SEARCHING FOR DIVISIA/INFLATION RELATIONSHIPS WITH THE AGGREGATE FEEDFORWARD NEURAL NETWORK

Vincent A. Schmidt, Jane M. Binner

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

Divisia component data is used in the training of an Aggregate Feedforward Neural Network (AFFNN), a general-purpose connectionist system designed to assist with data mining activities. The neural network is able to learn the money-price relationship, defined as the relationships between the rate of growth of the money supply and inflation. Learned relationships are expressed in terms of an automatically generated series of human-readable and machine-executable rules, shown to meaningfully and accurately describe inflation in terms of the original values of the Divisia component dataset.

Original languageEnglish
Title of host publicationApplications of Artificial Intelligence in Finance and Economics
EditorsJane Binner, Graham Kendall, Shu-Heng Chen
Pages225-241
Number of pages17
DOIs
Publication statusPublished - 1 Dec 2004

Publication series

NameAdvances in Econometrics
Volume19
ISSN (Print)0731-9053

ASJC Scopus subject areas

  • Economics and Econometrics

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