Investment Decision Support Based on Interval Type-2 Fuzzy Expert System

The decision-making process on investing in financial markets is a very complex and difficult task, mainly due to the chaotic behavior high uncertainty development of prices investment instruments. For this reason, are increasingly using means artificial intelligence, namely fuzzy logic, which able capture nonlinear behavior.Fuzzy logic provides way draw definitive conclusions from vague, ambiguous, or inaccurate information.However, there some drawbacks associated with type-1 so type-2 comes forward, can work greater uncertainty. Type-2 works new third dimension set that additional degrees freedom allows model numerical linguistic uncertainties directly. paper applies stock market aim create simple understandable for deciding instruments, important investors area. proposed uses return, risk, dividend total expense ratio ETF as input variables. created system generate aggregated models certain number language rules, investor understand model. Using lead more realistic accurate results than logic.