Title of article :
Forecasting Stock Market Using Wavelet Transforms and Neural Networks: An integrated system based on Fuzzy Genetic algorithm (Case study of price index of Tehran Stock Exchange)
Author/Authors :
Anvary Rostamy، Ali Asghar نويسنده , , Mousazadeh Abbasi، Noraddin نويسنده , , Aghaei، Mohammad Ali نويسنده , , Moradzadeh Fard، Mahdi نويسنده ,
Issue Information :
فصلنامه با شماره پیاپی سال 2012
Pages :
12
From page :
83
To page :
94
Abstract :
Abstract The jamor purpose of the present research is to predict the total stock market index of Tehran Stock Exchange, using a combined method of Wavelet transforms, Fuzzy genetics, and neural network in order to predict the active participations of finance market as well as macro decision makers. To do so, first the prediction was made by neural network, then a series of price index was decomposed by wavelet transform and the prediction made by neural network was repeated, finally, the extracted pattern from the neural network was stated through discernible rules using Fuzzy theory. The main focus of this paper is based on a theory in which investors and traders achieve a method for predicting stock market. Concerning the results of previous researches, which confirmed the relative superiority of non-linear models in price index prediction, an appropriate model has been offered in this research by combining the non-linear methods such as Wavelet transforms, Fuzzy genetics, and neural network, The results indicated the superiority of the designed system in predicting price index of Tehran Stock Exchange.
Keywords :
Fuzzy Theory and Fuzzy Genetic System , genetic algorithm , Wavelet Transforms , Artificial neural network
Journal title :
International Journal of Finance, Accounting and Economics Studies
Serial Year :
2013
Journal title :
International Journal of Finance, Accounting and Economics Studies
Record number :
2404267
Link To Document :
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