4 resultados para Abnormal trading volume
em Brock University, Canada
Resumo:
This thesis examines the impact of a corporate name change on stock price and trading volume of Canadian companies around the announcement date, the approval date, and the adoption date over the time period from 1997 to 2011. Name changes are classified into six categories: major and minor, structural and pure, diversified and focused, accompanied with a change in ticker symbol and without a change in ticker symbol, “Gold” name addition and deletion, and different reasons for name changes (e.g., merger and acquisition, change of structure, change of strategy, and better image). The thesis uses the standard event study methodology to perform abnormal return and trading volume analyses. In addition, regression analysis is employed to examine which type of a name change has the largest impact on cumulative abnormal returns. Sample stocks exhibit a significant positive abnormal return one-day prior to the approval day and one day after the adoption date. Around the approval date we observe significant abnormal returns for stocks with a structural name change. On the day after the adoption date we document abnormal returns for stocks with major, minor, structural, pure, focused, and ticker symbol name changes. If a merger or acquisition is the reason for a name change, companies tend to experience a significant positive abnormal return one-day before the approval date and on the adoption date. If a change of structure is the reason for a name change, companies exhibit a significant positive abnormal return on the approval date and a significant negative abnormal return on the adoption date. In case of a change of strategy as the reason for a name change, companies show a significant negative abnormal return around the approval date and a significant positive abnormal return around the adoption date.
Resumo:
We examine stock market reactions around the Nasdaq-100 Index reconstitutions. We find a symmetric and transitory price response accompanied by a significant increase in trading volume on the effective date. Firms added to the Nasdaq-100 Index experience significant increases in institutional ownership, the number of market makers, and the number of shareholders. In contrast, firms removed from the index show significant decreases in the number of institutional shareholders. Additions to the Nasdaq-100 Index also show significant increases in four liquidity measures, whereas deletions demonstrate significant decreases in two liquidity measures. These changes in liquidity are related to the abnormal return on the announcement day. Taken together, the results suggest support for the price pressure, liquidity, and investor awareness hypotheses.
Resumo:
Margin policy is used by regulators for the purpose of inhibiting exceSSIve volatility and stabilizing the stock market in the long run. The effect of this policy on the stock market is widely tested empirically. However, most prior studies are limited in the sense that they investigate the margin requirement for the overall stock market rather than for individual stocks, and the time periods examined are confined to the pre-1974 period as no change in the margin requirement occurred post-1974 in the U.S. This thesis intends to address the above limitations by providing a direct examination of the effect of margin requirement on return, volume, and volatility of individual companies and by using more recent data in the Canadian stock market. Using the methodologies of variance ratio test and event study with conditional volatility (EGARCH) model, we find no convincing evidence that change in margin requirement affects subsequent stock return volatility. We also find similar results for returns and trading volume. These empirical findings lead us to conclude that the use of margin policy by regulators fails to achieve the goal of inhibiting speculating activities and stabilizing volatility.
Resumo:
We assess the predictive ability of three VPIN metrics on the basis of two highly volatile market events of China, and examine the association between VPIN and toxic-induced volatility through conditional probability analysis and multiple regression. We examine the dynamic relationship on VPIN and high-frequency liquidity using Vector Auto-Regression models, Granger Causality tests, and impulse response analysis. Our results suggest that Bulk Volume VPIN has the best risk-warning effect among major VPIN metrics. VPIN has a positive association with market volatility induced by toxic information flow. Most importantly, we document a positive feedback effect between VPIN and high-frequency liquidity, where a negative liquidity shock boosts up VPIN, which, in turn, leads to further liquidity drain. Our study provides empirical evidence that reflects an intrinsic game between informed traders and market makers when facing toxic information in the high-frequency trading world.