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Transformative Impact of Deep Learning in Stock Market Decision-Making: A Comparative Study of Convolutional Neural Networks

Author

Listed:
  • Hammed Esa

    (Department of Business Administration, International American University Los Angeles, California, USA)

  • Mohammad Anisur Rahman

    (Department of Marketing & Business Analytics, Texas A&M University-Commerce, USA)

  • Md Abu Sufian Mozumder

    (College of Business, Westcliff University, Irvine, California, USA)

  • Nisha Gurung

    (Department of Business Analytics, Gannon University, Erie, Pennsylvania, USA)

  • Mohammed Nazmul Islam Miah

    (Department of Management Science and Quantitative Methods, Gannon University, USA)

  • Md Murshid Reja Sweet

    (Department of Management Science and Quantitative Methods, Gannon University, USA)

  • Mohammad Kawsur Sharif

    (Department of Business Administration and Management, Washington University of Virginia, USA)

  • Md Rasibul Islam

    (Department of Management Science and Quantitative Methods, Gannon University, USA)

  • Md Nasiruddin

    (Department of Management Science and Quantitative Methods, Gannon University, USA)

  • Md Sanowar Hossain Sabuj

    (Department of Marketing & Business Analytics, Texas A&M University-Commerce, USA)

Abstract

This research delves into the transformative impact of deep learning, specifically Convolutional Neural Networks (CNNs) such as VGG16, ResNet50, and InceptionV3, on organizational management and business intelligence. The study follows a comprehensive methodology, emphasizing the importance of high-quality datasets in leveraging deep learning for enhanced decision-making. Results demonstrate the superior performance of CNN models over traditional algorithms, with CNN (VGG19) achieving an accuracy rate of 89.45%. The findings underscore the potential of deep learning in extracting meaningful insights from complex data, offering a paradigm shift in optimizing various organizational processes. The article concludes by emphasizing the significance of investing in infrastructure and expertise for successful CNN integration, ensuring ethical considerations, and addressing data privacy concerns. This research contributes to the growing discourse on the application of deep learning in organizational management, providing a valuable resource for businesses navigating the dynamic landscape of the global market.

Suggested Citation

  • Hammed Esa & Mohammad Anisur Rahman & Md Abu Sufian Mozumder & Nisha Gurung & Mohammed Nazmul Islam Miah & Md Murshid Reja Sweet & Mohammad Kawsur Sharif & Md Rasibul Islam & Md Nasiruddin & Md Sanowa, 2024. "Transformative Impact of Deep Learning in Stock Market Decision-Making: A Comparative Study of Convolutional Neural Networks," Journal of Business and Management Studies, Al-Kindi Center for Research and Development, vol. 6(3), pages 28-34, May.
    • Handle: RePEc:alk:jbms00:v:6:y:2024:i:3:id:7209
    DOI: 10.32996/jbms.2024.6.3.4
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