The nature of statistical learning theory
The nature of statistical learning theory
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Predicting Time Series with Support Vector Machines
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
Forecasting stock market movement direction with support vector machine
Computers and Operations Research
An Improved CAViaR Model for Oil Price Risk
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
Support vector machines versus back propagation algorithm for oil price prediction
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
Prediction of movement direction in crude oil prices based on semi-supervised learning
Decision Support Systems
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This paper proposes a new method for crude oil price forecasting based on support vector machine (SVM). The procedure of developing a support vector machine model for time series forecasting involves data sampling, sample preprocessing, training & learning and out-of-sample forecasting. To evaluate the forecasting ability of SVM, we compare its performance with those of ARIMA and BPNN. The experiment results show that SVM outperforms the other two methods and is a fairly good candidate for the crude oil price prediction.