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Managing emotions and algorithms: the delicate equilibrium between artificial intelligence and behavioral finance
[Gérer les émotions et les algorithmes : l'équilibre délicat entre l'intelligence artificielle et la finance comportementale]

Author

Listed:
  • Sabhi Rajae

    (ENCGK - ENCG University Ibn Tofail of Kenitra, Morocco)

  • Abdelbaki Jamal Eddine

    (ENCGK - ENCG University Ibn Tofail of Kenitra, Morocco)

  • Taouab Omar

    (ENCGK - ENCG University Ibn Tofail of Kenitra, Morocco)

  • Eddaoudi Faissal

    (ENCGK - ENCG University Ibn Tofail of Kenitra, Morocco)

  • Abdelbaki Noureddine

    (ENCGK - ENCG University Ibn Tofail of Kenitra, Morocco)

Abstract

The paper takes a novel tack by suggesting artificial intelligence (AI) as a way to lessen behavioral biases in the process of making financial decisions. The paper explores how AI might assist avoid behavioral biases among financial planners and provide more effective investment recommendations, based on theoretical research that identifies these flaws. The expanding efficacy of AI is examined in order to overcome confirmation and hindsight biases, particularly via supervised and unsupervised learning. By developing a conceptual framework, outlining potential outcomes, and theoretically examining the relationships between behavioral finance and AI, the technique takes a theoretical approach. The theoretical technique highlights the necessity for conceptual exploration in the developing area of artificial intelligence in finance, which supports this approach even if it has limits due to the lack of empirical evidence.

Suggested Citation

  • Sabhi Rajae & Abdelbaki Jamal Eddine & Taouab Omar & Eddaoudi Faissal & Abdelbaki Noureddine, 2024. "Managing emotions and algorithms: the delicate equilibrium between artificial intelligence and behavioral finance [Gérer les émotions et les algorithmes : l'équilibre délicat entre l'intelligence a," Post-Print hal-04644322, HAL.
    • Handle: RePEc:hal:journl:hal-04644322
    DOI: 10.5281/zenodo.12705888
    Note: View the original document on HAL open archive server: https://hal.science/hal-04644322
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    References listed on IDEAS

    as
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