Master's Thesis at the University of Basra Examines Information Efficiency and Return Forecasting in the Iraq Stock Exchange:

A master's thesis at the College of Administration and Economics, University of Basra, examined information efficiency and return forecasting in the Iraq Stock Exchange using GARCH models and neural networks.

The thesis, submitted by student Ahmed Jalal Jaber, aimed to employ a dual methodology combining GARCH models to assess information efficiency and artificial intelligence techniques to predict returns.

The thesis included an analysis of weekly data on the returns of the Iraq Stock Exchange Index (ISX60) from 2019 to 2025. The thesis concluded that the Iraqi market lacks information efficiency, exhibiting significant volatility and shock memory, and that neural networks are superior in predicting returns.

The thesis recommended developing the market's infrastructure, enhancing transparency, and adopting artificial intelligence techniques in risk management and investment decision-making.