Financial Innovation in Taiwan: An Application of Neural Networks to the Broad Monetary Aggregates

Alicia M. Gazely*, Jane M. Binner, Shu Heng Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The econometric performance of a new generation of Divisia indices, which were reformulated to take account of financial innovation in Taiwan, was discussed. Artificial neural network (ANN) technology was used to examine the inflation. Two innovation adjusted Divisia series were analyzed and modified to allow for a learning process by individuals as they adapted to changes in the productivity of monetary assests and adjust their holdings. Analysis shows that the combination of Divisia measures of money with the ANN offers a promising starting point for the development of an improved model of inflation.

Original languageEnglish
Title of host publicationProceedings of the Fifth Joint Conference on Information Sciences, JCIS 2000, Volume 2
EditorsP.P. Wang, P.P. Wang
Pages903-907
Number of pages5
Edition2
Publication statusPublished - 2000
EventProceedings of the Fifth Joint Conference on Information Sciences, JCIS 2000 - Atlantic City, NJ, United States
Duration: 27 Feb 20003 Mar 2000

Publication series

NameProceedings of the Joint Conference on Information Sciences
Number2
Volume5

Conference

ConferenceProceedings of the Fifth Joint Conference on Information Sciences, JCIS 2000
Country/TerritoryUnited States
CityAtlantic City, NJ
Period27/02/003/03/00

ASJC Scopus subject areas

  • General Computer Science

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