Tehran Stock Exchange Daily Index Forecasting By Adaptive Network-based Fuzzy Inference System

To be successful in financial market treading, it’s necessary to predict the future movement of market correctly. Most of professional traders use technical analysis to forecast future market price. In this paper we present a new Adaptive Network-based Fuzzy Inference System (ANFIS) model to forecast financial time series especially Tehran Stock Market Daily Index. Like real traders this method uses statistical based indicators to forecasting market movements. There are many indicators and oscillators for market analysis, but in this paper we examine the efficiency of these indicators especially in Tehran Stock Market Index and select four top rated indicators as ANFIS inputs. The results shows that this model is very useful in stock market decision support field and have an acceptable accuracy.

Keywords:

Adaptive Network-based Fuzzy Inference System (ANFIS) , Tehran Stock Market Daily Index , Financial Forecasting