併購事件宣告前後資訊環境的變化; The Change of the Information Environment around M&A Announcements

NCUIR > School of Management at National Central University > Graduate Institute of Finance > Electronic Thesis & Dissertation > Item 987654321/60809

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/60809

Title:	併購事件宣告前後資訊環境的變化;The Change of the Information Environment around M&A Announcements
Authors:	王泊元;Wang,Po-Yuan
Contributors:	財務金融學系
Keywords:	資訊交易機率;潛在資訊交易誤差修正係數;併購事件;PIN;ECIN;M&A
Date:	2013-07-23
Issue Date:	2013-08-22 12:03:37 (UTC+8)
Publisher:	國立中央大學
Abstract:	本文主要在分析併購事件宣告和資訊環境之間的關係。我使用由Easley et al. (2002)以及Hwang and Qian (2010)所發展出的PIN和ECIN指標來衡量資訊環境的變化。我參考Aktas et al. (2007)的研究方法，使用事件研究法並計算併購宣告日附近三個不同窗口的資訊風險指標。令人驚訝的是，我的結果發現不只是資訊交易者甚至連沒資訊交易者都在事件宣告前很長一段時間就進入市場，這暗示著資訊傳遞的速度非常快，以至於私有資訊很快就成為公開資訊。此外，從原樣本與配對樣本的比較結果來看，證據顯示資訊環境的變化與併購事件宣告並沒有關係。這個結果顯示美國股票市場是一個較有效率的市場，因此私有資訊迅速成為公開資訊，所以併購事件宣告對資訊環境沒有影響。最後，穩健性測試也證明我的結果並不受不同期間(或不同資料庫)影響。 This study analyzes the relationship between merger and acquisition (M&A) announcements and corporations' information environment, by adopting the PIN and ECIN measures developed by Easley et al. (2002) and Hwang and Qian (2010) to measure the diff erence in the information environment. Following the methodology of Aktas et al. (2007), I use an event study and calculate the information risk measures for three diff erent windows around M&A announcements. My results are surprising that not only informed traders but also uninformed traders enter into the market far before the announcements. These results imply that the speed of transferring information is so fast that private information soon becomes public information. Moreover, from the results of a comparison between the original and matching samples, the evidence shows that the change in information environment has nothing to do with the M&A announcements. This conclusion suggests that the U.S. stock market is very e fficient and that M&A announcements do not impact fi rms' information environment. Finally, a robustness check demonstrates that my results are robust and are not be aff ected by di fferent time periods (or databases).
Appears in Collections:	[Graduate Institute of Finance] Electronic Thesis & Dissertation

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