Non-linear model identification and statistical significance tests and their application to financial modelling
Andrew N. Burgess · 1995
We describe a methodology, based upon the statistical concept of analysis of variance (ANOVA), which can be used both for non-linear model identification and for testing the statistical significance of inputs to a neural network. We compare our model identification procedure to established approach of correlation analysis on both linear and non-linear time-series. We describe how the significance tests can form the basis of a modelling methodology analagous to stepwise regression. Finally we consider an application of these techniques to the problem of modelling weekly returns of the FTSE 100 index.