Stock Price Forecasting through Using ANN and ARIMA Techniques: A Case Study of Pars Petroleum Company
Author(s):
Abstract:
Stock exchange market is one of the important ways to investment. In this market, the investors are looking for the best securities to maximize the profit. Therefore, forecasting the stock price of next day has a vital role in purchasing such securities. To do this, application of Neural Networks financial forecasting has become very popular over the last few years. In this paper, for predicting the next day's close stock price of Pars Petroleum Company, Artificial Neural Network (ANN) and Autoregressive Integrated Moving Average (ARIMA) will be developed, used and compared. The data are daily collected and analyzed during 2009-2011. The findings indicate that forecasting the price by Neural Network is superior to ARIMA due to its less error coefficients and high explanatory ability.
Keywords:
Language:
Persian
Published:
Quarterly Journal of Economic Modelling, Volume:6 Issue: 2, 2012
Pages:
105 to 121
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