The Impact of Artificial Intelligence Tools on the Weak-Form Efficiency of the Saudi Stock Market

Abstract

This study aims to test the weak-form efficiency and analyse the extent to which the spread of modern artificial intelligence (AI) tools has impacted this level of efficiency in the Saudi stock market. To achieve this goal, the study period was divided into two timeframes: the first from January 2019 to December 2022, representing the period before the emergence of AI tools; and the second from January 2023 to December 2024, representing the period following the widespread use of AI applications (e.g., ChatGPT).
The study used the daily return series of the Tadawul All Share Index (TASI) and applied statistical tests including the Autocorrelation Function (ACF), the Runs Test, and the Variance Ratio Test to examine the random walk hypothesis in each period independently. The statistical test results revealed clear differences between the two periods. In the first period (2019-2022), the random walk hypothesis was rejected, as the results showed statistically significant autocorrelation in index returns, indicating that the market was not weak-form efficient during that time. In contrast, in the second period (2023-2024), the random walk hypothesis was not rejected, as the tests did not find statistically significant relationships between past and current returns.
Overall, the study’s findings suggest an improvement in the weak-form efficiency of the Saudi market during the 2023-2024 period, which coincides with the widespread use of AI tools among traders. Accordingly, the study proposes that the adoption of these tools may be one of the factors contributing to enhanced market efficiency,