Due to the complexity of crude oil price series, traditional statistics-based forecasting approach cannot produce a good prediction performance. In order to improve the prediction performance, a novel compressed sensing based learning paradigm is proposed through integrating compressed sensing...

The impact of extreme events on crude oil markets is of great importance in crude oil price analysis due to the fact that those events generally exert strong impact on crude oil markets. For better estimation of the impact of events on crude oil price volatility, this study attempts to use an...

In this study, an empirical mode decomposition (EMD) based neural network ensemble learning paradigm is proposed for world crude oil spot price forecasting. For this purpose, the original crude oil spot price series were first decomposed into a finite, and often small, number of intrinsic mode...