Investigating the size and value effect in determining performance of Australian listed companies: A neural network approach

Luu, J; Kennedy, PJ

Investigating the size and value effect in determining performance of Australian listed companies: A neural network approach

Luu, J Kennedy, PJ

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Publication Type:: Conference Proceeding
Citation:: Conferences in Research and Practice in Information Technology Series, 2006, 61 pp. 155 - 161
Issue Date:: 2006-12-01

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Field	Value	Language
dc.contributor.author	Luu, J	en_US
dc.contributor.author	Kennedy, PJ https://orcid.org/0000-0001-7837-3171	en_US
dc.date.issued	2006-12-01	en_US
dc.identifier.citation	Conferences in Research and Practice in Information Technology Series, 2006, 61 pp. 155 - 161	en_US
dc.identifier.issn	1445-1336	en_US
dc.identifier.uri	http://hdl.handle.net/10453/1776
dc.description.abstract	This paper explores the size and value effect in influencing performance of individual companies using backpropagation neural networks. According to existing theory, companies with small market capitalization and high book to market ratios have a tendency to perform better in the future. Data from over 300 Australian Stock Exchange listed companies between 2000-2004 is examined and a neural network is trained to predict company performance based on market capitalization, book to market ratio, beta and standard deviation. Evidence for the value effect was found over longer time periods but there was less for the size effect. Poor company performance was also observed to be correlated with high risk. © 2006, Australian Computer Society, Inc.	en_US
dc.relation.ispartof	Conferences in Research and Practice in Information Technology Series	en_US
dc.title	Investigating the size and value effect in determining performance of Australian listed companies: A neural network approach	en_US
dc.type	Conference Proceeding
utslib.citation.volume	61	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Sydney, Australia	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	61	en_US

Abstract:

This paper explores the size and value effect in influencing performance of individual companies using backpropagation neural networks. According to existing theory, companies with small market capitalization and high book to market ratios have a tendency to perform better in the future. Data from over 300 Australian Stock Exchange listed companies between 2000-2004 is examined and a neural network is trained to predict company performance based on market capitalization, book to market ratio, beta and standard deviation. Evidence for the value effect was found over longer time periods but there was less for the size effect. Poor company performance was also observed to be correlated with high risk. © 2006, Australian Computer Society, Inc.

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http://hdl.handle.net/10453/1776