DocumentCode
1622505
Title
Non-linear model identification and statistical significance tests and their application to financial modelling
Author
Burgess, A.N.
Author_Institution
London Bus. Sch., UK
fYear
1995
Firstpage
312
Lastpage
317
Abstract
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
Keywords
economic cybernetics; identification; statistical analysis; ANOVA; FTSE 100 index; correlation analysis; financial modelling; model identification; neural network; statistical significance tests; stepwise regression; time-series;
fLanguage
English
Publisher
iet
Conference_Titel
Artificial Neural Networks, 1995., Fourth International Conference on
Conference_Location
Cambridge
Print_ISBN
0-85296-641-5
Type
conf
DOI
10.1049/cp:19950574
Filename
497837
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