Abstract
The exchange rate of each money pair can be predicted by using machine learning algorithm during classification process. With the help of supervised machine learning model, the predicted uptrend or downtrend of FoRex rate might help traders to have right decision on FoRex transactions. The installation of machine learning algorithms in the FoRex trading online market can automatically make the transactions of buying/selling. All the transactions in the experiment are performed by using scripts added-on in transaction application. The capital, profits results of use support vector machine (SVM) models are higher than the normal one (without use of SVM).
Highlights
Supervised machine learning can apply into many areas in computer science such as decision making, forecasting, and specially is to predict stock price or money exchange rate, and so on
The support vector machine can help to forecast FoRex trend of up or down. This is because the outputs of FoRex rate are received as binary values
The FoRex problems can be seen as classification ones which can be solved by supervised learning particular with support vector machine (SVM) models
Summary
Supervised machine learning can apply into many areas in computer science such as decision making, forecasting, and specially is to predict stock price or money exchange rate, and so on. Alternative experiments with different support vector machine models are performed in this paper. These are to show the advantage of using them in FoRex rate prediction. Based on this framework, a representative SVM model, which is proposed from research experiment in [27], is chosen to install into expert advisor (robotics) in FoRex transaction software to make the actual FoRex transactions with demo account
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