Financial time series representation using multiresolution important point retrieval method
Financial time series analysis usually conducts by determining the series important points. These important points which are the peaks and the dips indicate the affecting of some important factors or events which are available both internal factors and external factors. The peak and the dip points o...
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| Language: | en |
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Penerbit UTM Press
2008
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| Online Access: | http://eprints.utm.my/10370/1/ChaliawPhetking2008_FinancialTimeSeriesRepresentationUsing.pdf http://eprints.utm.my/10370/ |
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| author | Phetking, Chaliaw Md. Sap, Mohd. Noor Selamat, Ali |
| author_facet | Phetking, Chaliaw Md. Sap, Mohd. Noor Selamat, Ali |
| author_sort | Phetking, Chaliaw |
| building | UTM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Financial time series analysis usually conducts by determining the series important points. These important points which are the peaks and the dips indicate the affecting of some important factors or events which are available both internal factors and external factors. The peak and the dip points of the series may appear frequently in multiresolution over time. However, to manipulate financial time series, researchers usually decrease this complexity of time series in their techniques. Consequently, transfonning the time series into another easily understanding representation is usually considered as an appropriate approach. In this paper, we propose a multiresolution important point retrieval method for financial time series representation. The idea of the method is based on finding the most important points in multiresolution. These retrieved important points are recorded in each resolution. The collected important points are used to construct the TS-binary search tree. From the TS-binary search tree, the application of time series segmentation is conducted. The experimental results show that the TS-binary search tree representation for financial time series exhibits different performance in different number of cutting points, however, in the empirical results, the number of cutting points which are larger than 12 points show the better results. |
| format | Article |
| id | my.utm.eprints-10370 |
| institution | Universiti Teknologi Malaysia |
| language | en |
| publishDate | 2008 |
| publisher | Penerbit UTM Press |
| record_format | eprints |
| spelling | my.utm.eprints-103702017-11-01T04:17:24Z http://eprints.utm.my/10370/ Financial time series representation using multiresolution important point retrieval method Phetking, Chaliaw Md. Sap, Mohd. Noor Selamat, Ali QA75 Electronic computers. Computer science Financial time series analysis usually conducts by determining the series important points. These important points which are the peaks and the dips indicate the affecting of some important factors or events which are available both internal factors and external factors. The peak and the dip points of the series may appear frequently in multiresolution over time. However, to manipulate financial time series, researchers usually decrease this complexity of time series in their techniques. Consequently, transfonning the time series into another easily understanding representation is usually considered as an appropriate approach. In this paper, we propose a multiresolution important point retrieval method for financial time series representation. The idea of the method is based on finding the most important points in multiresolution. These retrieved important points are recorded in each resolution. The collected important points are used to construct the TS-binary search tree. From the TS-binary search tree, the application of time series segmentation is conducted. The experimental results show that the TS-binary search tree representation for financial time series exhibits different performance in different number of cutting points, however, in the empirical results, the number of cutting points which are larger than 12 points show the better results. Penerbit UTM Press 2008-06 Article PeerReviewed application/pdf en http://eprints.utm.my/10370/1/ChaliawPhetking2008_FinancialTimeSeriesRepresentationUsing.pdf Phetking, Chaliaw and Md. Sap, Mohd. Noor and Selamat, Ali (2008) Financial time series representation using multiresolution important point retrieval method. Jurnal Teknologi Maklumat, 20 (1). pp. 106-119. ISSN 0128-3790 |
| spellingShingle | QA75 Electronic computers. Computer science Phetking, Chaliaw Md. Sap, Mohd. Noor Selamat, Ali Financial time series representation using multiresolution important point retrieval method |
| title | Financial time series representation using multiresolution important point retrieval method |
| title_full | Financial time series representation using multiresolution important point retrieval method |
| title_fullStr | Financial time series representation using multiresolution important point retrieval method |
| title_full_unstemmed | Financial time series representation using multiresolution important point retrieval method |
| title_short | Financial time series representation using multiresolution important point retrieval method |
| title_sort | financial time series representation using multiresolution important point retrieval method |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.utm.my/10370/1/ChaliawPhetking2008_FinancialTimeSeriesRepresentationUsing.pdf http://eprints.utm.my/10370/ |
| url_provider | http://eprints.utm.my/ |