Unsupervised learning for financial forecasting
An unsupervised neural based approach to financial forecasting is presented; its performance is compared with that from a statistical technique and two other standard neural network techniques. The authors show that the unsupervised network outperforms multilayer perceptrons, radial basis function network and a standard ARIMA model.