Full metadata record
|dc.contributor||Department of Computing||en_US|
|dc.publisher||Hong Kong Polytechnic University||-|
|dc.rights||All rights reserved||en_US|
|dc.title||Prediction based on inter-relationship among different series of sequential events||en_US|
|dcterms.abstract||In the study of this dissertation, inter-relationship among sequential events in a number of series is dealt with. The testing data being in use are stock indexes of the following seven stock exchanges: - Hang Seng Index - NYSE composite - NASDAQ 100 - Dow Jones Industrials - FTSE 100 - NIKKEI 225 Stock Average - S&P 500 Composite This study is to find out the association between the fall / rise of an index and the previous fall / rise of different indexes. Using the discovered results, predictions of the fall / rise of upcoming indexes are performed based on the previous fall / rise of different indexes. For deciding whether an association exists between two events (fall / rise of an index), adjusted residual is employed. For better mining result, fuzzy data mining is performed. Fuzzification transformation is applied on the change ratio of the stock indexes. And, a Fuzzy Inference System is used for applying the mining results. Mamdani Inference System is employed in this study. For comparison on performance, Time Series Analysis is employed.||en_US|
|dcterms.extent||155 leaves : ill. ; 30 cm||en_US|
|dcterms.LCSH||Hong Kong Polytechnic University -- Dissertations||en_US|
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