Open AccessForex Data Analysis using Weka
Author(s) -
Luciana Abednego,
Cecilia Esti Nugraheni
Publication year - 2021
Publication title -
international journal of fuzzy logic systems
Language(s) - English
Resource type - Journals
ISSN - 1839-6283
DOI - 10.5121/ijfls.2021.11103
Subject(s) - foreign exchange market , computer science , robot , trading strategy , profit (economics) , algorithmic trading , position (finance) , visualization , artificial intelligence , data set , market data , big data , data mining , foreign exchange , econometrics , financial economics , economics , finance , microeconomics , monetary economics
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.