Creating trading systems with fundamental variables and neural networks: The Aby case study

Bruce Vanstone, Gavin Finnie, Tobias Hahn

Research output: Contribution to journalArticleResearchpeer-review

9 Citations (Scopus)

Abstract

The development of the Financial Crisis throughout 2008 and 2009 has made many investors and fund managers question whether growth-based investment approaches have had their day. Value-based approaches built on fundamental analysis have resurfaced again. Typically, these value-based models use fundamental variables to decide between investment opportunities. In a previous work, Vanstone et al. studied a set of filters published by Aby et al. during the dot-com crash of 2000 and subsequent aftermath, and tested and benchmarked these filters in the Australian market. The Aby filters rely on 4 different fundamental variables, and use rules with specific cut-off values to determine when to enter and exit trades. These cut-off values were found to be too restrictive for the Australian markets. This paper uses a neural network methodology by Vanstone and Finnie to develop a stockmarket trading system based on these same 4 fundamental variables, and demonstrates the important role neural networks have to play within complex and noisy environments, such as that provided by the stockmarket.

Original languageEnglish
Pages (from-to)78-91
Number of pages14
JournalMathematics and Computers in Simulation
Volume86
DOIs
Publication statusPublished - 2012

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Neural Networks
Filter
Neural networks
Financial Crisis
Managers
Crash
Methodology
Demonstrate
Market
Model
Trade

Cite this

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Creating trading systems with fundamental variables and neural networks : The Aby case study. / Vanstone, Bruce; Finnie, Gavin; Hahn, Tobias.

In: Mathematics and Computers in Simulation, Vol. 86, 2012, p. 78-91.

Research output: Contribution to journalArticleResearchpeer-review

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