Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model
As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important styli...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/341734 |
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| author | Qing Zhu Kaijian He Yingchao Zou Kin Keung Lai |
| author_facet | Qing Zhu Kaijian He Yingchao Zou Kin Keung Lai |
| author_sort | Qing Zhu |
| collection | DOAJ |
| description | As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations. |
| format | Article |
| id | doaj-art-6a37a9ce483c497791a2f44a79fc028e |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-6a37a9ce483c497791a2f44a79fc028e2025-02-03T06:44:26ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/341734341734Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based ModelQing Zhu0Kaijian He1Yingchao Zou2Kin Keung Lai3School of Economics and Finance, Xi’an Jiaotong University, Xi’an 710049, ChinaSchool of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, ChinaSchool of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, ChinaInternational Business School, Shaanxi Normal University, Xi’an 710062, ChinaAs a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.http://dx.doi.org/10.1155/2014/341734 |
| spellingShingle | Qing Zhu Kaijian He Yingchao Zou Kin Keung Lai Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model The Scientific World Journal |
| title | Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model |
| title_full | Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model |
| title_fullStr | Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model |
| title_full_unstemmed | Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model |
| title_short | Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model |
| title_sort | day ahead crude oil price forecasting using a novel morphological component analysis based model |
| url | http://dx.doi.org/10.1155/2014/341734 |
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