Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Computing | en_US |
| dc.creator | Lai, Leung | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/1207 | - |
| dc.language | English | 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.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2003 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.LCSH | Time-series analysis | en_US |
| dcterms.LCSH | Prediction theory | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b17452247.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 4.1 MB | Adobe PDF | View/Open |
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