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  • 1
    UID:
    (DE-627)1791400094
    Format: 1 Online-Ressource (17 p)
    Content: This study focuses on the rule prohibiting insider trading in securities law and its effectiveness. In theory, a pending M&A activity has great potential to induce substantial price movement in the public market after its announcement. However, a prohibition of insider trading prevents people who have the knowledge about a pending M&A from using this information to garner the price difference, when a latter announcement leads to increasing public price. In this view, in an ideal world, when a prohibition of insider trading is in place and taking its full effect, the price should only start to move toward the target price right after the news of M&A activity is publicly announced. Conversely, if the stock price starts to reflect the target price before its public announcement, that implies a likely leak of private information and a failure of insider trading prohibition rule. In other words, through observing the price movements before and after the mergers and acquisitions event samples, we can produce an approximation of the effectiveness of the insider trading law in place. This paper examines M&A data in Taiwan, collecting from the disclosure system administered by Taiwan Financial Supervisory Commission from 2004 to 2016, as evidence to test the actual implementation of insider trading law in Taiwan and how forceful it is. The pattern of information leakage, when observed, provides a valuable understanding for the law enforcement department and its improvement. This result of empirical investigation, and the insight it provides, are particularly important because (1) insider trading is considered to be highly detrimental to the securities market and investor confidence, and (2) insider trading activities are not directly observable due to the secretive way the related information is exchanged and thus hard to gauge its level of actual occurrence
    Note: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments February 13, 2017 erstellt
    Language: English
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