Investigating the Market Efficiency in Tehran Stock Exchange through Artificial Intelligence
الموضوعات :mohammad jouzbarkand 1 , Hossein Panahian 2
1 - Department of Accounting, Kashan Branch, Islamic Azad University, Kashan, Iran.
2 - Department of Accounting, Kashan Branch, Islamic Azad University, Kashan, Iran.
الکلمات المفتاحية: Artificial Neural Network, Total Share Index, market efficiency, Time series,
ملخص المقالة :
This study was an attempt to evaluate the progress of capital market efficiency in Iran. Optimal resource allocation and micro and macro investments play a key role in the capital market. The capital market's main task is to circulate capital and allocate resources efficiently and optimally. The main task of this market is to flow capital and allocate resources efficiently and optimally. Is there a regular pattern for determining the stock price? Market efficiency gains significance as it is important to know what factor or factors are effective in determining the price of the stock in the stock market or whether there is a regular pattern for determining the price of a stock. Thus, this study examined the efficiency of the capital market in Iran. In this regard, the researchers used the daily data of the total index of the Tehran Stock Exchange for 2008-2017. Artificial neural network and time series training tests were used to perform the test. The test results showed weak efficiency in the Tehran Stock Exchange and this inefficiency did not change significantly compared to the first period. In other words, in the Tehran Stock Market, one can predict returns using artificial intelligence.
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