| Author(s) | Hindi A. AI-Hindi and Zayed F. AI-Hasan* |
| Affiliation | Department of Quantitative Methods, College of Business and Economics, *Department of Economics, King Saud University, A/-Qasseem Branch. Saudia Arabia |
| Title | A Neural Network Approach to Forecasting Stock Prices of Saudi Companies |
| Source | Journal of King Saud University. Administrative Sciences. Volume 14, No 1. (2002/1422) |
| Abstract | Over the past decade, the local Saudi stock market has witnessed a rising interest, which is due mainly to the increase in investment in local stocks. In addition, government's commitment to the privatization of its profitable public utilities (e.g., the communication and electrical services) has encouraged many investors to move their money from overseas to the local market. This paper examines the use of artificial neural networks as an emerging technique for forecasting weekly stock prices. Stock prices of seven different Saudi companies were used in the study to demonstrate the capabilities of this new technology. Several evaluation measures were used to evaluate the performance of neural networks in forecasting stock prices for the selected companies. The results showed superior performance of neural network technology which makes it a valuable tool for decision making in the area of investment. |
