Dynamic causality between intraday return and order imbalance in NASDAQ speculative top gainers

YongChern Su and HanChing Huang

Applied Financial Economics, 2008, vol. 18, issue 18, 1489-1499

Abstract: This study explores dynamic conditional and unconditional causality relations between intraday return and order imbalance on extraordinary events. We examine intraday behaviour of NASDAQ speculative top gainers. In this study, we employ a regression model to examine intraday return-order imbalance behaviours. 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 will 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 trading volume on the order imbalance-return effect is weaker than that of the firm size. Moreover, the volume-stratified results suggest that order imbalance be a better return predictor in small trading volume quartile and the order imbalance-based trading strategies are useful in the afternoon regime.

Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/09603100701720278 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:apfiec:v:18:y:2008:i:18:p:1489-1499

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAFE20

DOI: 10.1080/09603100701720278

Access Statistics for this article

Applied Financial Economics is currently edited by Anita Phillips

More articles in Applied Financial Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().