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Modeling stock market prices based on GMDH Neural Network: a case study for Iran
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Mohsen Mehrara *   , Ali Moeini , Mehdi Ahrari , Amir Hamony |
| , MMehrara@ut.AC.ir |
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Abstract: (23945 Views) |
| This paper examines the relative importance of alternative asset prices
and macro variables in the movements of stock prices in Iran, by
applying GMDH (Group Method of Data Handling) neural network
with genetic learning algorithms. The results imply that CPI, base
money, oil price and house price play an important role in explaining
the fluctuations of TEPIX index, whereas exchange rate and gold
prices do not appear to have considerable effect on stock prices. |
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| Keywords: GMDH, Stock Price Index, Iran economy |
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Full-Text [PDF 412 kb]
(10235 Downloads)
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Type of Study: Research |
Subject:
General
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