在完全競爭市場，交易訊息應是對稱透明化。但在現實世界中，資訊並沒有達到雙面均衡。企業併購即為訊息不對稱的一個很好例子。企業併購宣告後，大眾投資人對被收購公司信心大增，股價大漲。因此在宣告併購前掌握訊息，將有套利機會。Meulbroek在1992年提出，美國違法內線交易事件，併購佔極大的比例。而避險基金套利型策略中，也有風險併購套利(併購宣告前，買進將被收購的公司，賣出購併者)。因此公司併購宣告前，是否有內部消息投資者已在市場上交易。
Easley, Hvidkjaer, and O’Hara (2002)提出市場微結構模型，利用交易與報價資料，算出訊息交易比例(PIN, the probability of information-based trading)，估計是否有投資者有掌握內部訊息。在市場微結構模型，需有買單跟賣單資料，估計訊息交易比例參數。採用Lee and Ready (1991)提出利用報價資料，分辨買賣單。Lee and Ready方法，在2002年Declerck驗證只有4.5%分類失誤，因此估出的訊息交易比例受到分類失誤的影響很小。
本論文採用Easley, Hvidkjaer, and O’Hara (2002)提出市場微結構模型，利用收購公司在併購宣告與目標公司下市日前後交易與報價資料，算出訊息交易比例(PIN, the probability of information-based trading)，藉此看出，是否有不正常的交易活動，隱含內部交易訊息。
實證結果發現，併購事件中的買方公司─併購公司，在宣告日前並沒有私有訊息擁有者進入市場交易，而對於一般認為以現金為併購手段所帶來的財富效果，在研究中並沒有發現此效果。而目標公司在宣告日前，確有私有訊息擁有者進入市場交易，進入時間點在宣告日前三個月。。

In complete market, the information is symmetry. But in the real world, the information is usually asymmetric. M&A is a good example of information asymmetry. After M&A is announced, stock price of the target company usually increases significantly. If the investors acquire private information before the M&A announcement date, they can profit from the private information. The M&A arbitrage hedge fund implements the trading strategy of buying the potential target company and at the same time selling the acquiring firms prior to the M&A announcement date. Meulborek (1992) analyzes that the illegal inside trading cases in America are most M&A.

Easley, Hvidkjaer, and O’Hara (2002) have established stock market microstructure model to infer the probability of information-based trading (PIN) from transaction and quote data. We employ Lee and Ready (1991) to distinguish between buy-order-driven transactions and sale-order-driven transactions.

The paper applies the microstructure model established by Easley, Hvidkjaer, and O’Hara (2002) to infer the probability of information-based trading before the announcement of M&A. The purpose of this paper is we aim to investigate whether there are, if any, information-based trading prior to the announcement of M&A.

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