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Applying Machine Learning Approach to Build an Automated Trading System for Gold Chart

by Mehdi Safaei Ghaderi, Adel Akbari, Zahra Najafi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 27
Year of Publication: 2022
Authors: Mehdi Safaei Ghaderi, Adel Akbari, Zahra Najafi
10.5120/ijca2022922344

Mehdi Safaei Ghaderi, Adel Akbari, Zahra Najafi . Applying Machine Learning Approach to Build an Automated Trading System for Gold Chart. International Journal of Computer Applications. 184, 27 ( Sep 2022), 57-61. DOI=10.5120/ijca2022922344

@article{ 10.5120/ijca2022922344,
author = { Mehdi Safaei Ghaderi, Adel Akbari, Zahra Najafi },
title = { Applying Machine Learning Approach to Build an Automated Trading System for Gold Chart },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2022 },
volume = { 184 },
number = { 27 },
month = { Sep },
year = { 2022 },
issn = { 0975-8887 },
pages = { 57-61 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number27/32489-2022922344/ },
doi = { 10.5120/ijca2022922344 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:22:36.738775+05:30
%A Mehdi Safaei Ghaderi
%A Adel Akbari
%A Zahra Najafi
%T Applying Machine Learning Approach to Build an Automated Trading System for Gold Chart
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 27
%P 57-61
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Nowadays, with the pervasiveness of online and algorithmic trading, there is a need to analyze financial markets’ trading data and turn them into profitable decisions in the shortest time possible. The purpose of this study is to develop an automated algorithmic trading system using AI (Artificial Intelligence) in the global gold market. In recent years, employing AI to build profitable strategies has considerably increased. In this paper, to create a trading system, the genetic algorithm is employed to optimize the two functions of net profit and return on conditional risk and technical analysis. Also, to complete the risk management system, the optimum profit and loss limit for the market is set. The results show that the generated trading system has a more favorable return-to-risk ratio than other competing strategies. A 30-minute timeframe is also suitable for building trading systems on gold.

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Index Terms

Computer Science
Information Sciences

Keywords

Algorithmic trading gold technical analysis strategy genetic algorithm

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