亚洲新兴市场并购分析的模型选择

Q4 Economics, Econometrics and Finance
Jianyu Ma, Mingzhai Geng, Yun Chu
{"title":"亚洲新兴市场并购分析的模型选择","authors":"Jianyu Ma, Mingzhai Geng, Yun Chu","doi":"10.1504/IJRM.2016.076183","DOIUrl":null,"url":null,"abstract":"We extract a dataset of mergers and acquisitions from Asian emerging markets and examine the distribution of the stock returns for the acquiring firm and the corresponding market portfolio in each deal. Non-normal distribution of the returns appears in the test of most deals. We use two robust regressions and a nonparametric statistic test to examine the efficacy of the standard OLS market model. The traditional methods of measuring abnormal returns (ARs) around event windows may be flawed. The robust regressions, Huber regression M-estimator and bootstrapping quantile regression, provide better and higher estimation of abnormal returns.","PeriodicalId":39519,"journal":{"name":"International Journal of Revenue Management","volume":"9 1","pages":"40-56"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJRM.2016.076183","citationCount":"0","resultStr":"{\"title\":\"Model selection for merger and acquisition analysis in Asian emerging markets\",\"authors\":\"Jianyu Ma, Mingzhai Geng, Yun Chu\",\"doi\":\"10.1504/IJRM.2016.076183\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We extract a dataset of mergers and acquisitions from Asian emerging markets and examine the distribution of the stock returns for the acquiring firm and the corresponding market portfolio in each deal. Non-normal distribution of the returns appears in the test of most deals. We use two robust regressions and a nonparametric statistic test to examine the efficacy of the standard OLS market model. The traditional methods of measuring abnormal returns (ARs) around event windows may be flawed. The robust regressions, Huber regression M-estimator and bootstrapping quantile regression, provide better and higher estimation of abnormal returns.\",\"PeriodicalId\":39519,\"journal\":{\"name\":\"International Journal of Revenue Management\",\"volume\":\"9 1\",\"pages\":\"40-56\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1504/IJRM.2016.076183\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Revenue Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJRM.2016.076183\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Economics, Econometrics and Finance\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Revenue Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJRM.2016.076183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 0

摘要

我们提取了亚洲新兴市场的并购数据集,并检查了每笔交易中收购公司和相应市场投资组合的股票回报分布。在大多数交易的测试中,回报率呈现非正态分布。我们使用两个稳健回归和一个非参数统计检验来检验标准OLS市场模型的有效性。衡量事件窗期异常收益(ARs)的传统方法可能存在缺陷。稳健回归,Huber回归m估计和自举分位数回归,提供了更好和更高的异常收益估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model selection for merger and acquisition analysis in Asian emerging markets
We extract a dataset of mergers and acquisitions from Asian emerging markets and examine the distribution of the stock returns for the acquiring firm and the corresponding market portfolio in each deal. Non-normal distribution of the returns appears in the test of most deals. We use two robust regressions and a nonparametric statistic test to examine the efficacy of the standard OLS market model. The traditional methods of measuring abnormal returns (ARs) around event windows may be flawed. The robust regressions, Huber regression M-estimator and bootstrapping quantile regression, provide better and higher estimation of abnormal returns.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
International Journal of Revenue Management
International Journal of Revenue Management Economics, Econometrics and Finance-Economics and Econometrics
CiteScore
1.40
自引率
0.00%
发文量
4
期刊介绍: The IJRM is an interdisciplinary and refereed journal that provides authoritative sources of reference and an international forum in the field of revenue management. IJRM publishes well-written and academically rigorous manuscripts. Both theoretic development and applied research are welcome.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信