Designing short term trading systems with artificial neural networks

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddCyfraniad i Gynhadledd

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Designing short term trading systems with artificial neural networks. / Vanstone, Bruce; Finnie, Gavin; Hahn, Tobias.
Advances in Electrical Engineering and Computational Science. Cyfrol 39 LNEE 2009. t. 401-409 (Lecture Notes in Electrical Engineering).

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddCyfraniad i Gynhadledd

HarvardHarvard

Vanstone, B, Finnie, G & Hahn, T 2009, Designing short term trading systems with artificial neural networks. yn Advances in Electrical Engineering and Computational Science. cyfrol. 39 LNEE, Lecture Notes in Electrical Engineering, tt. 401-409. https://doi.org/10.1007/978-90-481-2311-7_34

APA

Vanstone, B., Finnie, G., & Hahn, T. (2009). Designing short term trading systems with artificial neural networks. Yn Advances in Electrical Engineering and Computational Science (Cyfrol 39 LNEE, tt. 401-409). (Lecture Notes in Electrical Engineering). https://doi.org/10.1007/978-90-481-2311-7_34

CBE

Vanstone B, Finnie G, Hahn T. 2009. Designing short term trading systems with artificial neural networks. Yn Advances in Electrical Engineering and Computational Science. tt. 401-409. (Lecture Notes in Electrical Engineering). https://doi.org/10.1007/978-90-481-2311-7_34

MLA

Vanstone, Bruce, Gavin Finnie a Tobias Hahn "Designing short term trading systems with artificial neural networks". Advances in Electrical Engineering and Computational Science. Lecture Notes in Electrical Engineering. 2009, 401-409. https://doi.org/10.1007/978-90-481-2311-7_34

VancouverVancouver

Vanstone B, Finnie G, Hahn T. Designing short term trading systems with artificial neural networks. Yn Advances in Electrical Engineering and Computational Science. Cyfrol 39 LNEE. 2009. t. 401-409. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-90-481-2311-7_34

Author

Vanstone, Bruce ; Finnie, Gavin ; Hahn, Tobias. / Designing short term trading systems with artificial neural networks. Advances in Electrical Engineering and Computational Science. Cyfrol 39 LNEE 2009. tt. 401-409 (Lecture Notes in Electrical Engineering).

RIS

TY - GEN

T1 - Designing short term trading systems with artificial neural networks

AU - Vanstone, Bruce

AU - Finnie, Gavin

AU - Hahn, Tobias

PY - 2009

Y1 - 2009

N2 - There is a long established history of applying Artificial Neural Networks (ANNs) to financial data sets. In this paper, the authors demonstrate the use of this methodology to develop a financially viable, short-term trading system. When developing short-term systems, the authors typically site the neural network within an already existing non-neural trading system. This paper briefly reviews an existing medium-term long-only trading system, and then works through the Vanstone and Finnie methodology to create a short-term focused ANN which will enhance this trading strategy. The initial trading strategy and the ANN enhanced trading strategy are comprehensively benchmarked both in-sample and out-of-sample, and the superiority of the resulting ANN enhanced system is demonstrated.

AB - There is a long established history of applying Artificial Neural Networks (ANNs) to financial data sets. In this paper, the authors demonstrate the use of this methodology to develop a financially viable, short-term trading system. When developing short-term systems, the authors typically site the neural network within an already existing non-neural trading system. This paper briefly reviews an existing medium-term long-only trading system, and then works through the Vanstone and Finnie methodology to create a short-term focused ANN which will enhance this trading strategy. The initial trading strategy and the ANN enhanced trading strategy are comprehensively benchmarked both in-sample and out-of-sample, and the superiority of the resulting ANN enhanced system is demonstrated.

U2 - 10.1007/978-90-481-2311-7_34

DO - 10.1007/978-90-481-2311-7_34

M3 - Conference contribution

SN - 9789048123100

VL - 39 LNEE

T3 - Lecture Notes in Electrical Engineering

SP - 401

EP - 409

BT - Advances in Electrical Engineering and Computational Science

ER -