Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/68496
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dc.contributor.authorZhang, Xiaokun-
dc.date.accessioned2016-05-26T04:56:10Z-
dc.date.available2016-05-26T04:56:10Z-
dc.date.issued2016-
dc.identifier.urihttp://hdl.handle.net/10356/68496-
dc.description.abstractThe main purpose of the work presented in this report is to investigate if and how fuzzy neural networks (FNNs) can be used to forecast financial time series (i.e. the price curve of financial securities). Several researchers have already performed similar investigations, however there are some novel features of the approach used in this thesis that separates it from the bulk of the existing research. Probably the most important of these differences is that the empirical tests in this thesis were performed with intraday trade data, whereas the previous research has generally been carried out with only daily data (i.e. one data value for each day). So while the existing research has been restricted to mid-term and long-term forecasting, this thesis is unique in that it also investigates the viability of applying FNNs to short-term intraday forecasting.en_US
dc.format.extent57 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University-
dc.subjectDRNTU::Engineering::Computer science and engineering::Computer systems organization::Special-purpose and application-based systemsen_US
dc.titleIntraday trading system based on fuzzy neural network modelingen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorQuek Hiok Chaien_US
dc.contributor.schoolSchool of Computer Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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