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A Comparison Between Human Trading and Algorithmic Trading

In: Europe in the New World Economy: Opportunities and Challenges

Author

Listed:
  • Florentin Șerban

    (University of Bucharest
    Bucharest University of Economic Studies)

  • Bogdan-Petru Vrînceanu

    (Bucharest University of Economic Studies)

Abstract

This study presents a comparative analysis of human trading and algorithmic trading, focusing on the methodology employed and the resulting performance metrics. Methodologically, an algorithmic trading bot was developed using Pine Script 5, leveraging the Learning Vector Quantization (LVQ) algorithm model. The bot operated autonomously, executing predefined trading strategies without human intervention. In contrast, human trading involved manual decision-making within defined working hours. Key performance indicators such as net profit, total closed trades, win rate, and profit factor were analysed to assess the efficacy of each approach. The results revealed that while algorithmic trading offered benefits in terms of automation and efficiency, human trading demonstrated instances of superior profitability and adaptability, particularly during working hours. This study underscores the importance of integrating the strengths of both approaches to develop robust trading strategies that are adaptive and effective in navigating dynamic market conditions.

Suggested Citation

  • Florentin Șerban & Bogdan-Petru Vrînceanu, 2024. "A Comparison Between Human Trading and Algorithmic Trading," Springer Proceedings in Business and Economics, in: Luminita Chivu & Valeriu Ioan-Franc & George Georgescu & Ignacio De Los Ríos Carmenado & Jean Vasile (ed.), Europe in the New World Economy: Opportunities and Challenges, chapter 0, pages 141-154, Springer.
    • Handle: RePEc:spr:prbchp:978-3-031-71329-3_8
    DOI: 10.1007/978-3-031-71329-3_8
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