Variability analysis and control of financial sector: ise-30 index on fuzzy control application diagrams

It is well-known that statistical process control pproach is very useful to improve product quality. In production environment, control charts are one of the most widely used tools applied to determine whether a process is statistically in control or not. In this study, in addition to the traditional Shewhart control charts, it is purposed to develop a fuzzy control chart based on individual mesasurements. It will be helpful to achieve efficient studies under conditions with uncertainty by getting a new viewpoint to the classical set theory. Determining variability in process provides large gains in terms of costs and quality. Considering the costs that caused by delay in defining the variability, it is obvious to see the importance of determining the variation correctly and quickly in a process. In this study, after providing brief description of ISE-30 Index return volatility have been tested.Firstly, in order to determine the ISE-30 Index price based on its lagged value, simple exponential smoothing method which is an artificial intelligence method, have been applied of these methods. To this end, a fuzzy model based on control chart developped for determining the variation in process. The performance of fuzzy model has been control charts are compared and the results obtained are evaluated.