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The Market Response Of The Listet Companies' Penalty Notices

Posted on:2012-01-27Degree:MasterType:Thesis
Country:ChinaCandidate:Y RenFull Text:PDF
GTID:2189330335972375Subject:Accounting
Abstract/Summary:PDF Full Text Request
In recent years, cases of fraud by listed companies have been given the great concern from all aspects of society, including the public, investors, academics and regulators. As the highest authority of China's capital market regulator, the China Securities Regulatory Commission (CSRC) and the stock exchange under the leadership of the CSRC have announced the penalty notice which has become an important source of information for investment analysis and the focus that the parties pay close attention to.This paper has taken the listed companies which have been publicly punished by The China Securities Regulatory Commission and Shenzhen Stock Exchange and Shanghai Stock Exchange between the decade 2001-2010 as the sample, and has used the Cumulative Abnormal Return Method and multiple regression analysis to study the stock market response to the listed companies'punishment announcements, to test whether capital markets respond to announcements of punishment and whether penalties for different information notice will result in different market reaction. The research shows that this paper have come to in a relatively short period after the official penalty of regulators, especially after the publication of penalty notice within three days, the capital market reaction of the study samples and the control samples were significantly different, in other words, penalty notices have the information content. This paper also found that although in ten days to five days before the announcement, the penalty notice's market reaction of the financial fraud companies and the non-financial fraud companies were significantly different, but after the publication of announcements, the market reaction for both of them has no significant difference.
Keywords/Search Tags:penalty notices, market reaction, information content
PDF Full Text Request
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