DocumentCode
3498846
Title
Effects simulation of international gold prices on crude oil prices based on WBNNK model
Author
Jinliang, Zhang ; Mingming, Tang ; Mingxin, Tao
Author_Institution
Coll. of Resources Sci. & Technol., Bejing Normal Univ., Beijing, China
Volume
4
fYear
2009
fDate
8-9 Aug. 2009
Firstpage
459
Lastpage
463
Abstract
International gold prices could affect the entire world pricing system. And as international crude oil prices are very complex nonlinear time series, which are not only affected by the domination of objective economic laws, but also by politics and pricing system. Therefore it is difficult to establish an effective prediction model based on the general time series analysis. So we need to understand the effects of international gold prices on crude oil prices to get more accuracy prediction of crude oil prices. In this paper, we build up WBNNK (wavelet-based Boltzmann cooperative neural network and kernel density estimation) model. The international gold ad crude oil prices time series is decomposed into approximate components and random components. The approximate components, which represented the trend of oil price, are predicted with Boltzmann neural network, which is cooperative with international gold prices; the random components are predicted with Gaussian kernel density estimation model. In this paper, we analyzed the time-frequency structure of dubieties wavelet transform coefficient modulus for crude oil price time series, and predicted the oil price with Boltzmann neural network and Gaussian kernel density estimation model. The results show that the model has higher prediction accuracy.
Keywords
Gaussian processes; crude oil; econometrics; economic indicators; gold; neural nets; pricing; random processes; time series; wavelet transforms; Boltzmann cooperative neural network; WBNNK model; approximate component; econometrics; gaussian kernel density estimation model; international crude oil price; international gold price; nonlinear time series analysis; objective economic law; politics; prediction model; random component; time-frequency structure; wavelet transform coefficient modulus; world pricing system; Accuracy; Economic forecasting; Gold; Kernel; Neural networks; Petroleum; Predictive models; Pricing; Time frequency analysis; Time series analysis; Boltzman nerual network; Gaussian kernel density estimation; International crude oil price; Internationla gold price; Wavelet transform;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on
Conference_Location
Sanya
Print_ISBN
978-1-4244-4247-8
Type
conf
DOI
10.1109/CCCM.2009.5267557
Filename
5267557
Link To Document