Multiple duration analyses of dynamic limit order placement strategies and aggressiveness in a low-latency market environment
Anh Tu Le,
Thai-Ha Le,
Wai-Man Liu and
Kingsley Y. Fong
International Review of Financial Analysis, 2020, vol. 72, issue C
Abstract:
This study examines dynamic order placement strategies in a low-latency environment together with limit orders' aggressiveness by a new approach which utilises survival analysis with a multiple-spell duration model. Two samples are considered, including the period immediately followed Australian Securities Exchange (ASX)’s migration to Integrated Trading System (ITS) and the period subsequent to the launch of ASX Trade. We find the evidence supporting both the ‘cost of immediacy hypothesis' and the ‘chasing hypothesis' as in Hasbrouck and Saar (2009). Furthermore, several distinctions in the results are found between the samples of ITS period and ASX Trade period as well as between the samples of small-cap stocks and large-cap stocks. The findings of this study are beneficial not only for high-frequency traders in forming dynamic order placement strategies in a low-latency stock market environment, but also for market regulators in helping their attempt to improve regulations for stock exchanges.
Keywords: Tick-by-tick data; Dynamic order placement strategies; Survival analysis; Multiple-spell duration; Australian securities exchange (ASX) (search for similar items in EconPapers)
JEL-codes: C35 G15 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1057521920302192
Full text for ScienceDirect subscribers only
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:eee:finana:v:72:y:2020:i:c:s1057521920302192
DOI: 10.1016/j.irfa.2020.101575
Access Statistics for this article
International Review of Financial Analysis is currently edited by B.M. Lucey
More articles in International Review of Financial Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().