Forecasting the Moroccan Stock Market: A Theoretical Approach Integrating Macroeconomic and Sentiment Data through Deep Learning

Imad Talhartit, Sanae Ait Jillali () and Mounime El Kabbouri
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Imad Talhartit: Université Hassan 1er [Settat], Ecole Nationale de Commerce et Gestion - Settat, Laboratory of Finance, Audit and Organizational Governance Research
Sanae Ait Jillali: Université Hassan 1er [Settat], Ecole Nationale de Commerce et Gestion - Settat, Laboratory of Finance, Audit and Organizational Governance Research
Mounime El Kabbouri: Université Hassan 1er [Settat], Ecole Nationale de Commerce et Gestion - Settat, Laboratory of Finance, Audit and Organizational Governance Research

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Abstract: In today's data-driven economy, predicting stock market behavior has become a key focus for both finance professionals and academics. Traditionally reliant on historical and economic data, stock price forecasting is now being enhanced by AI technologies, especially Deep Learning and Natural Language Processing (NLP), which allow the integration of qualitative data like news sentiment and investor opinions. Deep Learning uses multi-layered neural networks to analyze complex patterns, while NLP enables machines to interpret human language, making it useful for extracting sentiment from media sources. Though most research has focused on developed markets, emerging economies like Morocco offer a unique context due to their evolving financial systems and data limitations. This study takes a theoretical and exploratory approach, aiming to conceptually examine how macroeconomic indicators and sentiment analysis can be integrated using deep learning models to enhance stock price prediction in Morocco. Rather than building a model, the paper reviews literature, evaluates data sources, and identifies key challenges and opportunities. Ultimately, the study aims to bridge AI techniques with financial theory in an emerging market setting, providing a foundation for future empirical research and interdisciplinary collaboration.

Keywords: Stock Price Prediction; Deep Learning; Natural Language Processing (NLP); Sentiment Analysis; Macroeconomic Indicators; Emerging Markets; Moroccan Financial Market (search for similar items in EconPapers)
Date: 2025-05
New Economics Papers: this item is included in nep-ara, nep-big, nep-cmp, nep-fdg, nep-fmk and nep-for
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Published in International journal of management sciences and business research, 2025, 14 (5), pp.10-23. ⟨10.5281/zenodo.15576354⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05094029

DOI: 10.5281/zenodo.15576354

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