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A hybrid intelligent model using technical and fundamental analysis to forecasting stock price index
Shavandi, H
A hybrid intelligent model using technical and fundamental analysis to forecasting stock price index
Shavandi, H ; Sharif University of Technology | 2010
464
Viewed
- Type of Document: Article
- Publisher: 2010
- Abstract:
- In this paper we develop a hybrid forecasting model which combines artificial intelligence and technical analysis to predict short-term stock price index. The results show that using technical indices as neural network's inputs yields good performance in forecasting short-term prices, but this model cannot predict long-term prices well. To overcome this shortcoming we have exploited a fuzzy inference system based on analyzing the historical effects of macro economic variables on the stock markets' indices. Our forecasting models differ from the other ones in two main aspects: the first one is analyzing previous macroeconomics trends in order to build a Mamdani FIS and the second one is providing two different techniques for short-term and long-term predictions. These models allow decision makers to forecast prices by using minimum data and calculations. The good performance of the proposed model is confirmed by real stock market data
- Keywords:
- Forecasting ; Fundamental analysis ; Fuzzy inference system ; Neural networks ; Stock price index ; Technical analysis
- Source: Economic Computation and Economic Cybernetics Studies and Research ; Volume 44, Issue 2 , 2010 , Pages 95-112 ; 0424267X (ISSN)
- URL: http://en.journals.sid.ir/ViewPaper.aspx?ID=175968
