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在美中概股私有化退市实证分析
An Empirical Research on The Delisting As “Going Private” of US-Listed Chinese Companies
【作者】 李波;
【导师】 李春红;
【作者基本信息】 重庆大学 , 金融学, 2016, 硕士
【摘要】 从20世纪90年代开始,在“低门槛、宽管制”的特点吸引下,大量良莠不齐的中国企业通过IPO或反向收购先后在美国资本市场完成了上市,它们被我们称为中概股,尽管在当时的“中国模式”的光环下受到了投资者的热烈追捧,却也埋下了诸多隐患。2010年前后,由于做空机构的攻击等原因,一些中概股暴露出了财务作假、公司治理差等问题,导致大量中概股不但价值被严重低估,更招致了美国证监会的严格审查。在此背景下,2010年开始中概股掀起了退市潮,其中既有被动退市,也有私有化主动退市的企业,时至今日这波退市潮仍然没有消退。本文在以往学者对于中外上市公司私有化研究成果的基础上,利用2013年到2015年间启动私有化的在美中概股作为样本,综合定性与定量的方法,从多个角度对其公告前和公告后的表现进行了考察,重点考察了私有化要约溢价的相关决定因素。文章先是从学界盛行的几个与私有化相关的理论入手,证明了尽管样本期间的公司从体量和行业构成上虽然与2013年之前私有化浪潮中的企业有所区别,其私有化动因却仍然是因为价值被长期低估。在确定了私有化的动因之后文章继续通过对多种假说的验证,创新性的选择了多个代理变量建立回归模型以分析中概股私有化要约溢价的影响因素,并得出了其主要影响因素是价值被低估程度以及企业现金保有率,至于公司治理情况和制度阻碍等因素并不显著影响样本企业的私有化要约溢价设定。接下来文章对私有化要约公布之后的“公告效应”进行了简略的分析,一方面证实了“公告效应”在研究对象中的显著存在,另一方面确认了溢价幅度是决定“公告效应”大小的重要影响因素,从而支持了私有化要约的价格可以很大程度上修正投资者对于股票价格预期的结论。在此基础上,文章进一步试图寻找能够可靠预测私有化完成概率的方式,通过涉及多种相关代理变量的二元逻辑回归,发现并不能通过所设定的相关变量可靠的预测私有化是否能顺利完成,尽管如此,文章对于可能影响私有化完成的各种因素也提供了一个概览,为后续的相关研究提供了一个方向。在样本数据的选择上,本文具备较好的时效性,并且其通过引入多个代理变量能够综合的验证各项假说的有效性,其不足在于样本仅覆盖纳斯达克市场和纽约交易所,涉及到的企业质量普遍比较优良,其私有化决策主观性因素比较多,因而得出的部分结论解释性有所欠缺。
【Abstract】 Since 1990 s, being attracted by the characteristics as ‘low barrier and loose regulation’, plenty of Chinese companies, good ones and bad ones,managed to list in the capital market of United States through IPO or reverse-merger, which was referred to as stocks with concepts of China. Though there was hot pursuit for these companies under the halo of ‘China mode’, some risks were neglected. Around 2010, some Chinese companies were revealed of accounting scandal and poor corporate governance, which caused server undervaluation and strict investigation by SEC. It was under this circumstance when Chinese companies rushed to get delisted, both voluntarily and involuntarily. The trend has not been turned until today. This article uses US-listed Chinese companies which announced to go private during 2013 and 2015, in both qualitative and quantitative ways to investigate their performance pre-and post-announcement, especially the determinants of premiums of the going private proposals.This article firstly digs into some major streams of theory concerning going private, and proves that, though there are some differences between the sample and those companies in the privatization trend before 2013, in aspects of market capitalization and industry structure, they still share the same motivation for going private: undervaluation. After verifying the motivation of going private, this article continues to test different hypothesis. It innovatively applies multiple proxy variables for regression model to analyze the determinants of premiums of Chinese companies’ going private transaction, and comes to the conclusion that the key factors determining premiums are the degree of undervaluation and cash holding percentage of those companies. Corporate governance and litigation risks don’t significantly influence the premiums of going private proposals. Then this article makes a brief analyze of ‘announcement effect’ after the going private proposal, to both conform the widely existence of ‘announcement effect’ and it being determined by the size of the premium, thus supporting that the going private proposal can make great correction of investor’s anticipation for the stock price.From here this article goes further to search for a reliable way to predict the success of going private proposal. It proposes a binary logic regression involving a couple of proxy variables but fails to make reliable prediction. Even though this, it takes an overview of some factors which may affect the success or not of the proposal thus to provide a suggestion for later research.The timeliness of data of the sample and multiple proxy variables are the main innovations of this article, while its shortcoming is that the sample excludes companies from OTCBB, so the conclusions may be lack of explanatory power to some extent.
【Key words】 Stocks with concepts of China; going private; premium; regression analysis;
- 【网络出版投稿人】 重庆大学 【网络出版年期】2017年 03期
- 【分类号】F832.51
- 【被引频次】20
- 【下载频次】743