dc.contributor.author | Loginov, Alexander | |
dc.date.accessioned | 2013-03-27T19:12:19Z | |
dc.date.available | 2013-03-27T19:12:19Z | |
dc.date.issued | 2013-03-27 | |
dc.identifier.uri | http://hdl.handle.net/10222/21433 | |
dc.description.abstract | This research investigates the ability of genetic programming to build profitable trad- ing strategies for the Foreign Exchange Market (FX) of one major currency pair (EURUSD) using one hour prices from July 1, 2009 to November 30, 2012. We rec- ognize that such environments are likely to be non-stationary and we do not expect that a single training partition, used to train a trading agent, represents all likely future behaviours. The proposed adaptive retraining algorithm – hereafter FXGP – detects poor trading behaviours and trains a new trading agent. This represents a significant departure from current practice which assumes some form of continuous evolution. Extensive benchmarking is performed against the widely used EURUSD currency pair. The non-stationary nature of the task is shown to result in a prefer- ence for exploration over exploitation. Moreover, adopting a behavioural approach to detecting retraining events is more effective than assuming incremental adaptation on a continuous basis. From the application perspective, we demonstrate that use of a validation partition and Stop-Loss (S/L) orders significantly improves the perfor- mance of a trading agent. In addition the task of co-evolving of technical indicators (TI) and the decision trees (DT) for deploying trading agent is explicitly addressed. The results of 27 experiments of 100 simulations each demonstrate that FXGP sig- nificantly outperforms existing approaches and generates profitable solutions with a high probability. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Foreign Exchange Trading, Dynamic Environments, Symbiosis, Genetic Programming | en_US |
dc.title | ON THE UTILITY OF EVOLVING FOREX MARKET TRADING AGENTS WITH CRITERIA BASED RETRAINING | en_US |
dc.date.defence | 2013-03-25 | |
dc.contributor.department | Faculty of Computer Science | en_US |
dc.contributor.degree | Master of Computer Science | en_US |
dc.contributor.external-examiner | n/a | en_US |
dc.contributor.graduate-coordinator | Dr. Qigang Gao | en_US |
dc.contributor.thesis-reader | Dr. Garnett Wilson | en_US |
dc.contributor.thesis-reader | Dr. Vlado Keselj | en_US |
dc.contributor.thesis-supervisor | Dr. Malcolm I. Heywood | en_US |
dc.contributor.ethics-approval | Not Applicable | en_US |
dc.contributor.manuscripts | Not Applicable | en_US |
dc.contributor.copyright-release | Not Applicable | en_US |