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

Research output: Contribution to journalArticlepeer-review

Standard Standard

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, 12.2012, p. 78-91.

Research output: Contribution to journalArticlepeer-review

HarvardHarvard

APA

CBE

MLA

VancouverVancouver

Vanstone B, Finnie G, Hahn T. Creating trading systems with fundamental variables and neural networks: The Aby case study. Mathematics and Computers in Simulation. 2012 Dec;86:78-91. doi: 10.1016/j.matcom.2011.01.002

Author

Vanstone, Bruce ; Finnie, Gavin ; Hahn, Tobias. / Creating trading systems with fundamental variables and neural networks: The Aby case study. In: Mathematics and Computers in Simulation. 2012 ; Vol. 86. pp. 78-91.

RIS

TY - JOUR

T1 - Creating trading systems with fundamental variables and neural networks: The Aby case study

AU - Vanstone, Bruce

AU - Finnie, Gavin

AU - Hahn, Tobias

PY - 2012/12

Y1 - 2012/12

N2 - 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.

AB - 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.

U2 - 10.1016/j.matcom.2011.01.002

DO - 10.1016/j.matcom.2011.01.002

M3 - Article

VL - 86

SP - 78

EP - 91

JO - Mathematics and Computers in Simulation

JF - Mathematics and Computers in Simulation

SN - 0378-4754

ER -