"We test the Elton and Gruber model of ex-dividend stock pricing over a period spanning all US tax law changes since 1926. Our results indicate that price drop ratios (ΔP/D) and ex-day returns are related to dividend and capital gains tax rates in the theorized manner. Consistent with tax clienteles, we also find that ex-day price movements of higher dividend yield stocks are driven more by corporate tax rates, while lower yield stocks are more influenced by personal rates. Finally, we demonstrate that the positive relationship between ΔP/D and the dividend yield becomes stronger as the tax differential | td - t cg | widens." Copyright (c) 2010 Financial Management Association International.

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Taxes and microstructure constraints are often cited as possible explanations for why stock prices drop by less than the dividend on their ex-dates. Using a sample of real estate investment trusts, which have no significant correlation between dividend size and yield, we find that close-to-open ex-dividend price drops are related to dividend size as suggested by the microstructure models, but close-to-close price drops are related to dividend yield as predicted by the tax theory. These results imply that overnight price drops are primarily determined by microstructure, but that trading during the ex-day causes prices to adjust to reflect individual tax preferences.Empirical research has firmly established that on ex-dividend days stock prices drop by less than the full dividend amount. While there is no clear consensus about why this occurs, there have been several plausible explanations. Elton and Gruber (1970, hereafter EG) attribute the anomaly to the fact that dividends are taxed more heavily than capital gains for most investors. Their pricing model further predicts that there will be a positive relation between the ex-day price drop ratio ( P/D) and the dividend yield due to the formation of taxmotivated dividend "clienteles," where investors in higher (lower) tax brackets tend to select lower (higher) dividend yield stocks. More recent explanations for the ex-day anomaly are based on market microstructure. Bali and Hite (1998, hereafter BH) argue that the effect is driven by the fact that stock prices historically have been constrained to discrete tick multiples, and Dubofsky (1992) also incorporates disparate treatment of buy and sell limit orders at the ex-day open. In both of the microstructure models, P/D is a sawtooth-shaped function of the dividend amount (D), but the dividend yield (D/P) has no special importance.In this article, we test for the specific patterns implied by the tax and microstructure hypotheses using both close-to-close and overnight price drops.

PurposeThis study explores the “Sell-in-May” effect in environmental, social and governance (ESG) indices and compares the seasonal effects in ESG equity indices with conventional equity indices.Design/methodology/approachThe authors use ordinary least squares (OLS) models and M-estimation as a robustness check, as OLS estimates may be sensitive to outliers. The authors also employ bootstrap simulations to use the data efficiently and to test whether seasonal trading strategies can produce abnormal returns.FindingsThe regression results reveal that seasonal effects in USA ESG equity indices are similar to those in conventional equity indices. Higher returns are noticeable from November through April, mainly in ESG indices including small and medium capitalization stocks. When the authors extend the Sell-in-May strategy from October through April, the authors find that the seasonal effect is significant for multiple ESG indices, even after accounting for the January effect. Bootstrap simulations show that the Sell-in-May and Extended Sell-in-May strategies appear to beat a buy-and-hold strategy on a risk-adjusted basis and that this result is stronger in medium and small capitalization ESG indices.Originality/valueAlthough previous research has considered the effectiveness of seasonal equity trading strategies and the general performance of ESG stocks, this is the first study to specifically examine the “Sell in May” effect in ESG indices. The authors also consider an “Extended” Sell-in-May strategy where stocks are purchased one month earlier and show that the strategy produces higher returns.