Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/62694
Title: | Anfis for trading | Authors: | Poh, Priscilla Qiong Wei | Keywords: | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence | Issue Date: | 2015 | Abstract: | For the purpose of this research, adaptive neuro-fuzzy inference system (ANFIS) had been designed and tested to construct a decision making model for the Foreign Exchange Market (Forex) of EUR/USD currency pair. The decision model attempts to imitate how a human will make decision in the Forex market. A set of technical analysis commonly used by traders was used to represent the human decision in this experiment. The proposed model was trained and tested with sets of data processed based on the set of technical analysis. The proposed model was evaluated based on its root mean square error, misclassification error and total profit or loss based on a unit of open price. By the analysis of the output produced, it is possible to conclude that the proposed model developed can predict the trend of the market by making correct decision in the Forex market. | URI: | http://hdl.handle.net/10356/62694 | Schools: | School of Computer Engineering | Rights: | Nanyang Technological University | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Student Reports (FYP/IA/PA/PI) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
FINAL YEAR REPORTv3.pdf Restricted Access | 1.99 MB | Adobe PDF | View/Open |
Page view(s)
415
Updated on Mar 28, 2025
Download(s) 50
28
Updated on Mar 28, 2025
Google ScholarTM
Check
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.