Dynamic focus strategies for electronic trade execution in limit order markets

Jiaqi, W; Chengqi, Z

Dynamic focus strategies for electronic trade execution in limit order markets

Jiaqi, W Chengqi, Z

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Publication Type:: Conference Proceeding
Citation:: CEC/EEE 2006 Joint Conferences, 2006, 2006
Issue Date:: 2006-12-01

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Field	Value	Language
dc.contributor.author	Jiaqi, W	en_US
dc.contributor.author	Chengqi, Z https://orcid.org/0000-0001-5715-7154	en_US
dc.date.issued	2006-12-01	en_US
dc.identifier.citation	CEC/EEE 2006 Joint Conferences, 2006, 2006	en_US
dc.identifier.isbn	0769525113	en_US
dc.identifier.isbn	9780769525112	en_US
dc.identifier.uri	http://hdl.handle.net/10453/12618
dc.description.abstract	Trade execution has attracted lots of attention from academia and financial industry due to its significant impact on investment return. Recently, limit order strategies for trade execution were backtested on historical order/trade data and dynamic price adjustment was proposed to respond state variables in execution. This paper emphasizes the effect of dynamic volume adjustment on limit order strategies and proposes dynamic focus (DF) strategies, which incorporate a series of market orders of different volume into the limit order strategy and dynamically adjusts their volume by monitoring state variables such as inventory and order book imbalance in real-time. The sigmoid function is suggested as the quantitative model to represent the relationship between the state variables and the volume to be adjusted. The empirical results on historical order/trade data of the Australian Stock Exchange show that the DF strategy can outperform the limit order strategy, which does not adopt dynamic volume adjustment. © 2006 IEEE.	en_US
dc.relation.ispartof	CEC/EEE 2006 Joint Conferences	en_US
dc.relation.isbasedon	10.1109/CEC-EEE.2006.36	en_US
dc.title	Dynamic focus strategies for electronic trade execution in limit order markets	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2006	en_US
utslib.for	0806 Information Systems	en_US
dc.location.activity	San Francisco, California, USA	en_US
dc.location.activity	Maui, USA
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (International)
pubs.organisational-group	/University of Technology Sydney/Strength - ACRI - Australia China Relations Institute
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	2006	en_US

Abstract:

Trade execution has attracted lots of attention from academia and financial industry due to its significant impact on investment return. Recently, limit order strategies for trade execution were backtested on historical order/trade data and dynamic price adjustment was proposed to respond state variables in execution. This paper emphasizes the effect of dynamic volume adjustment on limit order strategies and proposes dynamic focus (DF) strategies, which incorporate a series of market orders of different volume into the limit order strategy and dynamically adjusts their volume by monitoring state variables such as inventory and order book imbalance in real-time. The sigmoid function is suggested as the quantitative model to represent the relationship between the state variables and the volume to be adjusted. The empirical results on historical order/trade data of the Australian Stock Exchange show that the DF strategy can outperform the limit order strategy, which does not adopt dynamic volume adjustment. © 2006 IEEE.

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http://hdl.handle.net/10453/12618