Publication:
Prediction of Expert Advisor Trading System Using An Artificial Intelligence System
Prediction of Expert Advisor Trading System Using An Artificial Intelligence System
| cris.author.scopus-author-id | 57909907600 | |
| cris.author.scopus-author-id | 57201059019 | |
| cris.author.scopus-author-id | 57207458751 | |
| cris.author.scopus-author-id | 57578158900 | |
| dc.contributor.author | Muhammad Amir Hakim Bin Ismail | |
| dc.contributor.author | Zulkifli Bin Husin | |
| dc.contributor.author | Tan Wei Keong | |
| dc.contributor.author | Muhammad Luqman Bin Yasruddin | |
| dc.date.accessioned | 2024-09-27T07:14:09Z | |
| dc.date.available | 2024-09-27T07:14:09Z | |
| dc.date.issued | 2022-01-01 | |
| dc.description.abstract | The paper deals with a technical analysis for foreign exchange price predictions using Japanese Candlestick Patterns and Support Vector Machine (SVM). Manual traders are frequently influenced by emotions, which might result in a huge loss. As a result, this research aims to develop an Expert Advisor system that trades without regard for human emotions. To predict the movement of the foreign exchange price, we present a method that combines the Japanese Candlestick Patterns and the SVM algorithm. The article discusses the use of Japanese Candlestick Patterns and the SVM algorithm in expert advisor system to generate accurate predictions of foreign exchange prices. The experimental results on the Euro-Dollar (EURUSD) price indicate that the combination of the Japanese candlestick pattern and the SVM algorithm is effective at providing information for EURUSD price prediction. The proposed algorithm's performance is evaluated, demonstrating that it is capable of predicting the movement of foreign exchange prices using the Japanese Candlestick Patterns and SVM algorithm. | |
| dc.identifier.doi | 10.1109/GlobConET53749.2022.9872367 | |
| dc.identifier.isbn | [9781665443579] | |
| dc.identifier.scopus | 2-s2.0-85138883008 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14170/4698 | |
| dc.identifier.uri | https://ieeexplore.ieee.org/xpl/conhome/9872165/proceeding | |
| dc.language.iso | en | |
| dc.relation.grantno | undefined | |
| dc.relation.ispartof | 2022 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2022 | |
| dc.relation.ispartofseries | 2022 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2022 | |
| dc.subject | Automated trading system | |
| dc.subject | Candlestick pattern | |
| dc.subject | Expert advisor | |
| dc.subject | Support vector machine | |
| dc.title | Prediction of Expert Advisor Trading System Using An Artificial Intelligence System | |
| dc.type | Conference Proceeding | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 237 | |
| oaire.citation.startPage | 233 | |
| oairecerif.affiliation.orgunit | Universiti Malaysia Perlis | |
| oairecerif.affiliation.orgunit | Universiti Malaysia Perlis | |
| oairecerif.affiliation.orgunit | Universiti Malaysia Perlis | |
| oairecerif.affiliation.orgunit | Universiti Malaysia Perlis | |
| oairecerif.author.affiliation | Universiti Malaysia Perlis | |
| oairecerif.author.affiliation | Universiti Malaysia Perlis | |
| oairecerif.author.affiliation | Universiti Malaysia Perlis | |
| oairecerif.author.affiliation | Universiti Malaysia Perlis | |
| person.identifier.orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| person.identifier.orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| person.identifier.orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| person.identifier.orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| person.identifier.scopus-author-id | 57909907600 | |
| person.identifier.scopus-author-id | 57201059019 | |
| person.identifier.scopus-author-id | 57207458751 | |
| person.identifier.scopus-author-id | 57578158900 |
Files
Original bundle
1 - 1 of 1
- Name:
- Prediction of expert Advisor Trading System using An Artificial Intelligence System.pdf
- Size:
- 95.75 KB
- Format:
- Adobe Portable Document Format
- Description: