Automation of strategies in the futures market as a vector for mitigating cognitive biases and optimizing performance: a praxiological analysis
Automation of strategies in the futures market as a vector for mitigating cognitive biases and optimizing performance: a praxiological analysis
DOI:
https://doi.org/10.51473/rcmos.v1i2.2025.2186Keywords:
Algorithmic Trading. Behavioral Finance. Futures Market. Risk Management. Automation.Abstract
The contemporary financial market, characterized by high-frequency trading and the intrinsic volatility of derivatives, imposes severe challenges on human decision-making, often distorted by cognitive biases and emotional limitations. This scientific article proposes an exhaustive, technical, and multidisciplinary analysis of the implementation of automated trading systems (investment robots) in the B3 futures market, specifically in index and dollar contracts. The methodology adopted is based on a systematic bibliographic review and empirical data analysis, correlating the postulates of Fama's Efficient Market Hypothesis (1970) with the findings of Kahneman and Tversky's Behavioral Finance (1979). The study is structured into three thematic axes of extremely high density, dissecting everything from market microstructure and execution latency, through economic psychology applied to risk management, to the architecture of algorithms for return consistency. The results demonstrate that automation eliminates behavioral asymmetry, standardizes the execution of technical setups, and maximizes the Sharpe Ratio of portfolios. It is concluded that the modern trader must transition from a manual operator to a systems manager, using technology as a protective barrier against human fallibility and as a lever for financial scalability.
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References
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Copyright (c) 2025 Cezario Soares da Silva (Autor)
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