Using volatility of stock price index by investor caused prediction of stock price
index to be considered as one of the most controversial topics in finance. This
study have been conducted using two artificial neural network and hybrid
models of genetic algorithm-neural network as a successful model to predict the
volatility of stock price index in Tehran stock exchange. Inputs to both models
are nine indicators of guidance relating to eleven periods of 6-month from 2005
to 2010. Hybrid model of ANN-GA and ANN model were able to predict the
volatility of the stock price index for 11 periods, on average, 96.34% and
89.80% respectively and this study showed that genetic algorithm combination
with other models create an effective model to predict artificial intelligence
model optimization.
