Scientific Journal of KubSAU

In this article we propose a method of determining the share or the significance (weight) of indicators of Beaver and risks R in the portfolio formed by these parameters allowing us to minimize the mean square error evaluating the effectiveness of the portfolio (risk) in the assessment of the financial condition of the companies investigated. The proposed method is the minimization of a quadratic form in variables satisfying lengthy conditions, i.e. the quadratic programming. This technique is implemented using four methods of optimization: analytical method, using built-in function minimization block given, the penalty function method and the gradient method. More so, this technique allows, as shown by the results of the computational experiments, the expert without routine statistical data processing to obtain additional information on the credit worthiness of the investigated enterprise and make a more informed conclusion about its financial condition, which speeds up the decision on granting a loan required by a company. Based on the techniques proposed in this paper, other techniques of assessing the creditworthiness of businesses may be constructed using the results of optimization theory based on well-established applied research methods: Method of evaluating the creditworthiness of Russia, Credit scoring method, the American method, method of Altman and others

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

In this article we have proposed a method using the apparatus of fuzzy sets theory in conjunction with the five-factor model of Altman to assess the creditworthiness of the investigated companies. The Altman model was improved in two ways: by using RMS integral approximation for the exact calculation of the quantitative credit assessment (probability of bankruptcy) and the application of the apparatus of fuzzy sets for ordered sets by the degree of confidence resulting probability