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| Article name |
Reducing Excessive Loss Risk with Grid Trading and Target Based Position Closure via Trading Bots
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| Article type |
Research article
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| Authors |
Alongkot Gongmanee(1), Thitikorn Rueanmon(1), Paween Khoenkaw(1), Kongkarn Dullayachai(1) and Somnuek Sinthupuan(1*)
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| Office |
Computer Science Department, Faculty of Science, Maejo University(1) *Corresponding author: somnuk@mju.ac.th
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| Journal name |
Vol. 12 No.1 (2026): January - April
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| Abstract |
This research aims to implement multi-level trading at predetermined prices using grid trading strategies, enabling profit generation from price movements within defined ranges without requiring constant market monitoring or directional predictions. The study developed three algorithmic trading approaches: 1) Buy-only grid trading, 2) Two-way (Buy & Sell) grid trading, and 3) Two-way grid trading with targeted position closure to prevent excessive losses. Back tested on USOUSD 4-hour data from January 1, 2024, to July 4, 2025 (denominated in cents), the analysis revealed that the two-way grid strategy with position closure delivered optimal performance - generating total returns of 4,779.20 cents. This outperformed the basic two-way grid strategy by 70% and significantly surpassed the buy-only grid strategy, while maintaining controlled risk exposure (Maximum Drawdown of 1.62%). The standard two-way grid achieved respectable results (2,800.18 cents) with tight drawdown control (1.15%), though remained inferior to the enhanced version. Notably, the buy-only strategy produced negative returns (-255.9 cents) despite its high 93.88%-win rate, demonstrating the critical importance of integrated risk management systems in grid trading methodologies. The superior performance of the position-closure enhanced strategy highlights how automated exit mechanisms can optimize grid trading effectiveness while controlling downside risk.
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| Keywords |
FOREX; Grid Strategy; Target Based Position Closure; USOUSD; Trading robot
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| Page number |
99-118
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| ISSN |
ISSN 3027-7280 (Online)
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| DOI |
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| ORCID_ID |
0000-0003-1461-1243
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| Article file |
https://mitij.mju.ac.th/ARTICLE/R69006.pdf
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