अमेरिकन जर्नल ऑफ कंप्यूटर साइंस एंड इंजीनियरिंग सर्वे खुला एक्सेस

अमूर्त

Forex Data Analysis Using Weka

Luciana Abednego* and Cecilia Esti Nugraheni

This paper conducts some experiments with forex trading data. The data being used is from kaggle.com, a website that provides datasets for machine learning and data scientists. The goal of the experiments is to know how to design many parameters in a forex trading robot. Some questions that want to be investigated are: How far the robot must set the stop loss or target profit level from the open position? When is the best time to apply for a forex robot that works only in a trending market? Which one is better: a forex trading robot that waits for a trending market or a robot that works during a sideways market? To answer these questions, some data visualizations are plotted in many types of graphs. The data representations are built using Weka, an open-source machine learning software. The data visualization helps the trader to design the strategy to trade the forex market.