Multi-strategy Integration for Actionable Trading Agents

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Show simple item record Cao, L
dc.contributor.editor Pericles, AM
dc.contributor.editor Longbing, C
dc.contributor.editor Vladimir, G
dc.contributor.editor Justin, Z 2009-11-09T05:35:36Z 2007-01
dc.identifier.citation Workshop on Agents & Data Mining Interaction (ADMI 2007), 2007, pp. 487 - 490
dc.identifier.isbn 0-7695-3028-1
dc.identifier.other E1 en_US
dc.description.abstract Trading agents are very useful for developing and back-testing quality trading strategies to support smart trading actions in the market. However, the existing trading agent research mainly focuses on simple and simulated strategies. As a result, there exists a big gap between academia and business when the developed trading agents are deployed in the real life. Therefore, the actionable capability of developed trading agents is often very limited. In this paper, we introduce approaches for optimizing and integrating multiple classes of strategies for trading agents. Five categories of trading strategies, including 36 types of trading strategies are trained and tested. A strategy integration and optimization approach is proposed to identify golden trading strategy in each category, and finally recommend positions associated with these golden strategies to trading agents. Test in five international markets on ten years of data respectively has shown that the final strategies recommended to trading agents can lead to high benefits while low costs. Concurrent execution of positions recommended by all golden strategies can greatly enhance performance.
dc.publisher IEEE Computer Soc
dc.relation.isbasedon 10.1109/WIIATW.2007.4427634
dc.title Multi-strategy Integration for Actionable Trading Agents
dc.type Conference Proceeding
dc.parent Workshop on Agents & Data Mining Interaction (ADMI 2007)
dc.journal.number en_US
dc.publocation Los Alamitos, USA en_US
dc.publocation Sydney, Australia
dc.identifier.startpage 487 en_US
dc.identifier.endpage 490 en_US QCIS Investment Core en_US
dc.conference Verified OK en_US
dc.conference Association of Architecture Schools of Australasia Annual Conference
dc.conference International Workshop on Agents and Data Mining Interaction
dc.conference.location San Jose, USA en_US
dc.for 080110 Simulation and Modelling
dc.personcode 034535
dc.percentage 100 en_US Simulation and Modelling en_US
dc.classification.type FOR-08 en_US
dc.custom International Workshop on Agents and Data Mining Interaction en_US 20071102 en_US 2007-09-27 2007-11-02
dc.location.activity San Jose, USA en_US
dc.location.activity UTS
dc.description.keywords trading; agent trading; strategy optimization ;integration en_US
dc.description.keywords dance, architecture, chance, multimedia, virtual technologies
dc.description.keywords trading
dc.description.keywords agent trading
dc.description.keywords strategy optimization
dc.description.keywords integration
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Strength - Quantum Computation and Intelligent Systems
utslib.copyright.status Closed Access 2015-04-15 12:17:09.805752+10
utslib.collection.history General Collection (ID: 346) [2015-05-15T14:12:20+10:00]
utslib.collection.history Closed (ID: 3)
utslib.collection.history Uncategorised (ID: 363)

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