This paper explores multilayer artificial neural networks (ANNs) for predicting the price trend of the years of Iraqi Stock Market Index (ISX60). In an unstable economy and a politically unstable country such as Iraq, traditional forecasting techniques, such as ARIMA and linear models, fail to reflect the intricate and non-linear behavior of the market. The ANN model was constructed based on daily observations of the ISX60 index value and trading volume. The proposed model obtained a high R² of 0.92 and was better than classical models in terms of accuracy and error reduction. The forecast findings indicate a mild but rising ISX60 index moving from 2025 to 2029. This study sheds light on the benefits of ANN models in the context of developing markets, in particular that they can respond to volatile market environments and discloses information about the underlying patterns from financial time series data. The outcomes are helpful to the investors, analysts and policy makers who required also read financial forecasting and risk management tools in a turbulent economic environment like Iraq.
Keywords: Artificial Neural Networks (ANN), Iraq Stock market, price behavior
