In this article, a mixed methodology that combines both the Autoregressive Moving Average Model (ARMA) and Neural Network Regression (NNR) models is proposed to take advantage of the unique strength of ARMA and NNR models in linear and nonlinear modelling. Experimental results with real data...

The motivation for this article is to investigate the use of a promising class of Neural Network (NN) models, Higher Order Neural Networks (HONNs), when applied to the task of forecasting the 1-day ahead Value at Risk (VaR) of the brent oil and gold bullion series with only autoregressive terms...

A clear motivation for this paper is the investigation of a correlation filter to improve the return/risk performance of spread trading models. A further motivation for this paper is the extension of trading futures spreads beyond the 'Fair Value' type of model used by Butterworth and Holmes...