Impact of the Orientation of the Ordered Fuzzy Assessment on the Simple Additive Weighted Method

Piasecki, Krzysztof; Roszkowska, Ewa; Łyczkowska-Hanćkowiak, Anna

doi:10.3390/sym11091104

Cited by 10 publications

(7 citation statements)

References 23 publications

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“…Comparing the membership function charts, we see that OPV ambiguity of total portfolio, π, is less than OPV ambiguity of the rising securities' portfolio, π + ⊂ π, and the falling securities' portfolio, π − ⊂ π. In (Piasecki et al 2019), the mathematical theorem showing that the analogous result we get for any total portfolio containing simultaneously rising securities and falling securities was proven. In addition, it was proven that this effect is not revealed when we use FNs to determine imprecise PV.…”

Section: Discussionmentioning

confidence: 79%

Representation of Japanese Candlesticks by Oriented Fuzzy Numbers

Piasecki

Łyczkowska-Hanćkowiak

2019

Econometrics

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The Japanese candlesticks’ technique is one of the well-known graphic methods of dynamic analysis of securities. If we apply Japanese candlesticks for the analysis of high-frequency financial data, then we need a numerical representation of any Japanese candlestick. Kacprzak et al. have proposed to represent Japanese candlesticks by ordered fuzzy numbers introduced by Kosiński and his cooperators. For some formal reasons, Kosiński’s theory of ordered fuzzy numbers has been revised. The main goal of our paper is to propose a universal method of representation of Japanese candlesticks by revised ordered fuzzy numbers. The discussion also justifies the need for such revision of a numerical model of the Japanese candlesticks. There are considered the following main kinds of Japanese candlestick: White Candle (White Spinning), Black Candle (Black Spinning), Doji Star, Dragonfly Doji, Gravestone Doji, and Four Price Doji. For example, we apply numerical model of Japanese candlesticks for financial portfolio analysis.

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Section: Discussionmentioning

confidence: 79%

Representation of Japanese Candlesticks by Oriented Fuzzy Numbers

Piasecki

Łyczkowska-Hanćkowiak

2019

Econometrics

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“…The negotiation support systems based on fuzzy logic [27][28][29], fuzzy negotiation scoring systems [30][31][32][33][34], fuzzy negotiation strategies [35,36], and fuzzy protocols [37,38] were proposed. In some of the papers, the preferences of the system's user (who can be the principal or their agent) were expressed using the linguistic scale discussed in [31,39,40]. In line with Zadeh [41][42][43], the ratings corresponding to the linguistic terms were represented by fuzzy numbers (FN).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Representation of Principal’s Preferences in Inspire Negotiation Support System

Piasecki

Roszkowska

Wachowicz

et al. 2021

Entropy

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We consider the negotiation problem, in which an agent negotiates on behalf of a principal. Our considerations are focused on the Inspire negotiation support system in which the principal’s preferences are visualised by circles. In this way, the principal describes the importance of each negotiation issue and the relative utility of each considered option. The paper proposes how this preference information may be implemented by the agent for determining a scoring function used to support decisions throughout the negotiation process. The starting point of our considerations is a discussion regarding the visualisation of the principal’s preferences. We assume here that the importance of each issue and the utility of each option increases with the size of the circle representing them. The imprecise meaning of the notion of “circle size” implies that in a considered case, the utility of an option should be evaluated by a fuzzy number. The proposed utility fuzzification is justified by a simple analysis of results obtained from the empirical prenegotiation experiment. A novel method is proposed to determine trapezoidal fuzzy numbers, which evaluates an option’s utility using a series of answers given by the participants of the experiment. The utilities obtained this way are applied to determine the fuzzy scoring function for an agent. By determining such a common generalised fuzzy scoring system, our approach helps agents handle the differences in human cognitive processes associated with understanding the principal’s preferences. This work is the first approach to fuzzification of the preferences in the Inspire negotiation support system.

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“…In this paper, PV is modelled by oriented fuzzy numbers (OFN) defined in [13]. In recent years, OFNs have been increasingly used to describe and analyze economic [14,15], financial [16][17][18][19][20][21][22][23][24][25] and decision-making [26][27][28][29][30][31][32][33] problems. The application of OFNs in financial analysis may minimize imprecision risk, which was presented, for instance, in [32].…”

Section: Introductionmentioning

confidence: 99%

The Use of Trapezoidal Oriented Fuzzy Numbers in Portfolio Analysis

Łyczkowska-Hanćkowiak

2021

Symmetry

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Oriented fuzzy numbers are a convenient tool to manage an investment portfolio as they enable the inclusion of uncertain and imprecise information about the financial market in a portfolio analysis. This kind of portfolio analysis is based on the discount factor. Thanks to this fact, this analysis is simpler than a portfolio analysis based on the return rate. The present value is imprecise due to the fact that it is modelled with the use of oriented fuzzy numbers. In such a case, the expected discount factor is also an oriented fuzzy number. The main objective of this paper is to conduct a portfolio analysis consisting of the instruments with the present value estimated as a trapezoidal oriented fuzzy number. We consider the portfolio elements as being positively and negatively oriented. We test their discount factor. Due to the fact that adding oriented fuzzy numbers is not associative, a weighted sum of positively oriented discount factors and a weighted sum of negatively oriented factors is calculated and consequently a portfolio discount factor is obtained as a weighted addition of both sums. Also, the imprecision risk of the obtained investment portfolio is estimated using measures of energy and entropy. All theoretical considerations are illustrated by an empirical case study.

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Impact of the Orientation of the Ordered Fuzzy Assessment on the Simple Additive Weighted Method

Cited by 10 publications

References 23 publications

Representation of Japanese Candlesticks by Oriented Fuzzy Numbers

Representation of Japanese Candlesticks by Oriented Fuzzy Numbers

Fuzzy Representation of Principal’s Preferences in Inspire Negotiation Support System

The Use of Trapezoidal Oriented Fuzzy Numbers in Portfolio Analysis

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