日內報酬與買賣單不對稱之動態關係

Dynamic Relation between Intraday Return and Order Imbalance

黃漢青(Han-Ching Huang)

指導教授 ： 蘇永成

國立臺灣大學/管理學院/財務金融學研究所/博士(2006年)

https://doi.org/10.6342/NTU.2006.01689

摘要

第一章
在不同市場期間下，日內股票報酬與買賣單不對稱之隨時間變異GARCH與網狀因果關係

摘要
本文以NASDAQ100指數成份股的日內資料來檢視在不同市場期間下，股票報酬和買賣單不對稱之關係。我們建立一個依據Llorente, Michaely, Sarr, and Wang (2002)動態報酬與成交量關係之隨時間變異GARCH模型。結果顯示在所有市場期間下，當期買賣單不對稱對報酬之影響大體上符合存貨效果與價格形成之資訊不對稱效果。以Llorente, et al. (2002)之觀點，投機動機之交易遠多於避險動機之交易。當期買賣單不對稱對報酬之效果，在所有效果中是最大的。我們發現在15分鐘時間間隔之效果，基本上均顯著地大於90秒鐘時間間隔之效果。較大的公司規模常伴隨著較低的股票報酬。此外，本研究採用多假說檢定來探究買賣單不對稱與股票報酬間之特定因果關係。雖然文獻多認為在採日資料下，可用買賣單不對稱來預測未來股價，但以90秒為單位之日內資料來分析的結果顯示並非總是如此。當公司資本額愈小時，顯示買賣單不對稱對股票報酬單向影響關係的公司之比例愈大。在股市呈現上漲趨勢時，顯示買賣單不對稱對股票報酬單向影響關係的公司之比例，比股市呈現下跌趨勢時大。

第二章
NASDAQ最大漲幅投機型個股之日內股票報酬與買賣單不對稱之動態因果關係

摘要
本文以特定事件之資料來探索日內股票報酬和買賣單不對稱之條件與非條件動態因果關係。我們以一迴歸模型來檢視檢視NASDAQ漲幅最大投機股的股票報酬與買賣單不對稱之日內行為。此外，本研究採用多假說檢定方法，即網狀因果關係法，來探究買賣單不對稱與股票報酬間之特定因果關係。我們發現買賣單不對稱確實比交易量更能傳遞更多的訊息。當檢視三個日內期間，我們發現當期報酬-買賣單不對稱的關係於第三期最顯著，表示訊息交易通常發生在下午。以公司資本額分層的結果顯示公司資本額與當期報酬-買賣單不對稱效果有負向關係。公司資本額對當期報酬-買賣單不對稱效果之影響比前三個月之日平均交易量之影響來得大。此外，以交易量分層的結果顯示在前三個月之日平均交易量較低的股票之範疇下，買賣單不對稱是預測未來報酬的較佳指標。

第三章
NASDAQ 100指數成分股的日內股票報酬與買賣單不對稱之隨時間變異GARCH與網狀因果關係

摘要
我們依據Llorente, Michaely, Sarr, 與 Wang (2002) 和Chordia與Subrahmanyam (2004)之股票報酬與交易量、買賣單不對稱關係，建立GARCH (1,1)與OLS模型，來檢視NASDAQ100指數成份股之日內股票報酬和買賣單不對稱之關係。我們發現當期報酬-買賣單不對稱效果在每一個模型均為正且顯著。此外，當交易單數為中單的效果均比其他單數來得大。當檢視三個日內期間，我們發現當期報酬-買賣單不對稱的關係於第二期最顯著，表示訊息交易通常發生在中午期間。就資訊不對稱之代理變數而言，交易價差比公司資本額、交易量來得好。此外，本研究採用多假說檢定方法，即網狀因果關係法，來探究買賣單不對稱與股票報酬間之特定因果關係。結果顯示在公司資本額較低及交易價差較大股票之範疇下，買賣單不對稱是預測未來報酬的較佳指標。

關鍵字

買賣單不均衡 ； 動態價量關係 ； 資訊不對稱 ； 多假說因果關係之檢定方法 ； 報酬-買賣單不對稱效果 ； 最大漲幅

並列摘要

Chapter 1
Time Varing GARCH and Nested Causality Relations between Intraday Stock Return and Order Imbalance in Different Market Periods

Abstract
This paper examines the relation between stock return and order imbalance by intraday data for a sample of NASDAQ-100 component stocks in different market periods. We develop a time varing GARCH model that depends on the dynamic return–volume relation of individual stock on Llorente, Michaely, Sarr, and Wang (2002). Our results show that the contemporaneous order imbalance-return effect is in a manner consistent with both the inventory and asymmetry information effects of price formation in all the market periods. Moreover, speculative trades dominate hedging trade in the light of Llorente, et al. (2002). The influence of contemporaneous order imbalance-return effect is the greatest among the effects. We find that all the effects in the 15-minute time interval are virtually significantly greater than those in the 90-second time interval. Higher firm size is associated with the lower stock returns. Moreover, we adopt a systematic multiple hypotheses testing method to determine a specific causal relationship between order imbalances and stock returns. Our results show that order imbalance is not always a good indicator for predicting future returns in the 90-second time interval, although many articles document that future daily returns could be predicted by daily order imbalances. Larger percentage of firms exhibiting a unidirectional relationship from order imbalances to returns is associated with smaller firm size. The unidirectional relationship from order imbalances to returns in a bull market period is higher than that in a bear market period.

Chapter 2
Dynamic Causality between Intraday Return and Order Imbalance in NASDAQ Speculative Top Gainers

Abstract
This study explores dynamic conditional and unconditional causality relations between intraday return and order imbalance on extraordinary events. We examine intraday behavior of NASDAQ speculative top gainers. In this study, we employ a regression model to examine intraday return-order imbalance behaviors. Moreover, we introduce a multiple hypotheses testing method, namely a nested causality, to identify the dynamic relationship between intraday returns and order imbalances. We find order imbalance convey more information than trading volume does. While examining three intraday time regimes, we find the contemporaneous order imbalance-return effect is significant in the third sub-period, which implies that informed trading take place in the afternoon. The size-stratified results show there is a negative relation between firm size and the order imbalance–return effect. The impact of the firm size on the order imbalance–return effect is stronger than that of the trading volume. Moreover, the volume-stratified results suggest that order imbalance be a better return predictor in small trading volume quartile.

Chapter 3
Time Varing GARCH and Nested Causality Relations between Intraday Return and Order Imbalance in NASDAQ-100 Component Stocks

Abstract
In this study, we employ the GARCH (1,1) and OLS models based on the argument of return-volume and return-order imbalance relations of individual stocks (Llorente, Michaely, Sarr, and Wang (2002); Chordia and Subrahmanyam (2004)) to examine the relation between return and order imbalance in the NASDAQ-100 component stocks. The contemporaneous order imbalance-return effects are positive and significant in every model. Besides, the effect in the medium size is more significant than that in other size categories. The contemporaneous order imbalance-return effect is the greatest in the sub-period 2, implying that informed trading often take place from 11:30 A.M. to 2:00 P.M. Spread is superior to firm size and trading volume as a proxy for information asymmetry. Moreover, we introduce a multiple hypotheses testing method for identifying the dynamic relationship between returns and order imbalances. The order imbalance could be a better indicator for predicting returns in smaller firm size and larger spread quartiles.

並列關鍵字

order imbalance ； dynamic return–volume relation ； information asymmetry ； multiple hypotheses nested causality testing method ； return–order imbalance relation ； top gainer

參考文獻

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Chordia, T. and A. Subrahmanyam, 2004, Order imbalances and individual stock returns: Theory and evidence, Journal of Financial Economics 72, 485-518.

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