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Long-Run Common Stock Returns Following Stock Splits and Stock Dividends

Long-Run Common Stock Returns Following Stock Splits and Stock Dividends
Author: Hemang Desai
Publisher:
Total Pages:
Release: 2012
Genre:
ISBN:

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We examine one-to three-year performance of common stocks following stock split and stock dividend announcements made during the period 1976 to 1991. The average one-and three-year buy-and-hold abnormal returns after the announcement month are 8.19% and 7.55% respectively. Also, smaller firms exhibit larger announcement period as well as larger one-to three-year abnormal returns. The results cannot be explained away by general cash-dividend increase announcements or earnings announcements. Overall, the results are consistent with the hypothesis that the market underreacts to the stock split and the stock dividend announcements.


Long-Run Common Stock Returns Following Stock Splits and Reverse Splits

Long-Run Common Stock Returns Following Stock Splits and Reverse Splits
Author: Hemang Desai
Publisher:
Total Pages:
Release: 2012
Genre:
ISBN:

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We examine one- to three-year performance of common stocks following 5596 stock split and 76 reverse split announcements made during the period 1976 to 1991. For stock splits, on average, the one- and three-year buy-and- hold abnormal after the announcement month are 7.05% and 11.87%, respectively. For reverse splits, the corresponding abnormal returns are - 10.76% and -33.90%. The results suggest that the market underreacts to both the stock split and the reverse split announcements. We also provide evidence that the signal in stock splits is related to change in dividends. In particular, the announcement period and the long-run abnormal returns are both positively associated with an increase in dividends.


The Market Reaction to Stock Splits and the Ability to Earn Abnormal Returns

The Market Reaction to Stock Splits and the Ability to Earn Abnormal Returns
Author: Phương Anh Nguyễn
Publisher:
Total Pages: 402
Release: 2010
Genre:
ISBN:

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A stock split is often regarded as a pure cosmetic accounting treatment and yet prior research shows that the market reacts positively upon the arrival of the split announcement. However, up to now, there has not been any convincing explanation for this favourable response while there is intense debate amongst researchers about whether these positive abnormal returns persist in the future. We revisit the issues related to the performance of splitting companies both around and following the announcement date. This allows us to study the information content of the event and assess whether the market has incorporated the implication of such information in a timely manner. In addition, we hope to draw meaningful inference about the profitability of trading following the announcement date. Our findings suggest that there is information in the split announcements, which is positively valued by the market. However, abnormal returns cannot be earned with certainty following the event. This is evident in both the option market and the stock market. Specifically, if informed investors use the option market to trade on their information, then our results indicate that informed investors do not believe in the success of a strategy that buys splitting companies subsequent to the announcement date. This is because the post-split announcement drift does not exist following every split; it is conditioned on whether the firms will split again in the future. While prior studies argue that the long-run abnormal returns are sensitive to the time period, we find that the aggregate long-run abnormal returns are higher in a time period where there is a large proportion of companies that split multiple times. Nevertheless, knowing whether the companies have split multiple times in the past will not lead to positive abnormal returns ex-ante; these returns can only be guaranteed if investors are able to forecast accurately which sample firms will implement another split in the future. Once the split again condition is controlled for, there is no role for the time period to influence the magnitude and significance of the abnormal returns. We also discover that firms that have not split before consistently outperform firms that have. This implies that instead of buying every company that splits, investors can achieve higher returns by focusing on those that have not split in the recent past. However, the profitability of this strategy depends on the state of the market (bull versus bear market). In summary, the thesis shows that while stock splits are perceived as good news by investors, abnormal returns cannot be guaranteed following the announcement date. The information contained in a stock split is incorporated into stock prices in a timely manner, however, what type of information this event is capturing remains an open question.


Stock Splits and Large Stock Dividends

Stock Splits and Large Stock Dividends
Author: Graeme Rankine
Publisher:
Total Pages:
Release: 2000
Genre:
ISBN:

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Prior research has used inaccurate classification rules to distinguish between stock splits and stock dividends. For a sample of two-for-one stock distributions, we show that firms that accounted for the distribution as a stock dividend generated five-day abnormal returns of 2.70%, compared to 0.93% for the stock split firms. Announcement returns are positively related to earnings growth in the two years following the distribution for stock dividend firms but not for stock split firms. The accounting choice appears to be used to confirm management's private information about future earnings revealed at the time of the distribution announcement.


Long-Run Common Stock Performance After Stock Splits

Long-Run Common Stock Performance After Stock Splits
Author: Craig G. (Craig Gordon) Dunbar
Publisher: London : Richard Ivey School of Business, University of Western Ontario
Total Pages: 13
Release: 1997
Genre:
ISBN: 9780771420450

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Reexamining the Long-Run Stock Split Anomaly Puzzle

Reexamining the Long-Run Stock Split Anomaly Puzzle
Author: Rodney D. Boehme
Publisher:
Total Pages: 45
Release: 2001
Genre:
ISBN:

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Long-run performance is reexamined following stock splits during 1950 to 2000. Significantly positive and robust equally weighted abnormal returns are documented during the first year following the announcement month; however, significant value weighted long-run abnormal returns are largely confined to the period from 1975 to 1987. When long-run performance is examined following the ex or effective date of stock splits, abnormal returns are insignificant, except for equally weighted portfolios during 1975 to 1987. Further analysis documents that the equally weighted long-run abnormal performance during 1975 to 1987 is strongly correlated with unexpected decreases in post-split systematic risk.


Measurement Effects and the Variance of Returns after Stock Splits and Stock Dividends

Measurement Effects and the Variance of Returns after Stock Splits and Stock Dividends
Author: Jennifer L. Koski
Publisher:
Total Pages:
Release: 1998
Genre:
ISBN:

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This paper examines the relation between two institutional factors affecting stock price measurement, the bid-ask spread and price discreteness, and the increase in return variance after ex-dates of stock splits and stock dividends. Controlling for these measurement effects, the variance of daily returns still increases significantly after stock distributions. The variance of weekly returns also increases significantly, and the variance of returns for a control sample of nonsplitting firms shows no significant increase. Variance ratio tests show that bid-ask errors are small for NYSE stocks that split and therefore could not account for the large increase in variance. Price discreteness and the bid-ask spread do not explain increased variance after stock distributions.


Long-Run Performance after Stock Splits

Long-Run Performance after Stock Splits
Author: Jinho Byun
Publisher:
Total Pages:
Release: 2003
Genre:
ISBN:

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We measure the postsplit performance of 12,747 stock splits from 1927 to 1996 using two methods to measure abnormal returns: size and book-to-market reference portfolios with bootstrapping, and calendar-time abnormal returns combined with factor models. Between 1927 and 1996, neither method applied to splits 25 percent or larger finds performance significantly different from zero. Over selected subperiods, subsamples of 2-1 splits restricted by book-to-market availability requirements display positive abnormal returns using some methods. However, these samples show small or negligible abnormal returns using the calendar-time method. Overall, the stock split evidence against market efficiency is neither pervasive nor compelling.


Nonparametric Statistical Methods

Nonparametric Statistical Methods
Author: Myles Hollander
Publisher: John Wiley & Sons
Total Pages: 872
Release: 2013-11-25
Genre: Mathematics
ISBN: 1118553292

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Praise for the Second Edition “This book should be an essential part of the personal library of every practicing statistician.”—Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given situation. Written by leading statisticians, Nonparametric Statistical Methods, Third Edition provides readers with crucial nonparametric techniques in a variety of settings, emphasizing the assumptions underlying the methods. The book provides an extensive array of examples that clearly illustrate how to use nonparametric approaches for handling one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. In addition, the Third Edition features: The use of the freely available R software to aid in computation and simulation, including many new R programs written explicitly for this new edition New chapters that address density estimation, wavelets, smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science, astronomy, biology, criminology, education, engineering, environmental science, geology, home economics, medicine, oceanography, physics, psychology, sociology, and space science Nonparametric Statistical Methods, Third Edition is an excellent reference for applied statisticians and practitioners who seek a review of nonparametric methods and their relevant applications. The book is also an ideal textbook for upper-undergraduate and first-year graduate courses in applied nonparametric statistics.