International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 10, No. 9, 8 Sep. 2018
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Supervised Support Vector Machine in Predicting Foreign Exchange Trading
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Author(s)
Index Terms
Foreign Exchange Market, Exchange Rates, Machine Learning, Support Vector Machine (SVM), Prediction
Abstract
Trends of currency rates can be predicted with supporting from supervised machine learning in the transaction systems such as support vector machine (SVM). By assumption of binary classification problems, the SVM can predict foreign exchange transaction as uptrend or downtrend. The prediction is performed basing on collected historical data. Alternative SVM models have been used to vote the best one, which is deployed detail in Expert Advisor (Robotics). This is to show that support vector machine models might help investors to automatically make transaction decisions of Bid/Ask in Foreign Exchange Market. For comparison, the transactions without using SVM model also are performed. The results of experimental transactions show the advantages of using SVM model compared to the transactions without using SVM model.
Cite This Paper
Thuy Nguyen Thi Thu, Vuong Dang Xuan, "Supervised Support Vector Machine in Predicting Foreign Exchange Trading", International Journal of Intelligent Systems and Applications(IJISA), Vol.10, No.9, pp.48-56, 2018. DOI:10.5815/ijisa.2018.09.06
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