- Title
- Forecasting model for crude oil prices based on artificial neural networks
- Creator
- Haidar, Imad; Kulkarni, Siddhivinayak; Pan, Heping
- Date
- 2008
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/53428
- Identifier
- vital:3721
- Identifier
-
https://doi.org/10.1109/ISSNIP.2008.4761970
- Identifier
- ISBN:9781424438228
- Abstract
- This paper presents short-term forecasting model for crude oil prices based on three layer feedforward neural network. Careful attention was paid on finding the optimal network structure. Moreover, a number of features were tested as an inputs such as crude oil futures prices, dollar index, gold spot price, heating oil spot price and S&P 500 index. The results show that with adequate network design and appropriate selection of the training inputs, feedforward networks are capable of forecasting noisy time series with high accuracy.
- Publisher
- Sydney, New South Wales : IEEE
- Relation
- Paper presented at International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2008, Sydney, New South Wales : 15th-18th December 2008 p. 103-108
- Rights
- Copyright IEEE
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0902 Automotive Engineering; Commodity trading; Crude oil; Economic forecasting; Economic indicators; Feedforward neural nets; Learning (artificial intelligence); Pricing; Time series
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