若報價包含著資訊內涵，如同理論所闡釋的，則從每一報價就可能得到這些資訊。我們提供一個簡單的方法，可以從報價修正中萃取出私屬資訊成份與公共資訊成份。這種萃取的方式只需要知道前一次的交易方向。我們的實證結果，所估計的私屬資訊成份（公共資訊成份）與交易報酬有高度相關性，證明我們的估計能夠恰當的衡量資訊的內涵。甚且，相對於買賣價差的模式，我們證明買賣雙方的私屬資訊成份會隨著交易時間而趨於收斂。這現象與理論預期一致。而公共資訊成份也有類似私屬資訊成份遞減的模式，只是導致兩者的原因並不相同。

If a quote contains information as formulated in theory, then it is possible to elicit the information from each quote. We offer a simple method to extract the private and
the public information elements from the quote revision. The extraction is only required to know the trade direction of the previous trade. We then present empirical evidence that our estimates are informational pertinent by showing that they are highly correlated with transaction returns. Furthermore, contrasting to the pattern of the bid-ask spread, we show that the intraday private information elements are converging as trading progresses. This phenomenon is consistent to the prediction in the theory. Our public information elements also have a similar declining pattern as that of the private information element only with a different reason.

第一章 導論 1
第二章 報價分解的模型 3
2.1 模型的概念 4
2.2 模型設計 7
第三章 樣本資料 9
第四章 實證結果 10
4.1 交易報酬與私屬資訊及公共資訊的相關性 13
4.2 私屬資訊成份與公共資訊成份的日內模式 17
第五章 結論 22
參考文獻 24

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