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Application of Genetic Algorithms to the Optimisation of Neural Network Configuration for Stock Market Forecasting

conference contribution
posted on 2023-05-23, 02:49 authored by Hulme, D, Shuxiang XuShuxiang Xu
© Springer-Verlag Berlin Heidelberg 2001. Neural networks are recognised as an effective tool for predicting stock prices (Shin & Han, 2000), but little is known about which configurations are best and for which indices. The present study uses genetic algorithms to find a near optimal learning rate, momentum, tolerance and network architecture for 47 indices listed on the Australian Stock Exchange (ASX). Some relationships were determined between stock index and neural network attributes, and important observations were made for the further development of a methodology for determining optimal neural network configurations.

History

Publication title

AI 2001: Advances in Artificial Intelligence

Volume

LNAI 2256

Editors

M Stumptner, D Corbett

Pagination

285-296

ISBN

3-540-42960-3

Department/School

School of Information and Communication Technology

Publisher

Springer-Verlag

Place of publication

Berlin

Event title

14th Australian Joint Conference on Artificial Intelligence

Event Venue

Adelaide

Date of Event (Start Date)

2001-12-10

Date of Event (End Date)

2001-12-14

Repository Status

  • Restricted

Socio-economic Objectives

Information systems, technologies and services not elsewhere classified

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