市场在并购,股息支付和股票回购事件中是否有偏见?
1Ho Chi Minh University of Banking, Ho Chi Minh City, Viet Nam.
Heliyon
|April 22, 2024
概括
市场对企业金融事件 (如并购,股票回购和股息) 的反应往往是有偏见的. 信息泄露发生在公告之前,市场准确性因事件类型而异,影响过剩资本分配的执行决策.
科学领域:
- 企业金融公司财务
- 市场效率 市场效率
- 事件研究方法论 事件研究方法论
背景情况:
- 资本过剩的公司面临着战略选择:股息,股票回购或并购 (M&A).
- 了解市场对这些金融事件的反应对于最佳的资本配置和股东价值至关重要.
- 之前的研究已经探讨了市场反应,但需要对不同类型的事件和随着时间的推移进行细致的观察.
研究的目的:
- 调查市场偏见对并购,股票回购和股息支付事件的反应.
- 分析这些公司财务决策在官方公布之前的信息泄露情况.
- 评估市场反应的准确性,通过检查公司在事件发生三年后的业绩.
主要方法:
- 在事件研究方法中使用差异差异方法.
- 采用独特的,手动收集的数据集进行实证分析.
- 检查了市场反应和信息泄露在并购,股票回购和股息支付事件.
主要成果:
- 在所有被调查事件的官方公布前一天,观察到信息泄露.
- 市场反应对于并购和股票股息支付有偏见,但对于现金股息支付和股票回购而言是准确的.
- 股票回购引起了最强烈和最长的市场反应;股票股息最弱;现金股息最短;收购对收购者股票产生了负面影响,但对目标股票产生了积极影响.
结论:
- 该研究提供了市场对企业财务信息反应模式的经验证据.
- 市场反应表现出不同程度的偏见和准确性,取决于金融事件.
- 调查结果支持首席执行官在关于过剩现金流分配方面做出更明智的决策.
更多相关视频
06:39Electroencephalographic, Heart Rate, and Galvanic Skin Response Assessment for an Advertising Perception Study: Application to Antismoking Public Service Announcements
Published on: August 28, 2017
14.3K
08:24The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
Published on: August 25, 2023
695
相关概念视频
Bias
4.2K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
4.2K
Bias in Epidemiological Studies
254
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
254
Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
Confirmation Biases
5.5K
The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
5.5K
Weighted Mean
5.1K
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
5.1K
The Anchoring-and-Adjustment Heuristic
7.2K
In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...
7.2K
