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Morphological Component Analysis based Hybrid Approach for Prediction of Crude Oil Price
Kaijian He1; Kin Keung Lai1; Jerome Yen2
2010
Conference Name2010 Third International Joint Conference on Computational Science and Optimization
Source PublicationProceedings of the 2010 Third International Joint Conference on Computational Science and Optimization
Conference Date28-31 May 2010
Conference PlaceHuangshan, China
Abstract

The prediction of crude oil price remains a challenging issue due to its complicated data generating process. Aside from the long perceived nonlinear data feature issue, recent empirical evidence suggests that the mixture of data characteristics in the time scale domain is another important data feature to be incorporated in the modeling process. This paper proposes a novel Morphological Component Analysis based hybrid methodology for modeling the multi scale heterogeneous data generating process. Empirical studies in the marker crude oil market show the significant performance improvement of the proposed algorithm, against benchmark models. The superior performance of the proposed model is attributed to the separation of the underlying distinct data features and the identification of appropriate model specifications for them. Meanwhile, the proposed methodology offers additional insights into the underlying data generating process and their economic viability.

KeywordTime Series Model Morphological Component Analysis Crude Oil Price Support Vector Regression Randomwalk Model
DOI10.1109/CSO.2010.22
Language英语
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Document TypeConference paper
专题Faculty of Business Administration
INSTITUTE OF COLLABORATIVE INNOVATION
Affiliation1.Department of Management SciencesCity University of Hong KongTat Chee Avenue, Kowloon, Hong Kong
2.School of Business Administration and Tourism ManagementThe Chinese University of Hong Kong -Tung Wah Group of Hospitals Community CollegeWylie Road, Homantin, Kowloon, Hong Kong
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GB/T 7714
Kaijian He,Kin Keung Lai,Jerome Yen. Morphological Component Analysis based Hybrid Approach for Prediction of Crude Oil Price[C],2010.
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