Intuitionistic fuzzy rule-base evidential reasoning with application to the currency trading system on the Forex market

In this paper, the application of the intuitionistic fuzzy rule-base evidential reasoning (IFRBER) to the development of a new optimized automated trading system (ATS) for the Forex market is presented. The used IFRBER approach represents the intuitionistic fuzzy sets in the framework of the evidence theory that allows us to avoid the revealed drawbacks of the IFS operational laws and enhance the overall performance of the IFRBER approach. It is shown that the IFRBER approach extracts from an analyzed system considerably more of useful for the decision making information than the usual fuzzy rule-base evidential reasoning (FRBER). Then based on the IFRBER, a new approach to make the justified transaction buying and selling decisions was proposed. This approach was used to develop a new optimized ATS for the Forex market. It is shown that due to the ability of a new approach to use more of useful information that present implicitly in the problem formulation than the proposed earlier usual fuzzy rule-base evidential reasoning method, the developed ATS provides a considerably more profitable and comfortable (with a higher percent of winning trades and with low risks) trading than the earlier developed ATS. (C) 2022 Elsevier B.V. All rights reserved.

Automated summary

This paper presents the application of the intuitionistic fuzzy rule-base evidential reasoning (IFRBER) in developing a new optimized automated trading system (ATS) for the Forex market. The IFRBER approach represents intuitionistic fuzzy sets within the framework of the evidence theory, addressing the limitations of the IFS operational laws and improving overall performance. The study demonstrates that the IFRBER approach extracts more useful information for decision making compared to the usual fuzzy rule-base evidential reasoning. Based on the IFRBER approach, a new method for making justified buying and selling decisions is proposed, leading to the development of a highly profitable and low-risk optimized ATS.