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Author

Muhammad Al-Qurishi

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Open access 2026

Empirical Evaluation of Language Models for Arabic Financial Sentiment Analysis: A Comparative Study of Pretrained and General Large Language Models

This study presents a comparative study on the effectiveness of large and pre-trained language models in analyzing sentiment in Arabic financial news. While sentiment analysis using AI has advanced significantly in English-language finance, similar progress in Arabic remains limited. Most existing Arabic models, such a...

Abdullah Almusned, Mohammad Mehedi Hassan, Muhammad Al-Qurishi et al. · 0 citations
Open access 2026

Predicting Next-Trading-Session Stock Movements from Arabic Corporate Announcements: A Hybrid Transformer-Boosted Ensemble

Predicting next-day stock movements from corporate announcements is a complex task, especially in markets where financial text is published in low-resource languages such as Arabic. In this study, we develop a hybrid, multimodal forecasting framework designed to capture both the semantic depth of Arabic announcements a...

Abdullah Almusned, Mohammad Mehedi Hassan, Muhammad Al-Qurishi et al. · 0 citations

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