Creating short-term stockmarket trading strategies using artificial neural networks: A case study
Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Cyfraniad i Gynhadledd
Fersiynau electronig
Developing short-term stockmarket trading systems is a complex process, as there is a great deal of random noise present in the time series data of individual securities. The primary difficulty in training neural networks to identify return expectations is to find variables to help identify the signal present in the data. In this paper, the authors follow the previously published Vanstone and Finnie methodology. They develop a successful neural network, and demonstrate its effectiveness as the core element of a financially viable trading system.
| Iaith wreiddiol | Saesneg |
|---|---|
| Teitl | WORLD CONGRESS ON ENGINEERING 2008, VOLS I-II |
| Golygyddion | SI Ao, L Gelman, DWL Hukins, A Hunter, AM Korsunsky |
| Cyhoeddwr | INT ASSOC ENGINEERS-IAENG |
| Tudalennau | 80-84 |
| Nifer y tudalennau | 5 |
| ISBN (Argraffiad) | 978-988-98671-9-5 |
| Statws | Cyhoeddwyd - 2008 |
| Cyhoeddwyd yn allanol | Ie |
Cyfres gyhoeddiadau
| Enw | Lecture Notes in Engineering and Computer Science |
|---|---|
| Cyhoeddwr | INT ASSOC ENGINEERS-IAENG |