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Enhancing existing stockmarket trading strategies using artificial neural networks: A case study

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Enhancing existing stockmarket trading strategies using artificial neural networks: A case study. / Vanstone, Bruce; Finnie, Gavin.
Neural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers. Vol. 4985 LNCS PART 2. ed. 2008. p. 478-487 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

HarvardHarvard

Vanstone, B & Finnie, G 2008, Enhancing existing stockmarket trading strategies using artificial neural networks: A case study. in Neural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers. PART 2 edn, vol. 4985 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 478-487. https://doi.org/10.1007/978-3-540-69162-4_50

APA

Vanstone, B., & Finnie, G. (2008). Enhancing existing stockmarket trading strategies using artificial neural networks: A case study. In Neural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers (PART 2 ed., Vol. 4985 LNCS, pp. 478-487). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-69162-4_50

CBE

Vanstone B, Finnie G. 2008. Enhancing existing stockmarket trading strategies using artificial neural networks: A case study. In Neural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers. PART 2 ed. pp. 478-487. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-69162-4_50

MLA

Vanstone, Bruce and Gavin Finnie "Enhancing existing stockmarket trading strategies using artificial neural networks: A case study". Neural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers. PART 2 udg., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2008, 478-487. https://doi.org/10.1007/978-3-540-69162-4_50

VancouverVancouver

Vanstone B, Finnie G. Enhancing existing stockmarket trading strategies using artificial neural networks: A case study. In Neural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers. PART 2 ed. Vol. 4985 LNCS. 2008. p. 478-487. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-69162-4_50

Author

Vanstone, Bruce ; Finnie, Gavin. / Enhancing existing stockmarket trading strategies using artificial neural networks: A case study. Neural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers. Vol. 4985 LNCS PART 2. ed. 2008. pp. 478-487 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

RIS

TY - GEN

T1 - Enhancing existing stockmarket trading strategies using artificial neural networks: A case study

AU - Vanstone, Bruce

AU - Finnie, Gavin

N1 - 14th International Conference on Neural Information Processing, ICONIP 2007 ; Conference date: 13-11-2007 Through 16-11-2007

PY - 2008

Y1 - 2008

N2 - Developing financially viable stockmarket trading systems is a difficult, yet reasonably well understood process. Once an initial trading system has been built, the desire usually turns to finding ways to improve the system. Typically, this is done by adding and subtracting if-then style rules, which act as filters to the initial buy/sell signal. Each time a new set of rules are added, the system is retested, and, dependant on the effect of the added rules, they may be included into the system. Naturally, this style of data snooping leads to a curve-fitting approach, and the resultant system may not continue to perform well out-of-sample. The authors promote a different approach, using artificial neural networks, and following their previously published methodology, they demonstrate their approach using an existing medium-term trading strategy as an example.

AB - Developing financially viable stockmarket trading systems is a difficult, yet reasonably well understood process. Once an initial trading system has been built, the desire usually turns to finding ways to improve the system. Typically, this is done by adding and subtracting if-then style rules, which act as filters to the initial buy/sell signal. Each time a new set of rules are added, the system is retested, and, dependant on the effect of the added rules, they may be included into the system. Naturally, this style of data snooping leads to a curve-fitting approach, and the resultant system may not continue to perform well out-of-sample. The authors promote a different approach, using artificial neural networks, and following their previously published methodology, they demonstrate their approach using an existing medium-term trading strategy as an example.

U2 - 10.1007/978-3-540-69162-4_50

DO - 10.1007/978-3-540-69162-4_50

M3 - Conference contribution

SN - 3540691596

VL - 4985 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 478

EP - 487

BT - Neural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers

ER -