Master’s Thesis at University of Basrah Examines Iraqi Stock Market Efficiency and Return Forecasting Using Artificial Intelligence
A master’s thesis at the College of Administration and Economics, University of Basrah, examined the assessment of informational efficiency and return forecasting in the Iraq Stock Exchange using GARCH models and neural networks.
The thesis, submitted by Ahmed Jalal Jaber, aimed to employ an approach combining statistical models and artificial intelligence techniques to analyze market efficiency and forecast returns.
The study analyzed weekly data on the returns of the Iraq Stock Exchange Index (ISX60) for the period from 2019 to 2025.
The findings showed that the market does not exhibit weak-form informational efficiency, with evidence of volatility effects and shock persistence. Neural networks also demonstrated superior performance in forecasting returns.
The study recommended enhancing transparency, developing infrastructure, and adopting artificial intelligence in risk management and investment decision-making.
Department of Media and Governmental Communication
