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International Conference on Statistics, Combinatorics and Related Areas and the Eighth International Conference of Forum for Interdisciplinary Mathematics
December 19-21, 2001
School of Mathematics and Applied Statistics, University of Wollongong
Wollongong, NSW, Australia

Organizers
Satya N. Mishra (University of South Alabama), Chandra M. Gulati (University of Wollongong)

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A Comparative Study of Neural Network, Genetic Programming, and Support-Vector Machine Methods in Forecasting Financial Time Series
by
David Edelman
University of Wollongong
Coauthors: Pamela Davy, Lyndon Ang, Emma Lawrence, Simon Reid

The problem of forecasting daily returns for the Australian All-Ordinaries Index is used as a Case Study for comparing Neural Network, Genetic Programming, and Support-Vector Machine Methods. The present paper is an overview of individual studies carried out, as part of their degree requirements, by Honours' students Lyndon Ang, Emma Lawrence, and Simon Reid, under the joint supervision of Pamela Davy and David Edelman. While each of the three approaches is found to be successful for this problem, a number of distinct, interesting features of the various methods are worth noting.

Date received: November 12, 2001

Copyright © 2001 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Conferences Inc. Document # caid-73.