REVIEW OF AI TECHNIQUES IN FINANCIAL FORECASTING: APPLICATIONS IN STOCK MARKET ANALYSIS

Authors

  • David Iyanuoluwa Ajiga Independent Researcher, Chicago, Illinois, USA
  • Rhoda Adura Adeleye Information Technology & Management, University of Texas, Dallas, USA
  • Onyeka Franca Asuzu Dangote Sugar Refinery Plc, Lagos, Nigeria.
  • Oluwaseyi Rita Owolabi Independent Researcher, Indianapolis Indiana, USA
  • Binaebi Gloria Bello Kings International School, Port-Harcourt, Rivers State, Nigeria
  • Ndubuisi Leonard Ndubuisi Spacepointe Limited Rivers State, Nigeria

DOI:

https://doi.org/10.51594/farj.v6i2.784

Abstract

This scholarly inquiry delves into the burgeoning intersection of Artificial Intelligence (AI) and financial forecasting, particularly within the stock market domain. The study's backdrop is set against the rapid evolution of AI techniques, which have significantly altered the landscape of financial analysis. The primary aim is to dissect and evaluate the impact of AI on stock market predictions, juxtaposing its capabilities against traditional forecasting methods while navigating through the ethical and practical complexities inherent in AI implementation. The scope of the paper encompasses a comprehensive review of AI's evolution in financial analysis, its comparative effectiveness, and the sector-specific applications in stock markets. Methodologically, the study employs a systematic review of existing literature, focusing on peer-reviewed articles that shed light on the performance, challenges, and future prospects of AI in stock market forecasting. The findings reveal AI's profound potential in enhancing market efficiency and volatility understanding, albeit tempered by challenges such as data quality issues, model interpretability, and the need for robust regulatory frameworks. The main conclusions underscore AI's transformative role in financial forecasting, highlighting its ability to analyze vast datasets and predict market trends with heightened accuracy. However, the study also acknowledges the limitations within AI models, emphasizing the necessity for a balanced approach that integrates AI with traditional methods and continuous algorithmic refinement. Recommendations advocate for collaborative efforts between technologists, ethicists, and financial experts to develop ethically sound, transparent, and effective AI applications. In summary, this paper offers a panoramic view of AI's role in financial forecasting, serving as a guidepost for future explorations in this field. It underscores the immense possibilities and intricate challenges of AI in the dynamic landscape of stock market analysis, paving the way for a new era of data-driven decision-making in finance.

Keywords:  Artificial Intelligence, Financial Forecasting, Stock Market Prediction, Machine Learning, Ethical Considerations, Regulatory Frameworks.

Published

2024-02-14

Issue

Section

Articles