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Home > Archives > Volume 20, No 8 (2022) > Article

DOI: 10.14704/nq.2022.20.8.NQ22265

Pars Pharmaceutical Company Stock Price Forecast Utilizing Artificial Neural Networks and GMDH Shell Software

Sima Abolhassani Khajeh, Dr. Hossein Nasiri, Amirhossein Haddadi, Shafi Shafipouromrani

Abstract

Forecasting the process of the stock price is of a high importance. This forecasting is not an easy task due to a variety of factors. Utilizing artificial neural networks based on the GMHD Shell software which leads to the stock price forecast can be really useful. In this study, the price information has been used as a dependent variable and the transactions volume data, number of transactions, value of transactions and the overall index have been used as dependent variables. For this purpose, the variations from 2014 to 2020 (1530 days) have been taken into concentration. The results suggest that there is a meaningful relationship between the above mentioned variables and stock prices.

Keywords

Stock price forecast, Artificial Neural Networks, Overall Index, Index, Transactions volume, Number of Transactions, Value of Transactions

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