investigating the market efficiency in tehran stock exchange through artificial intelligence

This study aimed to assess the level of efficiency in the iranian capital market, a domain where optimal resource allocation and micro and macro investments hold pivotal significance. the primary role of the capital market is to facilitate the circulation of capital and the efficient allocation of resources. the central inquiry in this context pertains to whether there exists a consistent pattern for determining stock prices. the question of market efficiency gains particular importance since understanding the factors influencing stock prices is critical in the stock market. it prompts the examination of whether there is a discernible regular pattern for stock price determination. consequently, this study undertook an investigation into the efficiency of the capital market in iran. to conduct this analysis, the researchers utilized daily data from the total index of the tehran stock exchange spanning the years 2008-2017. the test methodology employed artificial neural networks and time series training tests. the results of the tests unveiled weak efficiency in the tehran stock exchange. importantly, this inefficiency remained relatively unchanged compared to the initial period studied. in other words, within the tehran stock market, it is feasible to make predictions about returns through the application of artificial intelligence.