Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

Joint Authors

Zhu, Qing
Lai, Kin Keung
He, Kaijian
Zou, Yingchao

Source

The Scientific World Journal

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-06-25

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Medicine
Information Technology and Computer Science

Abstract EN

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.

American Psychological Association (APA)

Zhu, Qing& He, Kaijian& Zou, Yingchao& Lai, Kin Keung. 2014. Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1049252

Modern Language Association (MLA)

Zhu, Qing…[et al.]. Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model. The Scientific World Journal No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1049252

American Medical Association (AMA)

Zhu, Qing& He, Kaijian& Zou, Yingchao& Lai, Kin Keung. Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1049252

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1049252