Scientific Journal of KubSAU

Polythematic online scientific journal
of Kuban State Agrarian University
ISSN 1990-4665
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Shevchenko Igor Viktorovich

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professor

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Kuban State University
   

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Articles count: 1

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ESTIMATION OF A COMPANY CREDIT STATUS BASED ON THE FIVE-FACTOR “ALTMAN” MODEL USING FUZZY SETS AND SIMULATION

abstract 1081504022 issue 108 pp. 334 – 356 30.04.2015 ru 1267
In this article we propose a method that uses the apparatus of the theory of fuzzy sets, together with the five-factor model of Altman in assessing the creditworthiness of an enterprise. Altman's model works in two ways: It applies the root mean square (RMS) integral approximation for the exact calculation of quantitative assessment of creditworthiness (probability of bankruptcy), and using the device of fuzzy sets for ordered sets by the degree of confidence in the resulting probability. In this paper we conducted simulation procedure for the credit assessment and showed the capabilities of the model. The model input parameters , forms system inputs (input variables), allowing you to get the value of the parameter z of Altman. With the help of Altman's model, approximating function L6, the decision function I(p) and the algorithm for calculating preference  we obtain the number of the set i to which belongs a number of ordered sets as fuzzy logic . On the selected simulation parameters, stable statistics can be obtained. Altman's model with the use of computational function allows real values of the input parameters of the enterprise replaced by random values of the simulation model. This technique allows, as shown by the results of computational experiments, the creditor to obtain additional information on the creditworthiness of the investigated enterprise and make a more informed conclusion about its financial condition, which speeds up the decision on the possibility of issuing the required credit. The development of method of estimating fuzzy logic can be applied to other models of assessing the creditworthiness of a company: Davydov's model, Zaitseva's, Saifullina's, Kadykova's and others with appropriate modification
.