This paper is devoted to the issue of forecasting financial ratios. The objective of the conducted research is to develop a predictive model with the use of an innovative methodology, i.e., fuzzy logic theory, and to evaluate its effectiveness. Fuzzy logic has been widely used in machinery,...

This paper evaluates several artificial intelligence and classical algorithms on their ability of forecasting the monthly yield of the US 10-year Treasury bonds from a set of four economic indicators. Due to the complexity of the prediction problem, the task represents a challenging test for the...

There are developed the approach and the model of identification and forecasting of financial indexes using methods of fuzzy logic theory taking into account a number of specific rules of price curve development from Elliott wave theory. The carried out analysis of forecasting results on real...

This article proposes the use of a fuzzy time series model based on neural networks that are intended to calculate the complicated fuzzy relationships among observations. The Taiwan stock exchange capitalisation weighted stock index is used as the forecasting target. Various parameters such as...

Fuzzy time series methods based on the fuzzy set theory proposed by Zadeh (1965) was first introduced by Song and Chissom (1993). Since fuzzy time series methods do not have the assumptions that traditional time series do and have effective forecasting performance, the interest on fuzzy time...