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DC FieldValueLanguage
dc.contributorDepartment of Computingen_US
dc.creatorLui, Hing-nin.-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/5397-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleForecasting near-future Hang Sang [i.e. Seng] Index with data mining techniquesen_US
dcterms.abstractThis paper is to investigate ways to use data mining methods and neural networks to predict the movement of an index for the near future. Here, the near future is defined as the future in the fifteen minutes. Daily movement of stock prices and indexes are predicted as a complicated real-world problem, factors such as the nominal value movements of related stocks and indexes are taking into account. A comparison on the results derived from data mining and neural networks are plotted among all the selected stocks and indexes. The data set for this research is collected through a sponsored company with a direct data-feed line from the Hong Kong Stock Exchange. Detailed data collection is down to a minute. The use of data mining and neural networks is shown to be effective experimentally: the prediction accuracies for both approaches are as good as 97% and 99% respectively for most of the indexes and selected stocks and there is 99% accuracy by using Neural Networks for the prediction of HSI for the next 15 minutes. Finally, the system is proved to be accurate for the time interval up to 45 minutes which may imply the present movement of index having an influence for 45 minutes long.en_US
dcterms.alternativeForecasting near-future Hang Seng Index with data mining techniques-
dcterms.extenti, 91, [20] leaves : col. ill. ; 30 cm.en_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2002en_US
dcterms.educationalLevelAll Masteren_US
dcterms.educationalLevelM.Sc.en_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.LCSHStock price indexes -- China -- Hong Kong -- Forecastingen_US
dcterms.LCSHStock index futures -- China -- Hong Kong -- Forecastingen_US
dcterms.LCSHData miningen_US
dcterms.accessRightsrestricted accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/5397