蘇永成臺灣大學：財務金融學研究所林茹靖Lin, Ju-ChingJu-ChingLin2007-11-282018-07-092007-11-282018-07-092004http://ntur.lib.ntu.edu.tw//handle/246246/60800根據先前的研究指出，資訊擁有者為了增加獲利，會儘量利用中單來慢慢佈局，避免使用大單造成其它投資者跟進。本文試圖透過加總短時間內的中單來還原真實資訊，為了避免小單的干擾，只以可能具有資訊內涵的中單及大單作為樣本，將小單及短時間內被加的中單刪除。並以GARCH(1,1)模型檢驗價量關係，將同期、差一期的買賣超作為資訊不對稱的代理變數，研究在多頭、空頭與多空整合市場下，資訊不對稱對股價報酬率的影響。研究樣本為NASDAQ-100成份股在2002年12月2日至2003年1月6日每九十秒鐘的交易資料。 實證結果發現無論在何種市場下，同期的買賣超均與股票報酬率有顯著正向關係。差一期的結果則大部份呈現負相關，唯有多頭市場下的持續效果較佳。這表示當鉅額買賣超發生後，股價在下一期會稍微被拉回。 此外，本研究亦證實同期的買賣超對股價報酬的影響與公司大小成顯著負向關係，這支持了資訊不對稱之程度與公司大小有關，小公司較易因資訊不對稱而產生異常報酬。In this article, we investigate contemporaneous and lag-one return-order imbalance relation for large trading of individual NASDAQ-100 stocks in bull, bear, and consolidation markets. We use 90 seconds order imbalances as our explanatory variable in GARCH (1, 1) model. The sample period is from Dec 2, 2002 to Jan 6, 2003. We only focus on medium to large size order imbalances in order to minimize noise of small trades. We sum those medium trades within 4.5 minutes, and the summands and other small trades are thus censored. By summing these medium orders, we can recover information that camouflaged by informed traders. The major findings in this study are as follows. There is a contemporaneous significant positive relation between stock returns and order imbalances of each individual stock no matter what market it is. While in lag-one period, more than 86% of the coefficients are negative; the positive relation continuation occurs more possibly in bull market, which means there might exists a return reversal in the next period. We also find that the relation of contemporaneous coefficients and market capitalization is significantly negative. It implies that order imbalances have substantial impact on stock returns of smaller firms due to their severe information asymmetry.Chapter 1 Introduction 1 1.1 Motives and Purposes 1 1.2 Framework of the Thesis 4 Chapter 2 Literature Review 5 2.1 Trading Behavior under Information Asymmetry 5 2.2 Price-Volume Relations in Previous Studies 9 2.2.1 Price-Volume Relations 9 2.2.2 Relationship between Order Imbalance and Stock Returns 13 Chapter 3 Data 16 3.1 Data Sample and Sources 16 3.2 Descriptive Statistics 19 Chapter 4 Methodologies 21 4.1 Data Processing Methodologies 21 4.1.1 Trade Size Categories 21 4.1.2 Random Censoring 22 4.2 GARCH Model and Variables 24 Chapter 5 Empirical Results 26 5.1 Dynamic Return-Order Imbalance Relation 26 5.1.1 Contemporaneous Effect 26 5.1.2 Lag-One Effect 28 5.2 Relation between Coefficients and Firm Capitalization 29 Chapter 6 Conclusions 31 References 68629722 bytesapplication/pdfen-US資訊不對稱買賣超設限資料偽裝效果Order ImbalanceCamouflageCensoredthesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/60800/1/ntu-93-R91723029-1.pdf