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Financial Time Series Forecasting Using Directed-Weighted Chunking SVMs
Joint Authors
Chang, Qing
Wang, Tingwei
Cai, Yongming
Song, Lei
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-24
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Support vector machines (SVMs) are a promising alternative to traditional regression estimation approaches.
But, when dealing with massive-scale data set, there exist many problems, such as the long training time and excessive demand of memory space.
So, the SVMs algorithm is not suitable to deal with financial time series data.
In order to solve these problems, directed-weighted chunking SVMs algorithm is proposed.
In this algorithm, the whole training data set is split into several chunks, and then the support vectors are obtained on each subset.
Furthermore, the weighted support vector regressions are calculated to obtain the forecast model on the new working data set.
Our directed-weighted chunking algorithm provides a new method of support vectors decomposing and combining according to the importance of chunks, which can improve the operation speed without reducing prediction accuracy.
Finally, IBM stock daily close prices data are used to verify the validity of the proposed algorithm.
American Psychological Association (APA)
Cai, Yongming& Song, Lei& Wang, Tingwei& Chang, Qing. 2014. Financial Time Series Forecasting Using Directed-Weighted Chunking SVMs. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-451485
Modern Language Association (MLA)
Cai, Yongming…[et al.]. Financial Time Series Forecasting Using Directed-Weighted Chunking SVMs. Mathematical Problems in Engineering No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-451485
American Medical Association (AMA)
Cai, Yongming& Song, Lei& Wang, Tingwei& Chang, Qing. Financial Time Series Forecasting Using Directed-Weighted Chunking SVMs. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-451485
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-451485