dc.contributor.author | Liljeblad, Daniel | swe |
dc.date.accessioned | 2006-12-13 | swe |
dc.date.accessioned | 2007-01-16T16:40:25Z | |
dc.date.available | 2007-01-16T16:40:25Z | |
dc.date.issued | 2003 | swe |
dc.identifier.uri | http://hdl.handle.net/2077/1057 | |
dc.description.abstract | The identification of specific patterns in stock price derived from technical stock analysis
heuristics, which after occurring resulted in a predefined price movement, was the subject of
this research effort. The motive was to enhance the profitability of an investment method
based on such patterns. To identify the specific patterns resulting in the predefined price
movement, artificial neural networks were used. A theoretical model for combining an expert
system, filled with knowledge from technical stock analysis heuristics, and artificial neural
networks into a hybrid integrated system was presented. Experiments were then conducted in
order to evaluate whether the proposed method actually could improve the profitability of the
selected investment method. Neural networks were trained in these experiments to classify
whether the outcome of an occurred pattern would result in a predefined price movement. The
major findings of this research was that; using the proposed method we were able to enhance
some specific patterns used in technical analysis, occurring in the Swedish OMX- index during
the specific period. | swe |
dc.format.extent | 45 pages | swe |
dc.format.extent | 393295 bytes | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | swe |
dc.subject | Artificial Intelligence; Expert System; Hybrid System;
Neural Network; Technical Analysis; Trading; | swe |
dc.title | Enhancing Trading with Technology
-A Neural Network-Expert System Hybrid Approach- | swe |
dc.setspec.uppsok | SocialBehaviourLaw | swe |
dc.type.uppsok | D | swe |
dc.contributor.department | Göteborgs universitet/Institutionen för informatik | swe |
dc.contributor.department | Göteborg University/Department of Informatics | eng |
dc.type.degree | Student essay | swe |
dc.gup.origin | Göteborg University. School of Business, Economics and Law | swe |
dc.gup.epcid | 2958 | swe |
dc.subject.svep | Informatics | swe |