Forex Trading Robot Using Fuzzy Logic

Fuente: arXiv
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Main Authors: Shabani, Mustafa, Nasiri, Alireza, Nafardi, Hassan
Format: Preprint
Published: 2025
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author Shabani, Mustafa
Nasiri, Alireza
Nafardi, Hassan
author_facet Shabani, Mustafa
Nasiri, Alireza
Nafardi, Hassan
contents In this study, we propose a fuzzy system for conducting short-term transactions in the forex market. The system is designed to enhance common strategies in the forex market using fuzzy logic, thereby improving the accuracy of transactions. Traditionally, technical strategies based on oscillator indicators have relied on predefined ranges for indicators such as Relative Strength Index (RSI), Commodity Channel Indicator (CCI), and Stochastic to determine entry points for trades. However, the use of these classic indicators has yielded suboptimal results due to the changing nature of the market over time. In our proposed approach, instead of employing classical indicators, we introduce a fuzzy Mamdani system for each indicator. The results obtained from these systems are then combined through voting to design a trading robot. Our findings demonstrate a considerable increase in the profitability factor compared to three other methods. Additionally, net profit, gross profit, and maximum capital reduction are calculated and compared across all approaches.
format Preprint
id arxiv_https___arxiv_org_abs_2507_06383
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Forex Trading Robot Using Fuzzy Logic
Shabani, Mustafa
Nasiri, Alireza
Nafardi, Hassan
Systems and Control
Computational Engineering, Finance, and Science
Logic in Computer Science
I.2.1
In this study, we propose a fuzzy system for conducting short-term transactions in the forex market. The system is designed to enhance common strategies in the forex market using fuzzy logic, thereby improving the accuracy of transactions. Traditionally, technical strategies based on oscillator indicators have relied on predefined ranges for indicators such as Relative Strength Index (RSI), Commodity Channel Indicator (CCI), and Stochastic to determine entry points for trades. However, the use of these classic indicators has yielded suboptimal results due to the changing nature of the market over time. In our proposed approach, instead of employing classical indicators, we introduce a fuzzy Mamdani system for each indicator. The results obtained from these systems are then combined through voting to design a trading robot. Our findings demonstrate a considerable increase in the profitability factor compared to three other methods. Additionally, net profit, gross profit, and maximum capital reduction are calculated and compared across all approaches.
title Forex Trading Robot Using Fuzzy Logic
topic Systems and Control
Computational Engineering, Finance, and Science
Logic in Computer Science
I.2.1
url https://arxiv.org/abs/2507.06383