Dynamic Relation between Intraday Return and Order Imbalance
Date Issued
2006
Date
2006
Author(s)
Huang, Han-Ching
DOI
en-US
Abstract
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.
Subjects
買賣單不均衡
動態價量關係
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
order imbalance
dynamic return–volume relation
information asymmetry
multiple hypotheses nested causality testing method
return–order imbalance relation
top gainer
Type
thesis