Comparison of various fuzzy time series approaches to the prediction of the Istanbul Stock Exchange data

Fuzzy Time Series (FTS) models have been quite intensely proposed in recent years. FTS models have been widely applied to diverse fields such as enrollments, stocks, weather and etc., as they can handle prediction problem under uncertain circumstances in which data are incomplete or vague. In this study, two factor high order Fuzzy time series articles have been reviewed and their forecasting methods determined. Related methods have been compared and finally, based on knowledge of the current literature, the best two factor high order Fuzzy time series method have demonstrated.