidence throughout is shown to be robust to the method of measuring total payouts.

Strategy's implementation in QuantConnect's framework (chart+statistics+code)
Other papers
Gray, Vogel: Dissecting Shareholder Yield
- Abstract

We study a variety of previously examined payout yields over time: dividends, share repurchases cash flow, and equity issuance. We confirm on a newer dataset what other research has found; dividend yield no longer works, but more complete measures of shareholder yield hold promise. We contribute to the literature by examining an additional variable to payout yield, net debt pay down. The addition of net debt pay down helps performance, but is not a panacea. We find that regardless of the yield metric chosen, the predictive power of separating stocks into high and low yield portfolios has lost considerable power in the last twenty years. We also explore the concept of separating yield metrics by payout percentage as a way to salvage the predictability of yield metrics. We find no evidence that using payout percentage within a yield category can systematically improve portfolio performance.

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