Forecasting Tehran Stock Exchange index using the industry index and economic
Stock price index reflects the overall state of the country's economy. Increase in the index means prosperity and improvement in economic conditions and its decrease indicates downturn and crisis. Artificial neural network based on GMDH Shell algorithm, which results in predicting stock price index, can be very useful. In this paper, it is tried to identify the factors affecting the stock exchange index by modeling and predicting the Tehran Stock Exchange Index based on a combination of genetic algorithms with neural network approach. In this paper, the aim is to predict the Tehran Stock Exchange Index with a look at the different industries index and the variables affecting it, by applying neural network based on genetic algorithm. For this purpose, the trend of changes during 2010 to 2013 was considered monthly. First, the theoretical literature is explained. Research literature is then discussed. After that, the neural network is described. The results of modeling and forecasting the stock index are provided, and finally in the end, the discussions and conclusions are summarized.
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