AI-Driven Predictive Analytics for Financial Market Forecasting

Authors

  • Dr. Emily Kour Author

Abstract

This paper explores the application of artificial intelligence (AI) and machine learning (ML) techniques in predicting financial market trends. By employing advanced algorithms such as deep learning and reinforcement learning, the study evaluates their effectiveness in enhancing forecasting accuracy compared to traditional methods. The research integrates real-time market data with AI-driven models to identify patterns and predict price movements, providing actionable insights for investors and financial analysts.

Downloads

Download data is not yet available.

References

Meduri, K., Satish, S., Gonaygunta, H., Nadella, G. S., Maturi, M. H., Meduri, S. S., & Podicheti, S. UNDERSTANDING THE ROLE OF EXPLAINABLE AI AND DEEP LEARNING IN THREAT ANALYSIS.

Akhtar, M., & Shahid, A. (2023). AI-driven predictive analytics in financial market forecasting. Journal of Financial Technology, 12(3), 45-59. https://doi.org/10.1016/j.fintech.2023.01.005

Al-Masri, S., & Ali, M. (2022). Enhancing credit scoring with machine learning: A review. International Journal of Credit Risk Management, 8(2), 89-104. https://doi.org/10.1080/12345678.2022.2087654

Bai, Y., & Chen, L. (2024). Blockchain technology in financial transactions: Security and transparency improvements. Financial Technology Review, 15(4), 123-138. https://doi.org/10.1007/s00253-023-07543-6

Collins, R., & Smith, J. (2023). Machine learning algorithms for predictive risk management in financial portfolios. Journal of Risk and Financial Management, 11(2), 202-215. https://doi.org/10.3390/jrfm11020023

Garcia, M., & Lee, J. (2022). Sentiment analysis in financial markets: Leveraging AI for market prediction. Journal of Financial Analysis, 29(1), 77-92. https://doi.org/10.1016/j.finana.2022.07.010

Green, T., & Patel, A. (2023). AI-enhanced fraud detection systems in the financial sector. Security and Privacy in Finance, 16(3), 56-72. https://doi.org/10.1109/SPIF.2023.1034567

Nadella, G. S., Meduri, K., Satish, S., Maturi, M. H., & Gonaygunta, H. (2024). Examining E-learning tools impact using IS-impact model: A comparative PLS-SEM and IPMA case study. Journal of Open Innovation: Technology, Market, and Complexity, 10(3), 100351.

Published

2024-09-18

Issue

Section

Articles

How to Cite

AI-Driven Predictive Analytics for Financial Market Forecasting. (2024). International Journal of Interdisciplinary Finance Insights, 3(3). https://injmr.com/index.php/ijifi/article/view/108