Abstract
Purpose Share repurchase programs are the most important form of payout, yet the implications of incomplete share repurchase programs have not been examined in previous literature. This study tests whether incomplete share repurchase programs are seen as a positive or as a negative signal by investors.Design/methodology/approach The perception of incomplete share repurchase programs by algorithmic traders, institutional investors and analysts is analyzed with structural equation models, seemingly unrelated regressions, propensity score matching and buy-and-hold abnormal returns on data from share repurchase programs in the United States. In contrast to previous literature, algorithmic trading is appropriately estimated as a latent variable, leading to more reliable results. Furthermore, decisions about share repurchases and dividends are appropriately modeled simultaneously and iteratively, based on findings from previous literature.Findings The results show that sophisticated investors such as algorithmic traders, institutional investors and financial analysts avoid incomplete share repurchase programs over a long-term investment horizon. Thus, incomplete share repurchase programs are interpreted as negative signals. Additional analyses reveal that share repurchase programs are not completed due to insufficient cash flow, as a result of financial difficulties. Overall, this implies that financial managers should be careful to announce share repurchase programs they know cannot be completed, similar to dividends that cannot be maintained over a long-term horizon.Originality/value This study is the first to consider incomplete share repurchase programs. The findings are of interest to scholars and practitioners, as this study goes beyond narrow repurchase program announcement windows, and instead focuses on the longer-term investment horizon over the life of the share repurchase program, which is often ignored in prior research.