Daily Crude Oil Price Forecasting Using Hybridizing Wavelet and Artificial Neural Network Model
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-16
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
A new method based on integrating discrete wavelet transform and artificial neural networks (WANN) model for daily crude oil price forecasting is proposed.
The discrete Mallat wavelet transform is used to decompose the crude price series into one approximation series and some details series (DS).
The new series obtained by adding the effective one approximation series and DS component is then used as input into the ANN model to forecast crude oil price.
The relative performance of WANN model was compared to regular ANN model for crude oil forecasting at lead times of 1 day for two main crude oil price series, West Texas Intermediate (WTI) and Brent crude oil spot prices.
In both cases, WANN model was found to provide more accurate crude oil prices forecasts than individual ANN model.
American Psychological Association (APA)
Shabri, Ani& Samsudin, Ruhaidah. 2014. Daily Crude Oil Price Forecasting Using Hybridizing Wavelet and Artificial Neural Network Model. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-453980
Modern Language Association (MLA)
Shabri, Ani& Samsudin, Ruhaidah. Daily Crude Oil Price Forecasting Using Hybridizing Wavelet and Artificial Neural Network Model. Mathematical Problems in Engineering No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-453980
American Medical Association (AMA)
Shabri, Ani& Samsudin, Ruhaidah. Daily Crude Oil Price Forecasting Using Hybridizing Wavelet and Artificial Neural Network Model. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-453980
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-453980