Predictable Corporate Distributions and Stock Returns (Digest Summary)

The authors demonstrate that announcements of corporate distributions tend to be highly predictable and more likely to happen at 12-month intervals. Thus, these types of events can be readily forecast given the demonstrated high level of predictability. But the market does not seem to fully reflect the degree to which distribution events can be predicted in terms of portfolio construction and return examination.

By looking specifically at four types of corporate distributions—stock splits, stock dividends, special dividends, and substantive increases in regular cash dividends—and examining when these types of distributions are announced and how the market reacts to the announcements, the authors add to the existing research on pricing anomalies. These four types of corporate distributions are likely to take place at predictable intervals, particularly at one-year anniversaries, and the market generally reacts positively once distributions are announced.

In addition, despite the demonstrated predictability of corporate distribution events, abnormal positive returns can be earned through a trading strategy of purchasing stocks with a high estimated probability of distribution events. The authors find that excess returns tend to be lower for value-weighted portfolio returns compared with equal-weighted portfolio returns, for portfolios composed of larger firms, and for portfolios with stocks that have a higher percentage of institutional ownership. Nevertheless, all of the subsamples examined show significant excess returns.

These results suggest that traders could conceivably exploit this revealed pricing anomaly. The results also point toward potential refinements that might be made to existing models of price formation and to theories explaining corporate distribution decisions and investor valuation or corporate distribution announcements.

The authors study data from CRSP for the four types of corporate distribution events announced during January 1963–December 2012 for all common stocks listed on US stock exchanges. They look at the patterns of distribution events and note that events are more likely to occur at firms that have announced a similar event within the past three years. In addition, the event is most likely to occur on the anniversary of a preceding event, particularly the 12-month anniversary.

Next, the authors look at the five-day cumulative abnormal returns around the announcement dates for the four types of corporate distributions and find that the returns are all significantly positive for the four events during both the first and second halves of the sample period. Having established that corporate distribution events occur at regular intervals and that the market reacts positively to announcements of these events, the authors examine whether it is possible to profit from purchasing securities with a high estimated probability of a follow-on corporate distribution event in the upcoming month. They find that this strategy does produce significant abnormal returns; they proceed to assess the robustness of the findings across various subsamples. The authors show that their results are unrelated to omitted risk factors or model misspecification and are verifiably independent of calendar-based anomalies or seasonal patterns in stock returns. Although declines in predictability measures and subsequent erosion in outsize returns over time may be attributable to market learning, the anomaly persists.

This article is a clear and well-organized description of results that would be pertinent to anyone interested in market operations, pricing formation, and investor behavior. Although the authors themselves point out that some of the subsamples are quite small, there is enough substance here to merit further inquiry and rethinking of current models and theories regarding corporate distributions and investor valuation.