Genetic algorithms for robust optimization in financial applications

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dc.contributor.author Lin, L
dc.contributor.author Cao, L
dc.contributor.author Zhang, C
dc.date.accessioned 2009-11-09T02:43:47Z
dc.date.issued 2005
dc.identifier.citation Proceedings of the IASTED International Conference on Computational Intelligence, 2005, 2005 pp. 387 - 391
dc.identifier.isbn 0889864810
dc.identifier.isbn 9780889864818
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/1683
dc.description.abstract In stock market or other financial market systems, the technical trading rules are used widely to generate buy and sell alert signals. In each rule, there are many parameters. The users often want to get the best signal series from the in-sample sets, (Here, the best means they can get the most profit, return or Sharpe Ratio, etc), but the best one will not be the best in the out-of-sample sets. Sometimes, it does not work any more. In this paper, the authors set the parameters a sub-range value instead of a single value. In the sub-range, every value will give a better prediction in the out-of-sample sets. The improved result is robust and has a better performance in experience.
dc.title Genetic algorithms for robust optimization in financial applications
dc.type Conference Proceeding
dc.parent Proceedings of the IASTED International Conference on Computational Intelligence
dc.journal.volume 2005
dc.journal.number en_US
dc.publocation Calgary, Canada en_US
dc.identifier.startpage 387 en_US
dc.identifier.endpage 391 en_US
dc.cauo.name FEIT.School of Systems, Management and Leadership en_US
dc.conference Verified OK en_US
dc.conference.location Calgary, Canada en_US
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 011221
dc.personcode 034535
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.custom IASTED International Conference on Computational Intelligence en_US
dc.date.activity 20050704 en_US
dc.location.activity Calgary, Canada en_US
dc.description.keywords Stock Market Data Mining, Technical Trading Rules, Genetic algorithms, Robust, Optimization en_US
dc.description.keywords Genetic algorithms
dc.description.keywords Optimization
dc.description.keywords Robust
dc.description.keywords Stock market data mining
dc.description.keywords Technical trading rules
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 Open Access
utslib.copyright.date 2015-04-15 12:23:47.074767+10
utslib.collection.history General (ID: 2)
utslib.collection.history General Collection (ID: 346) [2015-05-15T14:11:59+10:00]
utslib.collection.history Uncategorised (ID: 363)


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