Muhammad Amir Hakim Ismail, Muhammad Luqman Yasruddin, Z. Husin, W. Tan
{"title":"Automated Trading System for Forecasting the Foreign Exchange Market Using Technical Analysis Indicators and Artificial Neural Network","authors":"Muhammad Amir Hakim Ismail, Muhammad Luqman Yasruddin, Z. Husin, W. Tan","doi":"10.1109/CSPA55076.2022.9781856","DOIUrl":null,"url":null,"abstract":"The article discusses an automated trading system for forecasting foreign exchange markets that utilise Technical Analysis (TA) indicators and Artificial Neural Networks (ANN). Manual traders are usually swayed by their emotions, resulting in a catastrophic loss. As a result, this research will focus on developing an automated trading system that operates independently of human emotions. We provide a strategy for forecasting the movement of the foreign exchange market that incorporates TA indicators and the ANN system. The article examines TA indicators and the ANN system in automated trading systems to achieve accurate foreign exchange price forecasts. The experimental results on the Pound-Dollar (GBP/USD) exchange rate demonstrate that the combination of the TA indicators and the ANN system effectively provides information for forecasting the GBP/USD exchange rate. The performance of the suggested method is examined, revealing that it is capable of forecasting foreign exchange market movement utilising TA indicators and an ANN system.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSPA55076.2022.9781856","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The article discusses an automated trading system for forecasting foreign exchange markets that utilise Technical Analysis (TA) indicators and Artificial Neural Networks (ANN). Manual traders are usually swayed by their emotions, resulting in a catastrophic loss. As a result, this research will focus on developing an automated trading system that operates independently of human emotions. We provide a strategy for forecasting the movement of the foreign exchange market that incorporates TA indicators and the ANN system. The article examines TA indicators and the ANN system in automated trading systems to achieve accurate foreign exchange price forecasts. The experimental results on the Pound-Dollar (GBP/USD) exchange rate demonstrate that the combination of the TA indicators and the ANN system effectively provides information for forecasting the GBP/USD exchange rate. The performance of the suggested method is examined, revealing that it is capable of forecasting foreign exchange market movement utilising TA indicators and an ANN system.