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Forecasting Stock prices of banks using artificial neural networks (GMDH) and response surface methodology

Publish Year: 1398
Type: Conference paper
Language: English
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FAMA02_386

Index date: 12 February 2020

Forecasting Stock prices of banks using artificial neural networks (GMDH) and response surface methodology abstract

According to the importance of shares and investment forecasts for those in the capital market and insufficient analysis of financial information regardless of other variables and parameters as well as the economic data, behavioral and social sciences od time series which are effective in banks stock price, investors are encouraged toward additional tools and available soft wares. In this study modeling and forecasting stock prices of banks using artificial neural networks (GMDH) and response surface methodology (RSM) is accomplished. Obtained results showed that performance of the models in processing simultaneous effects of turnover, value of transactions and number of transactions on bank stock price is excellent.

Forecasting Stock prices of banks using artificial neural networks (GMDH) and response surface methodology Keywords:

banks stock prices forecasting , GMDH neural network , response surface methodology (RSM)

Forecasting Stock prices of banks using artificial neural networks (GMDH) and response surface methodology authors

Erfan Mohammadi

Master of Accounting, Shahid Beheshti University