Enhancing Analytical Precision in Company Earnings Reports through Neurofuzzy System Development: A Comprehensive Investigation
Matkarimov B. Barlybayev A. Karimov D.
2024Hindawi Limited
Journal of Electrical and Computer Engineering
2024#2024
The object of research is the fundamental and technical indicators of companies after the release of the earnings report. This study attempts to address the issue of understanding the impact of fundamental and technical analysis indicator dynamics on profits and loss news releases. This research provides an in-depth analysis of stock price forecasting models, focusing on the influence of earning report seasons as catalysts for stock price growth. The study explores the relationship between key financial indicators, including earnings per share (EPS), revenue, and the maximum price observed in the 52-week period of the previous year (MaxW52). A trading algorithm is developed based on the adaptive neurofuzzy inference system (ANFIS). Through a comprehensive analysis of the neural networks training sample, it is concluded that abnormally large negative indicators have a profound impact on traders emotional reactions. This results leads to a hypothesis for further research, suggesting that report indicators may be processed by computational algorithms, potentially including artificial intelligence (AI). Consequently, the emergence of emotional trading robots managed by investment funds becomes a crucial area for investigation. Understanding the behavior of these algorithms enables proactive decision-making, allowing traders to leverage their knowledge and sell-purchased securities to these algorithms before their transactions occur. The implications of this research shed light on the evolving landscape of trading strategies and the role of emotionality in financial markets.
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Department of Artificial Intelligence Technologies, L.N. Gumilyov Eurasian National University, Astana, 01000000, Kazakhstan
Higher School of Information Technology and Engineering, Astana International University, Astana, 01000000, Kazakhstan
Department of Artificial Intelligence Technologies
Higher School of Information Technology and Engineering
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