Scalper Major: A Computational Solution for Automated Trading in High Volatility Environments

• José Jeovane R. Cordeiro IFMA / UFPI
• Arlino Henrique M. de Araújo UFPI
• Guilherme A. Avelino UFPI

DOI: https://doi.org/10.5753/sbsi.2026.248290

Resumo

Research Context: The foreign exchange (Forex) market is the largest and most liquid in the world, characterized by high volatility and continuous operation. In this environment, human decision-making is often compromised by emotional biases and the limited ability to process large amounts of information in real time. Scientific and/or Practical Problem: Traditional trading strategies have weaknesses, including delayed signals and a lack of robust risk metrics. Furthermore, many existing studies in the literature focus only on cumulative return, neglecting the risk-return trade-off and practical applicability. Proposed Solution and/or Analysis: This work presents Scalper Major, an automated trading system designed to operate consistently in the Forex market. Its modular architecture integrates technical and managerial heuristics, as well as strict risk and capital management mechanisms. Related IS Theory: The research is based on the principles of information systems, applied to automated decision-making, aligning technical indicators, computational heuristics, and financial metrics as reliable support tools for investors. Research Method: The system was implemented in MQL5 on the MetaTrader 5 platform. The evaluation was conducted through eight-year backtests on four major currency pairs, taking into account commissions, execution delays, and various market scenarios. Summary of Results: With an initial capital of $20,000.00, Scalper Major achieved significant results: a net profit of $751,533.23, a win rate of 82.54%, and a maximum drawdown of 9.43%. The Sharpe Ratio of 1.63 demonstrates superior risk-return efficiency compared to related studies. Contributions and Impact to IS area: The study, in addition to proposing an operational tool, presents a methodological advancement by creating a novel compilation of the main evaluation indicators for automated trading systems.

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