Forecasting stock price movements using neural networks

The prediction of security prices has shown to be one of the most important but most difficult tasks in financial operations. Linear approaches failed to model the non-linear behaviour of markets and non-linear approaches turned out to posses too many constraints. Neural networks seem to be a suitable method to overcome these problems since they provide algorithms which process large sets of data from a non-linear context and yield thorough results. The first problem addressed by this research paper is the applicability of neural networks with respect to markets as a tool for pattern recognition. It will be shown that markets posses the necessary requirements for the use of neural networks, i.e. markets show patterns which are exploitable.

Grantor dc:publisher.institution

Department of Statistical Sciences

Year dc:date.issued

2006

Author dc:creator

• Rank, Christian

Advisor dc:contributor.advisor

• Guo, Renkuan

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/11427/4392

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/4392