Event-Driven Investment Recommendations Using Synthesized Financial News for Stock Market

Sana Sajid (), Sahar Arshad (), Nikhar Azhar (), Huma Ameer () and Seemab Latif ()
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Sana Sajid: National University of Sciences and Technology (NUST)
Sahar Arshad: National University of Sciences and Technology (NUST)
Nikhar Azhar: National University of Sciences and Technology (NUST)
Huma Ameer: National University of Sciences and Technology (NUST)
Seemab Latif: National University of Sciences and Technology (NUST)

A chapter in New Perspectives and Paradigms in Applied Economics and Business, 2025, pp 93-104 from Springer

Abstract: Abstract The stock market is subjected to the impact of multiple factors, such as news events, economic data, and investor sentiments. Nevertheless, the intricate relationship between news and stock prices contains hidden trends contributing toward the trading recommendations. This research investigates the relationship between news events and stock market trends by utilizing features specifically designed to address the unique market dynamics of the Pakistan Stock Exchange. The findings from our study highlight a notable ratio of 1:2 between positive and negative news events, emphasizing the significant impact of negative news on market volatility. This work is therefore a step forward toward the automation of data-driven well-informed trading decisions.

Keywords: Financial news; Event extraction; Pakistan Stock Exchange (PSX); Trading recommendations; Natural language processing (NLP) (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-031-77363-1_7

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DOI: 10.1007/978-3-031-77363-1_7

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