Type-2 Fuzzy Expert System Approach for Decision-Making of Financial Assets and Investing under Different Uncertainty

Extensive research results of stock market time series using classical fuzzy sets (type-1) are available in the literature. However, type-1 cannot fully capture uncertainty associated with developments due to their limited descriptiveness. This paper fills a scientific gap and focuses on type-2 logic applied markets. Type-2 may include additional resulting from unclear, uncertain, or inaccurate financial data through which model inputs calculated. Here we propose four methods based logic, differ level contained compared model. The case study aims create support investment decisions Exchange-Traded Funds (ETFs) listed international equity created models classic Based comparison, it can be said that dual is able better describe provides more accurate outputs. reflect capability effectiveness approach proposed this document. performance decreases inclusion increasing sets. For further research, would appropriate examine different levels input parameters themselves monitor such modified