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EN
Oriented fuzzy numbers are useful in portfolio management since they convey information regarding uncertainty and imprecision when considering financial markets. One may apply a fuzzy discount factor and an imprecise present value in the form of a trapezoidal oriented fuzzy number. An investor can obtain recommendations on individual stocks (buy, sell, accumulate, reduce). Analogous recommendations are also issued by experts. In such cases, recommendations are mostly based on available data and expert’s knowledge and experience. The purpose of the paper is to present a procedure for comparing the accuracy of both types of recommendations. Also, the real impact the recommendations have on potential changes in portfolio composition in trading-related industries is considered. The research uses quotations from companies from the trading sector of the Warsaw Stock Exchange (WSE). Theoretical considerations are presented in the form of an empirical case study.
2
Content available Modifications of order scales for assessing debtors
EN
In previous research, the Extended Order Scale (EOS) dedicated to risk assessment was analysed. It was characterised by a Numerical Order Scale (NOS) evaluated by trapezoidal oriented fuzzy numbers (TrOFNs). However, the research showed that EOS with two-stage orientation phases, was too complicated. Therefore, the main aim of our paper is to simplify a Complete Order Scale (COS) to a zero- or one-stage order scale and a hybrid approach. For this purpose, a way to calculate the scoring function is presented. The results show that changes in the COS structure influence the values of a scoring function. Replacing just one linguistic indicator gives different results. Another finding of the research is the method’s flexibility that allows an expert to individually choose the most suitable COS. The research proves that the boundary between various linguistic labels cannot be precisely defined. However, knowledge of a formal COS structure allows it to be transformed into a less complex one.
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